Multi-time-scale energy-carbon optimization method for integrated energy systems with integrated photovoltaic storage and charging

Abstract

The present invention relates to the technical field of energy-carbon scheduling of integrated energy systems, and provides a multi-time-scale energy-carbon optimization method for an integrated energy system including photovoltaic, storage and charging integration, comprising: establishing a photovoltaic, storage and charging integration system and an electric-thermal interconnected integrated energy system model, and constructing a coupling relationship model for the integrated energy system including photovoltaic, storage and charging integration; then, further setting a day-ahead and intraday multi-time-scale optimization scheduling strategy, and setting coupling connection conditions for the intraday rolling energy-carbon optimization scheduling and the day-ahead energy economic optimization scheduling; finally, through day-ahead and intraday optimization scheduling calculations, outputting data information on the energy-carbon optimization scheduling results of the integrated energy system. The present invention constructs a fine-grained model of an electric-thermal integrated energy system including photovoltaic, storage and charging integration and a day-ahead and intraday optimization scheduling strategy, which can provide reference and guidance for the multi-time-scale operation optimization, regulation and management of the integrated energy system, energy conservation, emission reduction and cost reduction analysis, source-load-storage energy economy and carbon emission tracking analysis, etc.

Description

Technical Field

[0001] The present invention relates to the technical field of energy-carbon scheduling of integrated energy systems, and in particular to a multi-time-scale energy-carbon optimization method for an integrated energy system including integrated photovoltaic storage and charging. Background Art

[0002] With the acceleration of global energy transition and increasingly stringent carbon emission controls, integrated energy systems (IESs) have attracted widespread attention as systems that enable efficient coupling and coordinated optimization of multiple energy sources. As an emerging energy utilization model, IESs, which integrate photovoltaics, energy storage, wind turbines, electric and thermal loads, gas turbines, and charging station clusters, achieve efficient energy utilization and flexible scheduling. They are becoming a crucial component of future energy systems, effectively addressing the difficulty in regulation caused by errors in source and load forecasting, while also providing flexible charging services and the supply of electric and thermal energy. They hold significant potential for energy conservation and emission reduction, as well as economic value.

[0003] Ensuring the coordinated optimization of integrated photovoltaic, storage, and charging systems with integrated electric and thermal energy systems, particularly achieving energy-carbon co-optimization at multiple time scales, has become a pressing technical challenge. Currently, the coordinated optimization of integrated photovoltaic, storage, and charging systems with integrated electric and thermal energy systems has not been fully studied, posing challenges to the energy balance and stable operation of integrated energy systems. Furthermore, existing research largely focuses on optimized scheduling at a single time scale, lacking in-depth exploration of multi-time-scale coordinated optimization. In actual operation, integrated energy systems require optimized scheduling at multiple time scales, including day-ahead and intraday. However, the existing technologies have the following problems: (1) There are deficiencies in the coordinated optimization operation of the integrated photovoltaic storage and charging system and the electric and thermal integrated energy system, multi-time scale optimization scheduling, and energy-carbon coordinated optimization, which makes it difficult to meet the needs of economic, efficient, stable, and low-carbon operation of the system; (2) The energy scheduling strategy under multiple time scales is not fully considered, resulting in the lack of flexibility and adaptability of the optimized scheduling strategy; (3) Carbon emission factors are ignored, and there is a lack of energy-carbon coordinated day-ahead and intra-day optimization scheduling strategies. The coupling relationship and dynamic change characteristics between multiple energy systems are ignored, which limits the overall efficiency of the energy system and makes it difficult to meet the urgent needs of energy conservation and emission reduction; (4) Most of them only focus on economic costs, and insufficient consideration is given to energy-carbon coordinated analysis, and there is a lack of systematic solutions for energy-carbon coordinated optimization. Summary of the Invention

[0004] The purpose of the present invention is to solve at least one technical problem in the background technology and provide a multi-time-scale energy-carbon optimization method for an integrated energy system with integrated photovoltaic storage and charging.

[0005] To achieve the above objectives, the present invention provides a multi-time-scale energy-carbon optimization method for an integrated energy system with integrated photovoltaic storage and charging, comprising:

[0006] Establish a photovoltaic, storage and charging integrated system model, including photovoltaic power generation model, electrical energy storage model, charging pile cluster model, and photovoltaic, storage and charging integrated system energy coupling balance model;

[0007] Establish an electric-thermal interconnected integrated energy system model, including a gas turbine model, a supplementary-fired waste heat boiler model, a fan power generation model, an electric energy coupling balance model, and a thermal energy coupling balance model;

[0008] The photovoltaic storage and charging integrated system model and the electric-thermal interconnected comprehensive energy system model are coupled and interconnected to form a coupling relationship model of the comprehensive energy system including photovoltaic storage and charging integration;

[0009] Set up a day-ahead energy economic optimization dispatch strategy for the integrated energy system coupling relationship model;

[0010] Set up a daily rolling energy-carbon optimization scheduling strategy for the integrated energy system coupling relationship model;

[0011] Set the coupling conditions between the intraday rolling energy-carbon optimization scheduling strategy and the day-ahead energy-economic optimization scheduling strategy. Once the coupling conditions are set, a comprehensive energy system is formed.

[0012] Input the integrated energy system operation initialization startup data information into the integrated energy system, and output the integrated energy system energy-carbon optimization scheduling result data information through the integrated energy system.

[0013] According to one aspect of the present invention, the photovoltaic power generation model includes: a mathematical model of a single photovoltaic module, a mathematical model of a photovoltaic array, and a photovoltaic power generation safe operation domain model;

[0014] The mathematical model of a single photovoltaic module is expressed as follows:

[0015] ;

[0016] Where: For photovoltaic modules at the moment The predicted power generation capacity; The power output of the photovoltaic module under standard test environment can be regarded as rated power; The photovoltaic modules generate electricity at the time Light intensity during operation, and light intensity in the working environment of photovoltaic modules under standard test conditions; The temperature adjustment factor for the photovoltaic module's power output, i.e., the temperature adjustment coefficient; Photovoltaic power generation at time Working temperature, working temperature of photovoltaic module power generation under standard test environment; Power generation for photovoltaic modules at all times Ambient temperature during operation; The operating rated temperature for generating electricity for photovoltaic modules;

[0017] The expression of the photovoltaic array mathematical model is as follows: ;

[0018] Where: The photovoltaic array at time The predicted power generation capacity; is the total number of PV modules in the PV array;

[0019] For photovoltaic modules at the moment The predicted power generation capacity; is the average total power generation efficiency of the photovoltaic array;

[0020] The expression of the photovoltaic power generation safe operation domain model is as follows:

[0021] ;

[0022] Where: The photovoltaic array at time The predicted power generation capacity; The photovoltaic array at time The predicted power generation capacity; The photovoltaic array at time The actual working power generation; is the maximum power generation of the photovoltaic array, which can be regarded as the installed capacity; To optimize the maximum allowed abandoned light rate within the scheduling cycle; To schedule the simulation run cycle;

[0023] The electric energy storage model consists of energy time domain relationship and operation safety domain;

[0024] The energy-time domain relationship expression of the electric energy storage model is as follows:

[0025] ;

[0026] Where: For electrical energy storage equipment at all times of storage capacity; For electrical energy storage equipment at all times of storage capacity; is the self-discharge rate of the electrical energy storage device; For electrical energy storage equipment at all times The discharge power; For electrical energy storage equipment at all times Charging power; Charging efficiency of electrical energy storage devices; is the discharge efficiency of the electrical energy storage device; Control the step resolution for scheduling simulation runs; It is the intermediate state variable in the linear transformation process of the electric energy storage device model; It is a large number of intermediate variables in the linear transformation process of the electric energy storage device model;

[0027] The operational safety domain expression of the electric energy storage model is as follows:

[0028] ;

[0029] Where: For electrical energy storage equipment at all times The discharge power; For electrical energy storage equipment at all times Charging power; The upper limit of the discharge power of the electric energy storage device; Upper limit of charging power for electric energy storage devices; For electrical energy storage equipment at all times of storage capacity; The lower limit factor of the real-time storage capacity of the energy storage device; The upper limit factor of the real-time storage capacity of the electric energy storage device; is the rated capacity of the electric energy storage device; The initial storage capacity of the energy storage device; The storage capacity of the energy storage device at the end of the operation cycle, that is, the storage capacity after the end of a scheduling simulation operation cycle, can also be used express; The matching degree of the energy storage device's initial and final states at the start and end of the scheduling simulation cycle. A value of 0 indicates no requirement, a value of 1 indicates a completely matching state, and other values ​​indicate an acceptable matching degree.

[0030] The expression of the charging pile cluster model is as follows:

[0031] ;

[0032] Where: For charging pile clusters at all times The percentage factor of the maximum interruptible charging load; For the integrated solar storage and charging system model at the moment Meet the actual charging pile cluster load power requirements; For charging pile clusters at all times The predicted charging load power; The maximum interruption charging load percentage coefficient allowed within the optimization scheduling period;

[0033] The expression of the energy coupling balance model of the integrated photovoltaic storage and charging system is as follows:

[0034] ;

[0035] Where: For the integrated solar storage and charging system model at the moment Power received from the distribution network; The upper limit of the power that the integrated solar-storage-charging system model can receive from the distribution network; For the integrated solar storage and charging system model at the moment Power delivered to the distribution network; The upper limit of the power delivered to the distribution network by the integrated solar-storage-charging system model; Capacity constraints of the distribution network interconnection lines for the integrated photovoltaic storage and charging system model; It is the intermediate state variable in the linear transformation process of the capacity constraint of the distribution network interconnection line in the integrated photovoltaic storage and charging system model; It is a large-valued variable in the intermediate process of the linear transformation of the capacity constraint of the distribution network interconnection line in the integrated photovoltaic storage and charging system model.

[0036] According to one aspect of the present invention, the gas turbine model includes: a gas turbine operation characteristic model and a gas turbine safe operation domain constraint;

[0037] The expression of the gas turbine operation characteristic model is as follows:

[0038] ;

[0039] Where: For gas turbines at the moment of electrical power; For gas turbines at the moment power generation efficiency; For gas turbines at the moment Fuel input; For gas turbines at the moment Thermal power; is the energy loss rate of the gas turbine; For gas turbines at the moment natural gas consumption rate; The calorific value of natural gas when burning natural gas in a gas turbine; For gas turbines at the moment The electrical load rate; is the polynomial coefficient of the gas turbine power generation efficiency characteristic curve, where the superscript is a polynomial power; For gas turbines at the moment The Boolean variable of the operating state of the gas turbine is 1 when the gas turbine is running and 0 when the gas turbine is stopped; For gas turbines at the moment operating costs; For gas turbines at the moment natural gas prices;

[0040] The expression of the gas turbine safe operation domain constraint is as follows: ;

[0041] Where: For gas turbines at the moment of electrical power; For gas turbines at the moment The running status Boolean variable, where the Boolean variable value is 1 when running and the Boolean variable value is 0 when stopped; is the cutting coefficient of the gas turbine; is the rated installed capacity of the gas turbine; is the ramp rate of the gas turbine under electrical power; is the electrical power ramp-up rate of the gas turbine; The upper limit of the number of gas turbine starts within the optimal scheduling cycle; To schedule the simulation run cycle; Control the step resolution for scheduling simulation runs;

[0042] The expression of the supplementary combustion waste heat boiler model is as follows:

[0043] ;

[0044] Where: For the supplementary burning waste heat boiler at time Heating power; For the supplementary burning waste heat boiler at time Heating power; is the heating efficiency of the supplementary-fired waste heat boiler; For the supplementary burning waste heat boiler at time Fuel input of supplementary natural gas; It is the comprehensive efficiency of high-temperature flue gas recovery of the supplementary-fired waste heat boiler; For the supplementary burning waste heat boiler at time Amount of recovered high-temperature flue gas; For the supplementary burning waste heat boiler at time natural gas consumption rate; The calorific value of natural gas when burning natural gas in a supplementary-fired waste heat boiler; For the supplementary burning waste heat boiler at time The operating status Boolean variable, wherein the Boolean variable value is 1 when the supplementary-fired waste heat boiler is running, and the Boolean variable value is 0 when the supplementary-fired waste heat boiler is stopped; is the trip coefficient of the supplementary-fired waste heat boiler; is the rated installed capacity of the supplementary-fired waste heat boiler; is the ramp rate of the electric power of the supplementary-fired waste heat boiler; The electric power ramp-up rate of the supplementary-fired waste heat boiler; Control the step resolution for scheduling simulation runs; For the supplementary burning waste heat boiler at time operating costs; For the supplementary burning waste heat boiler at time natural gas prices;

[0045] The wind turbine power generation model includes: a wind turbine power generation operation characteristic model and wind turbine power generation safety operation constraints;

[0046] The expression of the wind turbine power generation operation characteristic model is as follows:

[0047] ;

[0048] Where: For wind turbines at time The maximum predicted output power; is the rated maximum output power of the wind turbine; For wind turbines at time Actual working wind speed; The minimum starting wind speed for the wind turbine; is the rated operating wind speed of the wind turbine; The maximum operating wind speed of the wind turbine; Different fitting coefficients for predicting output curves of wind turbines;

[0049] The expression of the wind turbine power generation safety operation constraint is as follows:

[0050] ;

[0051] Where: For wind turbines at time The maximum predicted output power; Generating electricity for wind turbines at all times The actual power input into the electric-thermal interconnected integrated energy system model; is the penetration coefficient of wind turbine power generation; For the electric and thermal interconnected integrated energy system model at time Total power input power; To optimize the wind curtailment rate within the dispatch cycle; To optimize the maximum wind curtailment rate allowed within the dispatch cycle; is the upper limit of the permeability coefficient of wind turbine power generation;

[0052] The expression of the electric energy coupling balance model is as follows:

[0053] ;

[0054] Where: For distribution network at all times Power input to the electric-thermal interconnected integrated energy system model; For the electric and thermal interconnected integrated energy system model at time Power delivered to the distribution network; For the electric and thermal interconnected integrated energy system model at time Meet the power requirements of the electrical load; It is the intermediate state variable in the linear transformation process of the interconnection line capacity constraint of the electric-thermal interconnected integrated energy system model; It is a large number value variable in the intermediate process of the linear transformation of the capacity constraint of the interconnection line of the electric-thermal interconnected integrated energy system model; The upper limit of power delivered to the distribution grid for the electric-thermal interconnected integrated energy system model; The upper limit of the power input from the distribution network to the electric and thermal interconnected integrated energy system model;

[0055] The expression of the thermal energy coupling balance model is as follows: ;

[0056] Where: For the electric and thermal interconnected integrated energy system model at time Meet the heat load power requirements.

[0057] According to one aspect of the present invention, the expression of the coupling relationship model of the integrated energy system with integrated photovoltaic storage and charging is as follows:

[0058] ;

[0059] Where: For the integrated solar storage and charging system model at the moment Power delivered to the distribution network; For the electric and thermal interconnected integrated energy system model at time Power delivered to the distribution network; Transmit power to the grid connection line of the integrated energy system coupling relationship model including photovoltaic storage and charging integration; The upper limit of transmission power of the interconnection line of the grid connection point of the coupling relationship model of the integrated energy system with integrated photovoltaic storage and charging; For the integrated solar storage and charging system model at the moment Power received from the distribution network; For distribution network at all times Power input to the electric-thermal interconnected integrated energy system model; For gas turbines at the moment Thermal power; For the supplementary burning waste heat boiler at time The amount of recovered high-temperature flue gas.

[0060] According to one aspect of the present invention, setting a day-ahead energy economic optimization scheduling strategy for the integrated energy system coupling relationship model includes:

[0061] The scheduling simulation operation cycle of the day-ahead energy economic optimization scheduling of the integrated energy system coupling relationship model with integrated photovoltaic storage and charging is 24 hours a day, the scheduling simulation operation control step resolution is 1 hour, and a total of 24 control steps;

[0062] The expression of the day-ahead energy economic optimization scheduling strategy of the integrated energy system coupling relationship model with integrated photovoltaic storage and charging is as follows:

[0063] ;

[0064] Where: The total economic cost of day-ahead energy economic optimization scheduling for a coupled relationship model of an integrated energy system including photovoltaic storage and charging; The total gas consumption cost of the day-ahead energy economic optimization scheduling of the coupled relationship model of the integrated energy system including photovoltaic storage and charging; The total grid-connected electricity purchase cost for the day-ahead energy economic optimization dispatch of the integrated energy system coupling relationship model including photovoltaic storage and charging integration; The total penalty cost of interrupted charging load in the day-ahead energy economic optimization scheduling of the integrated energy system coupling relationship model including photovoltaic storage and charging integration; A coupling relationship model for an integrated energy system with integrated photovoltaic, storage and charging, and the total revenue of charging services for day-ahead energy economic optimization scheduling; For gas turbines at the moment operating costs; For the supplementary burning waste heat boiler at time operating costs; A coupling relationship model of an integrated energy system with integrated photovoltaic storage and charging for day-ahead energy economic optimization scheduling at time Time-of-use electricity prices at the grid connection point; Transmit power to the grid connection line of the integrated energy system coupling relationship model including photovoltaic storage and charging integration; For charging pile clusters at all times The percentage factor of the maximum interruptible charging load; For charging pile clusters at all times The predicted charging load power; is the polynomial coefficient of the penalty characteristic curve for interrupting charging load, where the superscript is a polynomial power; For the integrated solar storage and charging business at all times The charging electricity fee is the time-of-use electricity price; For the integrated solar storage and charging business at all times Time-sharing price of service fee; For the integrated solar storage and charging system model at the moment Meet the actual charging pile cluster load power requirements; To schedule the simulation run cycle; Control the step resolution for scheduling simulation runs.

[0065] According to one aspect of the present invention, setting a daily rolling energy-carbon optimization scheduling strategy for the integrated energy system coupling relationship model includes:

[0066] The intraday rolling cycle of the intraday rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with integrated photovoltaic storage and charging is once every 4 hours. There are 6 rolling optimization schedulings in 24 hours a day. The scheduling simulation operation cycles of the 1st, 2nd, 3rd, 4th, 5th and 6th rolling optimization scheduling are 24 hours, 20 hours, 16 hours, 12 hours, 8 hours and 4 hours respectively. The control step resolution of each scheduling simulation operation is 15 minutes. The scheduling simulation operation cycles of the 1st, 2nd, 3rd, 4th, 5th and 6th rolling optimization scheduling are 96, 80, 64, 48, 32 and 16 control steps respectively. The scheduling simulation operation control step resolution of a day-ahead energy and economic optimization scheduling includes 4 intraday rolling energy and carbon optimization scheduling simulation operation control step resolutions.

[0067] The intraday rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model containing integrated photovoltaic storage and charging performs rolling optimization scheduling on the basis of the results of the energy-economic optimization scheduling of the integrated energy system coupling relationship model containing integrated photovoltaic storage and charging on the day before. The intraday rolling energy-carbon optimization scheduling generally tracks the results of the energy-economic optimization scheduling on the day before. The results of the energy-economic optimization scheduling on the day before include the gas turbine output scheduling results, the grid connection point interconnection line transmission power scheduling results, the supplementary combustion type waste heat boiler heating power scheduling results, and the electric energy storage equipment storage capacity scheduling results. The intraday rolling energy-carbon optimization scheduling is only adjusted on the basis of the results of the energy-economic optimization scheduling on the day before, and the controllable unit equipment and the grid connection point power are adjusted to eliminate the power balance shortfall caused by the source-load power prediction error;

[0068] The intraday rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with integrated photovoltaic storage and charging is updated every 4 hours to obtain the latest photovoltaic power generation, wind turbine power generation, electric load, thermal load, and charging pile cluster predicted power, and the latest source-load prediction data is input into the current rolling optimization scheduling. The control step resolution of the first 16 control steps of the scheduling simulation operation cycle of each rolling optimization scheduling is the latest source-load prediction data, and the scheduling result within the scheduling simulation operation cycle of the previous rolling optimization scheduling is used as the initial quantity of the next rolling optimization scheduling;

[0069] The intraday rolling energy-carbon optimization scheduling strategy of the integrated energy system coupling relationship model with integrated photovoltaic storage and charging, while taking into account the energy economic operation cost, further considers the system carbon emission cost and rolling adjustment cost to perform energy-carbon coordinated optimization;

[0070] The expression of the daily rolling energy-carbon optimization scheduling strategy of the integrated energy system coupling relationship model with integrated photovoltaic storage and charging is as follows:

[0071] ;

[0072] Where: The total carbon emission cost of the daily rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model including photovoltaic storage and charging; The total economic cost of daily rolling energy and carbon optimization scheduling for the coupled relationship model of the integrated energy system including photovoltaic storage and charging; Adjust the total cost of the daily rolling energy-carbon optimization scheduling plan for the integrated energy system coupling relationship model including photovoltaic storage and charging; The equivalent carbon emission coefficient generated by purchasing unit electricity for the integrated energy system coupling relationship model including photovoltaic storage and charging; The equivalent carbon emission coefficient generated by purchasing a unit of natural gas for the integrated energy system coupling relationship model including photovoltaic storage and charging; is the price per unit of equivalent carbon emissions; is the carbon emission intensity factor of the gas turbine; is the carbon emission quota factor per unit power generated by the gas turbine; is the carbon emission intensity factor of the supplementary-fired waste heat boiler; is the carbon emission quota factor per unit heating power of the combustion type waste heat boiler; The total economic cost of day-ahead energy economic optimization scheduling for a coupled relationship model of an integrated energy system including photovoltaic storage and charging; For the supplementary burning waste heat boiler at time Fuel input of supplementary natural gas; Adjust the cost factor per unit power of gas turbine power generation; For gas turbines at the moment of electrical power; The gas turbine is scheduled at time under the daily rolling energy-carbon optimization of electrical power; The adjustment cost coefficient for the unit power change of the transmission power of the tie line at the grid connection point; Transmit power to the grid connection line of the integrated energy system coupling relationship model including photovoltaic storage and charging integration; The transmission power of the interconnection line of the grid connection point is based on the coupling relationship model of the integrated energy system with integrated photovoltaic storage and charging under the daily rolling energy and carbon optimization scheduling; Adjust the cost coefficient per unit power of the heating output of the supplementary-fired waste heat boiler; For the supplementary burning waste heat boiler at time Heating power; The supplementary combustion waste heat boiler is scheduled at time under the daily rolling energy and carbon optimization Heating power; Adjusting the cost factor per unit capacity of electric energy storage equipment; For electrical energy storage equipment at all times of storage capacity; For the daily rolling energy and carbon optimization scheduling of electric energy storage equipment at time of storage capacity; The scheduling simulation operation cycle under the daily rolling energy and carbon optimization scheduling; Control the step resolution for scheduling simulation runs.

[0073] According to one aspect of the present invention, the coupling connection conditions for setting the intraday rolling energy-carbon optimization scheduling strategy and the day-ahead energy-economic optimization scheduling strategy include:

[0074] Adjust quantity constraints, re-update the latest source-load forecast data input model, and transform the single-target intraday rolling energy-carbon optimization scheduling model;

[0075] The expression of the adjustment constraint in the coupling connection condition is as follows:

[0076] ;

[0077] Where: For gas turbines at the moment of electrical power; The gas turbine is scheduled at time under the daily rolling energy-carbon optimization of electrical power; Adjust margin factors for intraday rolling of gas turbines; is the rated installed capacity of the gas turbine; Transmit power to the grid connection line of the integrated energy system coupling relationship model including photovoltaic storage and charging integration; The transmission power of the interconnection line of the grid connection point is based on the coupling relationship model of the integrated energy system with integrated photovoltaic storage and charging under the daily rolling energy and carbon optimization scheduling; The daily rolling adjustment margin coefficient for the transmission power of the grid connection line; The upper limit of transmission power of the interconnection line of the grid connection point of the coupling relationship model of the integrated energy system with integrated photovoltaic storage and charging; For the supplementary burning waste heat boiler at time Heating power; The supplementary combustion waste heat boiler is scheduled at time under the daily rolling energy and carbon optimization Heating power; It is the daily rolling adjustment margin coefficient of the supplementary-fired waste heat boiler; is the rated installed capacity of the supplementary-fired waste heat boiler; For electrical energy storage equipment at all times of storage capacity; For the daily rolling energy and carbon optimization scheduling of electric energy storage equipment at time of storage capacity; Adjust the margin factor for the electric energy storage equipment on a rolling basis within the day; is the rated capacity of the electric energy storage device;

[0078] The expression for re-updating the latest source-load prediction data input model in the coupling connection condition is as follows:

[0079] ;

[0080] Where: For wind turbines at time The maximum predicted output power; For the electric and thermal interconnected integrated energy system model at time Meet the power requirements of the electrical load; For the electric and thermal interconnected integrated energy system model at time Meet the heat load power requirements; The photovoltaic array in the photovoltaic storage and charging integrated system model at time The predicted power generation capacity; For charging pile clusters at all times The predicted charging load power; In order to update and obtain the latest source load forecast data, the corresponding values ​​are assigned to the wind turbines at time The maximum predicted output power The electric and thermal interconnected integrated energy system model at the moment Meet the power demand of electrical load The electric and thermal interconnected integrated energy system model at the moment Meet the heat load power requirements Photovoltaic array at the moment Forecasted power generation and charging pile cluster at all times Predicted charging load power The resolution of the first 16 control steps of each rolling optimization scheduling simulation operation cycle; Reassign symbols after data update; A set of scheduling simulation run cycles for each rolling optimization schedule; The latest source-load power forecast is updated every 4 hours for the daily rolling energy-carbon optimization scheduling of the integrated energy system with integrated photovoltaic storage and charging; The scheduling simulation operation cycle under the daily rolling energy and carbon optimization scheduling;

[0081] The expression of the transformed single-objective intra-day rolling energy-carbon optimization scheduling model in the coupling connection condition is as follows:

[0082] ;

[0083] Where: The total carbon emission cost of the daily rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model including photovoltaic storage and charging; The total economic cost of daily rolling energy and carbon optimization scheduling for the coupled relationship model of the integrated energy system including photovoltaic storage and charging; Adjust the total cost of the daily rolling energy-carbon optimization scheduling plan for the integrated energy system coupling relationship model including photovoltaic storage and charging; are different weight coefficients corresponding to different single-objective optimization functions.

[0084] To achieve the above objectives, the present invention further provides a multi-time-scale energy-carbon optimization system for an integrated energy system with integrated photovoltaic storage and charging, comprising:

[0085] Data information acquisition module, which obtains the energy system operation initialization startup data information;

[0086] The photovoltaic, storage and charging integrated system model construction module establishes the photovoltaic, storage and charging integrated system model based on the initial startup data information, including the photovoltaic power generation model, the electric energy storage model, the charging pile cluster model, and the photovoltaic, storage and charging integrated system energy coupling balance model;

[0087] The electric-thermal interconnected integrated energy system model construction module establishes the electric-thermal interconnected integrated energy system model based on the initial startup data information, including the gas turbine model, the supplementary-fired waste heat boiler model, the fan power generation model, the electric energy coupling balance model, and the thermal energy coupling balance model;

[0088] The coupling relationship model acquisition module couples and interconnects the photovoltaic storage and charging integrated system model with the electric-thermal interconnected comprehensive energy system model to form a coupling relationship model of the comprehensive energy system including photovoltaic storage and charging integration;

[0089] The day-ahead energy and economic optimization scheduling strategy setting module sets the day-ahead energy and economic optimization scheduling strategy for the integrated energy system coupling relationship model;

[0090] The intraday rolling energy-carbon optimization scheduling strategy setting module sets the intraday rolling energy-carbon optimization scheduling strategy for the integrated energy system coupling relationship model;

[0091] The coupling connection condition setting module sets the coupling connection conditions between the intraday rolling energy-carbon optimization scheduling strategy and the day-ahead energy-economic optimization scheduling strategy. After the coupling connection conditions are set, a comprehensive energy system is formed;

[0092] The result output module inputs the energy system operation initialization startup data information into the integrated energy system, and outputs the integrated energy system energy-carbon optimization scheduling result data information through the integrated energy system.

[0093] To achieve the above-mentioned objectives, the present invention also provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and runnable on the processor. When the computer program is executed by the processor, the multi-time-scale energy-carbon optimization method for the integrated energy system with integrated photovoltaic storage and charging as described above is implemented.

[0094] To achieve the above-mentioned objectives, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the multi-time-scale energy-carbon optimization method for the integrated energy system with integrated photovoltaic storage and charging is implemented as described above.

[0095] According to the solution of the present invention, the present invention fully considers the multi-time-scale energy-carbon synergistic operation scenarios of the integrated photovoltaic storage and charging system and the electric thermal integrated energy system, and establishes fine-grained mathematical models such as photovoltaic power generation, electrical energy storage, wind turbine power generation, charging pile clusters, gas turbines, supplementary combustion type waste heat boilers, and grid connection points. This is conducive to the application and promotion of electric thermal integrated energy system engineering containing the integrated photovoltaic storage and charging system and the real-time and refined analysis of its operating status;

[0096] Based on the actual needs of energy conservation, cost reduction and carbon reduction in engineering applications, this paper proposes a day-ahead and intraday optimization scheduling strategy for an electric-thermal integrated energy system including an integrated photovoltaic storage and charging system. This effectively solves the technical difficulties of coordinated multi-scenario optimization operation of the integrated photovoltaic storage and charging system and the electric-thermal integrated energy system, energy-carbon operation characteristic analysis, and multi-time-scale fine-grained model construction.

[0097] The present invention constructs an overall full-process detailed plan for the equipment unit model, coupling relationship model, coupling connection condition model, day-ahead energy economic optimization scheduling strategy, and intraday rolling energy-carbon optimization scheduling strategy of the integrated energy system containing integrated photovoltaic storage and charging, thereby providing reference and guidance for multi-time scale operation optimization and control management, energy conservation, emission reduction and cost reduction analysis, source-load storage energy economy and carbon emission tracking analysis, etc. of the integrated energy system containing integrated photovoltaic storage and charging. BRIEF DESCRIPTION OF THE DRAWINGS

[0098] Figure 1 The flowchart schematically shows a multi-time-scale energy-carbon optimization method for an integrated energy system with integrated photovoltaic storage and charging according to an embodiment of the present invention. DETAILED DESCRIPTION

[0099] The present invention will now be discussed with reference to exemplary embodiments. It should be understood that the embodiments discussed are only intended to enable those skilled in the art to better understand and implement the present invention, rather than to imply any limitation on the scope of the present invention.

[0100] As used herein, the term "including" and variations thereof are to be interpreted as open-ended terms meaning "including, but not limited to." The term "based on" is to be interpreted as "based, at least in part, on." The terms "one embodiment" and "an embodiment" are to be interpreted as "at least one embodiment."

[0101] Figure 1 The flowchart schematically shows a multi-time-scale energy-carbon optimization method for an integrated energy system including photovoltaic storage and charging according to an embodiment of the present invention. Figure 1 As shown in this embodiment, the multi-time scale energy-carbon optimization method of the integrated energy system with integrated photovoltaic storage and charging is as follows: Figure 1 As shown, the following steps are included:

[0102] (1) Establishing a photovoltaic storage and charging integrated system model;

[0103] The photovoltaic storage and charging integrated system model includes photovoltaic power generation model, electric energy storage model, charging pile cluster model, and photovoltaic storage and charging integrated system energy coupling balance model;

[0104] (1a) Photovoltaic power generation model;

[0105] The photovoltaic power generation model includes the mathematical model of a single photovoltaic module, the mathematical model of a photovoltaic array, and the photovoltaic power generation safe operation domain model.

[0106] (1a-1) Mathematical model of a single photovoltaic module;

[0107] The mathematical model of a single photovoltaic module is expressed as follows:

[0108] ;

[0109] Where: For photovoltaic modules at the moment The predicted power generation capacity; The power output of the photovoltaic module under standard test environment can be regarded as rated power; The photovoltaic modules generate electricity at the time Light intensity during operation, and light intensity in the working environment of photovoltaic modules under standard test conditions; The temperature adjustment factor for the photovoltaic module's power output, i.e., the temperature adjustment coefficient; Photovoltaic power generation at time Working temperature, working temperature of photovoltaic module power generation under standard test environment; Power generation for photovoltaic modules at all times Ambient temperature during operation; The operating rated temperature for generating electricity for photovoltaic modules;

[0110] (1a-2) Mathematical model of photovoltaic array;

[0111] The mathematical model of the photovoltaic array is expressed as follows: ;

[0112] Where: The photovoltaic array at time The predicted power generation capacity; is the total number of PV modules in the PV array; For photovoltaic modules at the moment The predicted power generation capacity; is the average total power generation efficiency of the photovoltaic array;

[0113] (1a-3) Photovoltaic power generation safe operation domain model;

[0114] The expression of the photovoltaic power generation safe operation domain model is as follows:

[0115] ;

[0116] Where: The photovoltaic array in the photovoltaic storage and charging integrated system model at time The predicted power generation capacity; The photovoltaic array at time The predicted power generation capacity; The photovoltaic array at time The actual working power generation; is the maximum power generation of the photovoltaic array, which can be regarded as the installed capacity; To optimize the maximum allowed abandoned light rate within the scheduling cycle; To schedule the simulation run cycle;

[0117] (1b) Electric energy storage model;

[0118] The electric energy storage model consists of the energy time domain relationship and the operation safety domain.

[0119] The energy-time domain relationship expression of the electric energy storage model is as follows:

[0120] ;

[0121] Where: For electrical energy storage equipment at all times of storage capacity; For electrical energy storage equipment at all times of storage capacity; is the self-discharge rate of the electrical energy storage device; For electrical energy storage equipment at all times The discharge power; For electrical energy storage equipment at all times Charging power; Charging efficiency of electrical energy storage devices; is the discharge efficiency of the electrical energy storage device; Control the step resolution for scheduling simulation runs; It is the intermediate state variable in the linear transformation process of the electric energy storage device model; It is a large number of intermediate variables in the linear transformation process of the electric energy storage device model;

[0122] The operational safety domain expression of the electric energy storage model is as follows:

[0123] ;

[0124] Where: For electrical energy storage equipment at all times The discharge power; For electrical energy storage equipment at all times Charging power; The upper limit of the discharge power of the electric energy storage device; Upper limit of charging power for electric energy storage devices; For electrical energy storage equipment at all times of storage capacity; The lower limit factor of the real-time storage capacity of the energy storage device; The upper limit factor of the real-time storage capacity of the energy storage device; is the rated capacity of the electric energy storage device; The initial storage capacity of the energy storage device; The storage capacity of the energy storage device at the end of the operation cycle, that is, the storage capacity after the end of a scheduling simulation operation cycle, can also be used express; The matching degree of the energy storage device's initial and final states at the start and end of the scheduling simulation cycle. A value of 0 indicates no requirement, a value of 1 indicates a completely matching state, and other values ​​indicate an acceptable matching degree.

[0125] (1c) Charging pile cluster model;

[0126] The expression of the charging pile cluster model is as follows:

[0127] ;

[0128] Where: For charging pile clusters at all times The percentage factor of the maximum interruptible charging load; For the integrated solar storage and charging system model at the moment Meet the actual charging pile cluster load power requirements; For charging pile clusters at all times The predicted charging load power; The maximum interruption charging load percentage coefficient allowed within the optimization scheduling period;

[0129] (1d) Energy coupling balance model of integrated photovoltaic storage and charging system;

[0130] The expression of the energy coupling balance model of the integrated photovoltaic storage and charging system is as follows:

[0131] ;

[0132] Where: The photovoltaic array at time The actual working power generation; For electrical energy storage equipment at all times The discharge power; For the integrated solar storage and charging system model at the moment Power received from the distribution network; The upper limit of the power that the integrated solar-storage-charging system model can receive from the distribution network; For electrical energy storage equipment at all times Charging power; For the integrated solar storage and charging system model at the moment Power delivered to the distribution network; The upper limit of the power delivered to the distribution network by the integrated solar-storage-charging system model; For the integrated solar storage and charging system model at the moment Meet the actual charging pile cluster load power requirements; Capacity constraints of the distribution network interconnection lines for the integrated photovoltaic storage and charging system model; It is the intermediate state variable in the linear transformation process of the capacity constraint of the distribution network interconnection line in the integrated photovoltaic storage and charging system model; It is a large-valued variable in the intermediate process of the linear transformation of the capacity constraint of the distribution network interconnection line in the integrated photovoltaic storage and charging system model.

[0133] (2) Establish an integrated energy system model for electric and thermal interconnection;

[0134] The electric-thermal interconnected integrated energy system model includes a gas turbine model, a supplementary-fired waste heat boiler model, a fan power generation model, an electric energy coupling balance model, and a thermal energy coupling balance model.

[0135] (2a) Gas turbine model;

[0136] The gas turbine model includes the gas turbine operating characteristic model and the gas turbine safe operating domain constraints.

[0137] The expression of the gas turbine operation characteristic model is as follows:

[0138] ;

[0139] Where: For gas turbines at the moment of electrical power; For gas turbines at the moment power generation efficiency; For gas turbines at the moment Fuel input; For gas turbines at the moment Thermal power; is the energy loss rate of the gas turbine; For gas turbines at the moment natural gas consumption rate; The calorific value of natural gas when burning natural gas in a gas turbine; For gas turbines at the moment The electrical load rate; is the polynomial coefficient of the gas turbine power generation efficiency characteristic curve, where the superscript is a polynomial power; For gas turbines at the moment The Boolean variable of the operating state of the gas turbine is 1 when the gas turbine is running and 0 when the gas turbine is stopped; For gas turbines at the moment operating costs; For gas turbines at the moment natural gas prices;

[0140] The expression of gas turbine safe operation domain constraint is as follows:

[0141] ;

[0142] Where: For gas turbines at the moment The running status Boolean variable, where the Boolean variable value is 1 when running and the Boolean variable value is 0 when stopped; For gas turbines at the moment The running status Boolean variable, where the Boolean variable value is 1 when running and the Boolean variable value is 0 when stopped; is the cutting coefficient of the gas turbine; is the rated installed capacity of the gas turbine; For gas turbines at the moment of electrical power; is the ramp rate of the gas turbine under electrical power; is the electrical power ramp-up rate of the gas turbine; The upper limit of the number of gas turbine starts within the optimal scheduling cycle; To schedule the simulation run cycle; Control the step resolution for scheduling simulation runs;

[0143] (2b) Supplementary-fired waste heat boiler model;

[0144] The expression of the supplementary-fired waste heat boiler model is as follows:

[0145] ;

[0146] Where: For the supplementary burning waste heat boiler at time Heating power; is the heating efficiency of the supplementary-fired waste heat boiler; For the supplementary burning waste heat boiler at time Fuel input of supplementary natural gas; It is the comprehensive efficiency of high-temperature flue gas recovery of the supplementary-fired waste heat boiler; For the supplementary burning waste heat boiler at time Amount of recovered high-temperature flue gas; For the supplementary burning waste heat boiler at time natural gas consumption rate; The calorific value of natural gas when burning natural gas in a supplementary-fired waste heat boiler; For the supplementary burning waste heat boiler at time The operating status Boolean variable, wherein the Boolean variable value is 1 when the supplementary-fired waste heat boiler is running, and the Boolean variable value is 0 when the supplementary-fired waste heat boiler is stopped; is the trip coefficient of the supplementary-fired waste heat boiler; is the rated installed capacity of the supplementary-fired waste heat boiler; is the ramp rate of the electric power of the supplementary-fired waste heat boiler; The electric power ramp-up rate of the supplementary-fired waste heat boiler; Control the step resolution for scheduling simulation runs; For the supplementary burning waste heat boiler at time operating costs; For the supplementary burning waste heat boiler at time natural gas prices;

[0147] (2c) Wind turbine power generation model;

[0148] The wind turbine power generation model includes the wind turbine power generation operation characteristic model and the wind turbine power generation safety operation constraints.

[0149] The expression of the wind turbine power generation operation characteristic model is as follows:

[0150] ;

[0151] Where: For wind turbines at time The maximum predicted output power; is the rated maximum output power of the wind turbine; For wind turbines at time Actual working wind speed; The minimum starting wind speed for the wind turbine; is the rated operating wind speed of the wind turbine; The maximum operating wind speed of the wind turbine; Different fitting coefficients for predicting output curves of wind turbines;

[0152] The expression of wind turbine power generation safe operation constraint is as follows:

[0153] ;

[0154] Where: For wind turbines at time The maximum predicted output power; Generating electricity for wind turbines at all times The actual power input into the electric-thermal interconnected integrated energy system model; is the penetration coefficient of wind turbine power generation; For the electric and thermal interconnected integrated energy system model at time Total power input power; To optimize the wind curtailment rate within the dispatch cycle; To optimize the maximum wind curtailment rate allowed within the dispatch cycle; is the upper limit of the permeability coefficient of wind turbine power generation; To schedule the simulation run cycle;

[0155] (2d) Electric energy coupling balance model;

[0156] The expression of the electric energy coupling balance model is as follows:

[0157] ;

[0158] Where: For gas turbines at the moment of electrical power; For distribution network at all times Power input to the electric-thermal interconnected integrated energy system model; For the electric and thermal interconnected integrated energy system model at time Power delivered to the distribution network; For the electric and thermal interconnected integrated energy system model at time Meet the power requirements of the electrical load; It is the intermediate state variable in the linear transformation process of the interconnection line capacity constraint of the electric-thermal interconnected integrated energy system model; It is a large number value variable in the intermediate process of the linear transformation of the capacity constraint of the interconnection line of the electric-thermal interconnected integrated energy system model; The upper limit of power delivered to the distribution grid for the electric-thermal interconnected integrated energy system model; The upper limit of the power input from the distribution network to the electric and thermal interconnected integrated energy system model;

[0159] (2e) Thermal energy coupled balance model;

[0160] The expression of the thermal energy coupling balance model is as follows: ;

[0161] Where: For the supplementary burning waste heat boiler at time Heating power; For the electric and thermal interconnected integrated energy system model at time Meet the heat load power requirements.

[0162] (3) Construct a coupling relationship model of an integrated energy system with integrated photovoltaic, storage and charging;

[0163] The coupling relationship model of the integrated energy system with integrated photovoltaic storage and charging is to organically couple and interconnect the photovoltaic storage and charging integrated system model with the electric and thermal interconnected integrated energy system model to form an overall multi-energy system.

[0164] The expression of the coupling relationship model of the integrated energy system with integrated photovoltaic storage and charging is as follows:

[0165] ;

[0166] Where: For the integrated solar storage and charging system model at the moment Power delivered to the distribution network; For the electric and thermal interconnected integrated energy system model at time Power delivered to the distribution network; Transmit power to the interconnection line of the integrated energy system model with integrated photovoltaic storage and charging; The upper limit of transmission power for the interconnection line of the integrated energy system model with integrated photovoltaic storage and charging; For the integrated solar storage and charging system model at the moment Power received from the distribution network; For distribution network at all times Power input to the electric-thermal interconnected integrated energy system model; For gas turbines at the moment Thermal power; For the supplementary burning waste heat boiler at time The amount of recovered high-temperature flue gas.

[0167] (4) Setting up a day-ahead energy economic optimization scheduling strategy for the integrated energy system coupling relationship model;

[0168] The scheduling simulation operation cycle of the day-ahead energy economic optimization scheduling strategy for the integrated energy system coupling relationship model with integrated photovoltaic storage and charging is 24 hours a day, with a scheduling simulation operation control step resolution of 1 hour, for a total of 24 control steps;

[0169] The expression of the day-ahead energy economic optimization scheduling strategy of the integrated energy system coupling relationship model including photovoltaic storage and charging is as follows:

[0170] ;

[0171] Where: The total economic cost of day-ahead energy economic optimization scheduling for a coupled relationship model of an integrated energy system including photovoltaic storage and charging; The total gas consumption cost of the day-ahead energy economic optimization scheduling of the coupled relationship model of the integrated energy system including photovoltaic storage and charging; The total grid-connected electricity purchase cost for the day-ahead energy economic optimization dispatch of the integrated energy system coupling relationship model including photovoltaic storage and charging integration; The total penalty cost of interrupted charging load in the day-ahead energy economic optimization scheduling of the integrated energy system coupling relationship model including photovoltaic storage and charging integration; A coupling relationship model for an integrated energy system with integrated photovoltaic, storage and charging, and the total revenue of charging services for day-ahead energy economic optimization scheduling; For gas turbines at the moment operating costs; For the supplementary burning waste heat boiler at time operating costs; A coupling relationship model of an integrated energy system with integrated photovoltaic storage and charging for day-ahead energy economic optimization scheduling at time Time-of-use electricity prices at the grid connection point; Transmit power to the grid connection line of the integrated energy system coupling relationship model including photovoltaic storage and charging integration; For charging pile clusters at all times The percentage factor of the maximum interruptible charging load; For charging pile clusters at all times The predicted charging load power; is the polynomial coefficient of the penalty characteristic curve for interrupting charging load, where the superscript is a polynomial power; The charging business of the integrated solar storage and charging system model is The charging electricity fee is the time-of-use electricity price; The charging business of the integrated solar storage and charging system model is Time-sharing price of service fee; For the integrated solar storage and charging system model at the moment Meet the actual charging pile cluster load power requirements; To schedule the simulation run cycle; Control the step resolution for scheduling simulation runs.

[0172] (5) Setting up a daily rolling energy-carbon optimization scheduling strategy for the integrated energy system coupling relationship model;

[0173] The intraday rolling cycle of the intraday rolling energy-carbon optimization scheduling strategy of the integrated energy system coupling relationship model with integrated photovoltaic storage and charging is once every 4 hours. There are 6 rolling optimization schedulings in 24 hours a day. The scheduling simulation operation cycles of the 1st, 2nd, 3rd, 4th, 5th and 6th rolling optimization scheduling are 24 hours, 20 hours, 16 hours, 12 hours, 8 hours and 4 hours respectively. The control step resolution of each scheduling simulation operation is 15 minutes. The scheduling simulation operation cycles of the 1st, 2nd, 3rd, 4th, 5th and 6th rolling optimization scheduling are 96, 80, 64, 48, 32 and 16 control steps respectively. The scheduling simulation operation control step resolution of a day-ahead energy and economic optimization scheduling includes 4 intraday rolling energy and carbon optimization scheduling simulation operation control step resolutions.

[0174] The intraday rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model including photovoltaic storage and charging is carried out on the basis of the results of the energy-economic optimization scheduling of the integrated energy system coupling relationship model including photovoltaic storage and charging the day before. The intraday rolling energy-carbon optimization scheduling generally tracks the results of the energy-economic optimization scheduling of the day before. The results of the energy-economic optimization scheduling of the day before include the gas turbine output scheduling results, the grid connection point interconnection line transmission power scheduling results, the supplementary combustion type waste heat boiler heating power scheduling results, and the electric energy storage equipment storage capacity scheduling results. The intraday rolling energy-carbon optimization scheduling is only adjusted based on the results of the energy-economic optimization scheduling of the day before. The power of the controllable unit equipment and the grid connection point is adjusted to eliminate the power balance shortfall caused by the source-load power forecast error.

[0175] The daily rolling energy-carbon optimization scheduling of the integrated energy system with integrated photovoltaic storage and charging is updated every 4 hours to obtain the latest predicted power of photovoltaic power generation, wind turbine power generation, electrical load, thermal load, and charging pile cluster. The latest source-load prediction data is input into the current rolling optimization scheduling. The resolution of the first 16 control steps of the scheduling simulation operation cycle of each rolling optimization scheduling is the latest source-load prediction data. The scheduling result within the scheduling simulation operation cycle of the previous rolling optimization scheduling is used as the initial quantity for the next rolling optimization scheduling.

[0176] The intraday rolling energy-carbon optimization scheduling strategy of the integrated energy system coupling relationship model with integrated photovoltaic storage and charging, while considering the energy economic operation cost, further considers the system carbon emission cost and rolling adjustment cost to carry out energy-carbon coordinated optimization;

[0177] The expression of the daily rolling energy-carbon optimization scheduling strategy of the integrated energy system coupling relationship model with integrated photovoltaic storage and charging is as follows:

[0178] ;

[0179] Where: The total carbon emission cost of the daily rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model including photovoltaic storage and charging; The total economic cost of daily rolling energy and carbon optimization scheduling for the coupled relationship model of the integrated energy system including photovoltaic storage and charging; Adjust the total cost of the daily rolling energy-carbon optimization scheduling plan for the integrated energy system coupling relationship model including photovoltaic storage and charging; The equivalent carbon emission coefficient generated by purchasing unit electricity for the integrated energy system coupling relationship model including photovoltaic storage and charging; The equivalent carbon emission coefficient generated by purchasing a unit of natural gas for the integrated energy system coupling relationship model including photovoltaic storage and charging; is the price per unit of equivalent carbon emissions; is the carbon emission intensity factor of the gas turbine; is the carbon emission quota factor per unit power generated by the gas turbine; is the carbon emission intensity factor of the supplementary-fired waste heat boiler; is the carbon emission quota factor per unit heating power of the combustion type waste heat boiler; The total economic cost of day-ahead energy economic optimization scheduling for a coupled relationship model of an integrated energy system including photovoltaic storage and charging; For the supplementary burning waste heat boiler at time Fuel input of supplementary natural gas; Adjust the cost factor per unit power of gas turbine power generation; For gas turbines at the moment of electrical power; The gas turbine is scheduled at time under the daily rolling energy-carbon optimization of electrical power; The adjustment cost coefficient for the unit power change of the transmission power of the tie line at the grid connection point; Transmit power to the grid connection line of the integrated energy system coupling relationship model including photovoltaic storage and charging integration; The transmission power of the interconnection line of the grid connection point is based on the coupling relationship model of the integrated energy system with integrated photovoltaic storage and charging under the daily rolling energy and carbon optimization scheduling; Adjust the cost coefficient per unit power of the heating output of the supplementary-fired waste heat boiler; For the supplementary burning waste heat boiler at time Heating power; The supplementary combustion waste heat boiler is scheduled at time under the daily rolling energy and carbon optimization Heating power; Adjusting the cost factor per unit capacity of electric energy storage equipment; For electrical energy storage equipment at all times of storage capacity; For the daily rolling energy and carbon optimization scheduling of electric energy storage equipment at time of storage capacity; The scheduling simulation operation cycle under the daily rolling energy and carbon optimization scheduling; Control the step resolution for scheduling simulation runs.

[0180] (6) Setting the coupling conditions between the intraday rolling energy-carbon optimization scheduling strategy and the day-ahead energy-economic optimization scheduling strategy;

[0181] The coupling conditions for setting the intraday rolling energy-carbon optimization scheduling strategy and the day-ahead energy-economic optimization scheduling strategy include: adjusting the quantity constraint, re-updating the input model to obtain the latest source-load forecast data, and the transformed single-objective intraday rolling energy-carbon optimization scheduling model;

[0182] The expression of the adjustment constraint in the coupling connection condition is as follows:

[0183] ;

[0184] Where: For gas turbines at the moment of electrical power; The gas turbine is scheduled at time under the daily rolling energy-carbon optimization of electrical power; Adjust margin factors for intraday rolling of gas turbines; is the rated installed capacity of the gas turbine; Transmit power to the grid connection line of the integrated energy system coupling relationship model including photovoltaic storage and charging integration; The transmission power of the interconnection line of the grid connection point is based on the coupling relationship model of the integrated energy system with integrated photovoltaic storage and charging under the daily rolling energy and carbon optimization scheduling; The daily rolling adjustment margin coefficient for the transmission power of the grid connection line; The upper limit of transmission power of the interconnection line of the grid connection point of the coupling relationship model of the integrated energy system with integrated photovoltaic storage and charging; For the supplementary burning waste heat boiler at time Heating power; The supplementary combustion waste heat boiler is scheduled at time under the daily rolling energy and carbon optimization Heating power; It is the daily rolling adjustment margin coefficient of the supplementary-fired waste heat boiler; is the rated installed capacity of the supplementary-fired waste heat boiler; For electrical energy storage equipment at all times of storage capacity; For the daily rolling energy and carbon optimization scheduling of electric energy storage equipment at time of storage capacity; Adjust the margin factor for the daily rolling of electric energy storage equipment; is the rated capacity of the electric energy storage device;

[0185] The expression for re-updating the latest source load forecast data input model in the coupling connection condition is as follows:

[0186] ;

[0187] Where: For wind turbines at time The maximum predicted output power; For the electric and thermal interconnected integrated energy system model at time Meet the power requirements of the electrical load; For the electric and thermal interconnected integrated energy system model at time Meet the heat load power requirements; The photovoltaic array in the photovoltaic storage and charging integrated system model at time The predicted power generation capacity; For charging pile clusters at all times The predicted charging load power; In order to update and obtain the latest source load forecast data, the corresponding values ​​are assigned to the wind turbines at time The maximum predicted output power The electric-heat interconnected integrated energy system model at the moment Meet the power demand of electrical load The electric-heat interconnected integrated energy system model at the moment Meet the heat load power requirements Photovoltaic array at the moment Forecasted power generation and charging pile cluster at all times Predicted charging load power The resolution of the first 16 control steps of each rolling optimization scheduling simulation operation cycle; Reassign symbols after data update; A set of scheduling simulation run cycles for each rolling optimization schedule; The daily rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with integrated photovoltaic storage and charging is updated every 4 hours to obtain the latest source-load forecast power; Scheduling simulation operation cycle under intraday rolling energy-carbon optimization scheduling;

[0188] The intraday rolling energy-carbon optimization scheduling model of the integrated energy system coupling relationship model with integrated photovoltaic storage and charging is a multi-objective optimization problem. Each optimization objective function is to solve the economic minimization problem with consistent dimensional units. It is linearly weighted transformed into a single-objective optimization model. The expression of the transformed single-objective intraday rolling energy-carbon optimization scheduling model in the coupling connection condition is as follows:

[0189] ;

[0190] Where: The total carbon emission cost of the daily rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model including photovoltaic storage and charging; The total economic cost of daily rolling energy and carbon optimization scheduling for the coupled relationship model of the integrated energy system including photovoltaic storage and charging; Adjust the total cost of the daily rolling energy-carbon optimization scheduling plan for the integrated energy system coupling relationship model including photovoltaic storage and charging; are different weight coefficients corresponding to different single-objective optimization functions.

[0191] (7) Inputting the integrated energy system operation initialization startup data information into the integrated energy system, and outputting the integrated energy system energy-carbon optimization scheduling result data information through the integrated energy system;

[0192] The input integrated energy system operation initialization startup data information includes: single photovoltaic module parameters, photovoltaic array parameters, photovoltaic array maximum power generation, maximum allowable abandonment rate, charging efficiency of electric energy storage equipment, discharge efficiency of electric energy storage equipment, discharge power upper limit of electric energy storage equipment, charging power upper limit of electric energy storage equipment, initial storage capacity of electric energy storage equipment, percentage coefficient of maximum interruption charging load of charging pile cluster at each time, percentage coefficient of maximum interruption charging load allowed within the optimization scheduling cycle, power upper limit of integrated photovoltaic storage and charging system model transmitted to the distribution network, power upper limit of integrated photovoltaic storage and charging system model received from the distribution network, energy loss of gas turbine rate, polynomial coefficient of gas turbine power generation efficiency characteristic curve, natural gas price of gas turbine at various times, shedding coefficient of gas turbine, rated installed capacity of gas turbine, electric power of gas turbine at various times, ramp-down rate of electric power of gas turbine, ramp-up rate of electric power of gas turbine, upper limit of number of starts of gas turbine within the optimization scheduling cycle, heating efficiency of supplementary-fired waste heat boiler, comprehensive efficiency of high-temperature flue gas recovery of supplementary-fired waste heat boiler, shedding coefficient of supplementary-fired waste heat boiler, rated installed capacity of supplementary-fired waste heat boiler, ramp-down rate of electric power of supplementary-fired waste heat boiler, ramp-up rate of electric power of supplementary-fired waste heat boiler, The natural gas price of thermal boilers at various times, the rated maximum output power of wind turbines, the minimum starting wind speed of wind turbines, the rated working wind speed of wind turbines, the extreme working wind speed of wind turbines, the different fitting coefficients of wind turbine predicted output curves, the penetration coefficient of wind turbine power generation, the wind abandonment rate within the optimization scheduling period, the maximum wind abandonment rate allowed within the optimization scheduling period, the upper limit of the penetration coefficient of wind turbine power generation, the upper limit of the power transmitted from the electric-thermal interconnected integrated energy system model to the distribution network, the upper limit of the power input from the distribution network to the electric-thermal interconnected integrated energy system model, the upper limit of the power transmitted by the interconnection line of the grid connection point of the coupling relationship model of the integrated energy system including photovoltaic storage and charging, and the upper limit of the power transmitted by the interconnection line of the grid connection point of the integrated energy system including photovoltaic storage and charging. The comprehensive energy system coupling relationship model includes the time-of-use electricity price of the grid connection point at each moment, the percentage coefficient of the maximum interruptible charging load of the charging pile cluster at each moment, the polynomial coefficient of the penalty characteristic curve of the interrupted charging load, the time-of-use electricity price of the charging business of the photovoltaic storage and charging integrated system model at each moment, the time-of-use price of the service fee of the charging business of the photovoltaic storage and charging integrated system model at each moment, the equivalent carbon emission coefficient, the equivalent carbon emission unit price, the carbon emission intensity factor, the carbon emission quota factor, the unit power adjustment cost coefficient, the intraday rolling adjustment margin coefficient, and different weight coefficients corresponding to different single-objective optimization functions.

[0193] The output data information of the energy-carbon optimization scheduling results of the integrated energy system include: the actual working power generation of the photovoltaic array at each moment, the storage capacity of the energy storage equipment at each moment, the discharge power of the energy storage equipment at each moment, the charging power of the energy storage equipment at each moment, the actual charging pile cluster load power demand met by the photovoltaic storage and charging integrated system model at each moment, the power received by the photovoltaic storage and charging integrated system model from the distribution network at each moment, the power transmitted to the distribution network by the photovoltaic storage and charging integrated system model at each moment, the electric power of the gas turbine at each moment, the power generation efficiency of the gas turbine at each moment, the operating cost of the gas turbine at each moment, and the operating efficiency of the gas turbine at each moment. The value of the Boolean variable of the row state, the heating power of the supplementary combustion type waste heat boiler at each moment, the fuel input of the supplementary combustion type waste heat boiler for supplementary combustion of natural gas at each moment, the amount of high-temperature flue gas recovered by the supplementary combustion type waste heat boiler at each moment, the value of the Boolean variable of the operating state of the supplementary combustion type waste heat boiler at each moment, the operating cost of the supplementary combustion type waste heat boiler at each moment, the actual power input of the wind turbine power generation into the integrated energy system at each moment, the power input of the distribution network to the electric and thermal interconnected integrated energy system model at each moment, the power transmitted to the distribution network by the electric and thermal interconnected integrated energy system model at each moment, the transmission power of the interconnection line of the grid point of the integrated energy system coupling relationship model containing integrated photovoltaic storage and charging, The coupling relationship model of the integrated energy system with integrated photovoltaic, storage and charging, the total economic cost of the day-ahead energy economic optimization and dispatch, the total gas consumption cost of the day-ahead energy economic optimization and dispatch, the coupling relationship model of the integrated energy system with integrated photovoltaic, storage and charging, the total grid purchase cost of the day-ahead energy economic optimization and dispatch, the total penalty cost of the day-ahead energy economic optimization and dispatch of the charging load of the integrated energy system with integrated photovoltaic, storage and charging, the total revenue of the charging business of the day-ahead energy economic optimization and dispatch, the coupling relationship model of the integrated energy system with integrated photovoltaic, storage and charging, and the intraday rolling energy-carbon optimization and dispatch of carbon Total emission cost, total economic cost of intraday rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model including integrated photovoltaic storage and charging, total cost of adjustment of the intraday rolling energy-carbon optimization scheduling plan of the integrated energy system coupling relationship model including integrated photovoltaic storage and charging, electric power of gas turbine at each moment under intraday rolling energy-carbon optimization scheduling, transmission power of grid connection point interconnection line of the integrated energy system coupling relationship model including integrated photovoltaic storage and charging under intraday rolling energy-carbon optimization scheduling, heating power of supplementary combustion type waste heat boiler at each moment under intraday rolling energy-carbon optimization scheduling, storage capacity of electric energy storage equipment at each moment under intraday rolling energy-carbon optimization scheduling, and transformed single-target intraday rolling energy-carbon optimization scheduling results.

[0194] According to the above scheme of the present invention, the present invention fully considers the multi-time-scale energy-carbon collaborative operation scenarios of the integrated photovoltaic storage and charging system and the electric thermal integrated energy system, and establishes fine-grained mathematical models such as photovoltaic power generation, electrical energy storage, wind turbine power generation, charging pile clusters, gas turbines, supplementary combustion type waste heat boilers, and grid connection points. This is conducive to the application and promotion of electric thermal integrated energy system engineering containing the integrated photovoltaic storage and charging system and the real-time refined analysis of the operating status;

[0195] Based on the actual needs of energy conservation, cost reduction and carbon reduction in engineering applications, this paper proposes a day-ahead and intraday optimization scheduling strategy for an electric-thermal integrated energy system including an integrated photovoltaic storage and charging system. This effectively solves the technical difficulties of coordinated multi-scenario optimization operation of the integrated photovoltaic storage and charging system and the electric-thermal integrated energy system, energy-carbon operation characteristic analysis, and multi-time-scale fine-grained model construction.

[0196] The present invention constructs an overall full-process detailed plan for the equipment unit model, coupling relationship model, coupling connection condition model, day-ahead energy economic optimization scheduling strategy, and intraday rolling energy-carbon optimization scheduling strategy of the integrated energy system containing integrated photovoltaic storage and charging, thereby providing reference and guidance for multi-time scale operation optimization and control management, energy conservation, emission reduction and cost reduction analysis, source-load storage energy economy and carbon emission tracking analysis, etc. of the integrated energy system containing integrated photovoltaic storage and charging.

[0197] Furthermore, to achieve the above objectives, the present invention also provides a multi-time-scale energy-carbon optimization system for an integrated energy system with integrated photovoltaic storage and charging, comprising:

[0198] Data information acquisition module, which obtains the energy system operation initialization startup data information;

[0199] The photovoltaic, storage and charging integrated system model construction module establishes the photovoltaic, storage and charging integrated system model based on the initial startup data information, including the photovoltaic power generation model, the electric energy storage model, the charging pile cluster model, and the photovoltaic, storage and charging integrated system energy coupling balance model;

[0200] The electric-thermal interconnected integrated energy system model construction module establishes the electric-thermal interconnected integrated energy system model based on the initial startup data information, including the gas turbine model, the supplementary-fired waste heat boiler model, the fan power generation model, the electric energy coupling balance model, and the thermal energy coupling balance model;

[0201] The coupling relationship model acquisition module couples and interconnects the photovoltaic storage and charging integrated system model with the electric-thermal interconnected comprehensive energy system model to form a coupling relationship model of the comprehensive energy system including photovoltaic storage and charging integration;

[0202] The day-ahead energy and economic optimization scheduling strategy setting module sets the day-ahead energy and economic optimization scheduling strategy for the integrated energy system coupling relationship model;

[0203] The intraday rolling energy-carbon optimization scheduling strategy setting module sets the intraday rolling energy-carbon optimization scheduling strategy for the integrated energy system coupling relationship model;

[0204] The coupling connection condition setting module sets the coupling connection conditions between the intraday rolling energy-carbon optimization scheduling strategy and the day-ahead energy-economic optimization scheduling strategy. After the coupling connection conditions are set, a comprehensive energy system is formed;

[0205] The result output module inputs the energy system operation initialization startup data information into the integrated energy system, and outputs the integrated energy system energy-carbon optimization scheduling result data information through the integrated energy system.

[0206] According to the above-mentioned multi-time-scale energy-carbon optimization system of the integrated energy system with integrated photovoltaic storage and charging of the present invention, the above-mentioned multi-time-scale energy-carbon optimization method of the integrated energy system with integrated photovoltaic storage and charging can be realized. The specific process steps are as described above and will not be repeated here.

[0207] Furthermore, to achieve the above-mentioned purpose, the present invention also provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and runnable on the processor. When the computer program is executed by the processor, the multi-time-scale energy-carbon optimization method for the integrated energy system with integrated photovoltaic storage and charging as described above is implemented.

[0208] Furthermore, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the multi-time-scale energy-carbon optimization method of the integrated energy system with integrated photovoltaic storage and charging as described above is implemented.

[0209] Those skilled in the art will appreciate that the modules and algorithm steps described in conjunction with the embodiments disclosed herein can be implemented using electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0210] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and equipment can refer to the corresponding processes in the aforementioned method implementation methods and will not be repeated here.

[0211] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the modules is merely a logical function division. In actual implementation, there may be other division methods, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0212] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the objectives of the embodiments of the present invention.

[0213] In addition, each functional module in the embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0214] If the functions are implemented as software modules and sold or used as standalone products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the energy-saving signal transmission / reception method according to various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, ROM, RAM, a magnetic disk, or an optical disk.

[0215] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also encompasses other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the inventive concept. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in this application.

[0216] It should be understood that the size of the serial numbers of each step in the content of the invention and the implementation methods of the present invention does not absolutely mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the implementation methods of the present invention.

Claims

1. A multi-time-scale energy-carbon optimization method for an integrated energy system with integrated photovoltaic storage and charging, characterized by: include: Establish a photovoltaic, storage and charging integrated system model, including photovoltaic power generation model, electrical energy storage model, charging pile cluster model, and photovoltaic, storage and charging integrated system energy coupling balance model; Establish an electric-thermal interconnected integrated energy system model, including a gas turbine model, a supplementary-fired waste heat boiler model, a fan power generation model, an electric energy coupling balance model, and a thermal energy coupling balance model; The photovoltaic storage and charging integrated system model and the electric-thermal interconnected comprehensive energy system model are coupled and interconnected to form a coupling relationship model of the comprehensive energy system including photovoltaic storage and charging integration; Set up a day-ahead energy economic optimization dispatch strategy for the integrated energy system coupling relationship model; Set up a daily rolling energy-carbon optimization scheduling strategy for the integrated energy system coupling relationship model; Set the coupling conditions between the intraday rolling energy-carbon optimization scheduling strategy and the day-ahead energy-economic optimization scheduling strategy. Once the coupling conditions are set, a comprehensive energy system is formed. Inputting integrated energy system operation initialization startup data information into the integrated energy system, and outputting integrated energy system energy-carbon optimization scheduling result data information through the integrated energy system; The expression of the coupling relationship model of the integrated energy system with integrated photovoltaic storage and charging is as follows: ； Where: For the integrated solar storage and charging system model at the moment Power delivered to the distribution network; For the electric and thermal interconnected integrated energy system model at time Power delivered to the distribution network; Transmit power to the grid connection line of the integrated energy system coupling relationship model including photovoltaic storage and charging integration; The upper limit of transmission power of the interconnection line of the grid connection point of the coupling relationship model of the integrated energy system with integrated photovoltaic storage and charging; For the integrated solar storage and charging system model at the moment Power received from the distribution network; For distribution network at all times Power input to the electric-thermal interconnected integrated energy system model; For gas turbines at the moment Thermal power; For the supplementary burning waste heat boiler at time The amount of recovered flue gas; The coupling connection conditions for setting the intraday rolling energy-carbon optimization scheduling strategy and the day-ahead energy-economic optimization scheduling strategy include: Adjust quantity constraints, re-update the latest source-load forecast data input model, and transform the single-target intraday rolling energy-carbon optimization scheduling model; The expression of the adjustment constraint in the coupling connection condition is as follows: ； Where: For gas turbines at the moment of electrical power; The gas turbine is scheduled at time under the daily rolling energy-carbon optimization of electrical power; Adjust margin factors for intraday rolling of gas turbines; is the rated installed capacity of the gas turbine; Transmit power to the grid connection line of the integrated energy system coupling relationship model including photovoltaic storage and charging integration; The transmission power of the interconnection line of the grid connection point is based on the coupling relationship model of the integrated energy system with integrated photovoltaic storage and charging under the daily rolling energy and carbon optimization scheduling; The daily rolling adjustment margin coefficient for the transmission power of the grid connection line; The upper limit of transmission power of the interconnection line of the grid connection point of the coupling relationship model of the integrated energy system with integrated photovoltaic storage and charging; For the supplementary burning waste heat boiler at time Heating power; The supplementary combustion waste heat boiler is scheduled at time under the daily rolling energy and carbon optimization Heating power; It is the daily rolling adjustment margin coefficient of the supplementary-fired waste heat boiler; is the rated installed capacity of the supplementary-fired waste heat boiler; For electrical energy storage equipment at all times of storage capacity; For the daily rolling energy and carbon optimization scheduling of electric energy storage equipment at time of storage capacity; Adjust the margin factor for the daily rolling of electric energy storage equipment; is the rated capacity of the electric energy storage device; The expression for re-updating the latest source-load prediction data input model in the coupling connection condition is as follows: ； Where: For wind turbines at time The maximum predicted output power; For the electric and thermal interconnected integrated energy system model at time Meet the power requirements of the electrical load; For the electric and thermal interconnected integrated energy system model at time Meet the heat load power requirements; The photovoltaic array in the photovoltaic storage and charging integrated system model at time The predicted power generation capacity; For charging pile clusters at all times The predicted charging load power; In order to update and obtain the latest source load forecast data, the corresponding values ​​are assigned to the wind turbines at time The maximum predicted output power , electric and thermal interconnected integrated energy system model at the moment Meet the power demand of electrical load , electric and thermal interconnected integrated energy system model at the moment Meet the heat load power requirements , the photovoltaic array at the time Forecasted power generation and charging pile cluster at all times Predicted charging load power The resolution of the first 16 control steps of each rolling optimization scheduling simulation operation cycle; Reassign symbols after data update; A set of scheduling simulation run cycles for each rolling optimization schedule; The daily rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with integrated photovoltaic storage and charging is updated every 4 hours to obtain the latest source-load forecast power; The scheduling simulation operation cycle under the daily rolling energy and carbon optimization scheduling; The expression of the transformed single-objective intra-day rolling energy-carbon optimization scheduling model in the coupling connection condition is as follows: ； Where: The total carbon emission cost of the daily rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model including photovoltaic storage and charging; The total economic cost of daily rolling energy and carbon optimization scheduling for the coupled relationship model of the integrated energy system including photovoltaic storage and charging; Adjust the total cost of the daily rolling energy-carbon optimization scheduling plan for the integrated energy system coupling relationship model including photovoltaic storage and charging; are different weight coefficients corresponding to different single-objective optimization functions.

2. The multi-time-scale energy-carbon optimization method for an integrated energy system with integrated photovoltaic storage and charging according to claim 1 is characterized in that: The photovoltaic power generation model includes: a mathematical model of a single photovoltaic module, a mathematical model of a photovoltaic array, and a photovoltaic power generation safe operation domain model; The mathematical model of a single photovoltaic module is expressed as follows: ； Where: For photovoltaic modules at the moment The predicted power generation capacity; The power output of the photovoltaic module under the standard test environment is regarded as the rated power; The photovoltaic modules generate electricity at the time Light intensity during operation, and light intensity in the working environment of photovoltaic modules under standard test conditions; The temperature adjustment factor for the photovoltaic module's power output, i.e., the temperature adjustment coefficient; Photovoltaic power generation at time Working temperature, working temperature of photovoltaic module power generation under standard test environment; Power generation for photovoltaic modules at all times Working ambient temperature; The operating rated temperature for generating electricity for photovoltaic modules; The expression of the photovoltaic array mathematical model is as follows: ； Where: The photovoltaic array at time The predicted power generation capacity; is the total number of PV modules in the PV array; For photovoltaic modules at the moment The predicted power generation capacity; is the average total power generation efficiency of the photovoltaic array; The expression of the photovoltaic power generation safe operation domain model is as follows: ； Where: The photovoltaic array at time The predicted power generation capacity; The photovoltaic array at time The predicted power generation capacity; The photovoltaic array at time The actual working power generation; is the maximum power generated by the photovoltaic array, which is regarded as the installed capacity; To optimize the maximum allowed abandoned light rate within the scheduling cycle; To schedule the simulation run cycle; The electric energy storage model consists of energy time domain relationship and operation safety domain; The energy-time domain relationship expression of the electric energy storage model is as follows: ； Where: For electrical energy storage equipment at all times of storage capacity; For electrical energy storage equipment at all times of storage capacity; is the self-discharge rate of the electrical energy storage device; For electrical energy storage equipment at all times The discharge power; For electrical energy storage equipment at all times Charging power; Charging efficiency of electrical energy storage devices; is the discharge efficiency of the electrical energy storage device; Control the step resolution for scheduling simulation runs; It is the intermediate state variable in the linear transformation process of the electric energy storage device model; It is a large number of intermediate variables in the linear transformation process of the electric energy storage device model; The operational safety domain expression of the electric energy storage model is as follows: ; Where: For electrical energy storage equipment at all times The discharge power; For electrical energy storage equipment at all times Charging power; The upper limit of the discharge power of the electric energy storage device; Upper limit of charging power for electric energy storage devices; For electrical energy storage equipment at all times of storage capacity; The lower limit factor of the real-time storage capacity of the energy storage device; The upper limit factor of the real-time storage capacity of the electric energy storage device; is the rated capacity of the electric energy storage device; The initial storage capacity of the energy storage device; The storage capacity of the energy storage device at the end of the operation cycle, that is, the storage capacity after the end of a scheduling simulation operation cycle, can also be used express; The matching degree of the energy storage device's initial and final states at the start and end of the scheduling simulation cycle. A value of 0 indicates no requirement, a value of 1 indicates a completely matching state, and other values ​​indicate an acceptable matching degree. The expression of the charging pile cluster model is as follows: ； Where: For charging pile clusters at all times The percentage factor of the maximum interruptible charging load; For the integrated solar storage and charging system model at the moment Meet the actual charging pile cluster load power requirements; For charging pile clusters at all times The predicted charging load power; The maximum interruption charging load percentage coefficient allowed within the optimization scheduling period; The expression of the energy coupling balance model of the integrated photovoltaic storage and charging system is as follows: ； Where: For the integrated solar storage and charging system model at the moment Power received from the distribution network; The upper limit of the power that the integrated solar-storage-charging system model can receive from the distribution network; For the integrated solar storage and charging system model at the moment Power delivered to the distribution network; The upper limit of the power delivered to the distribution network by the integrated solar-storage-charging system model; Capacity constraints of the distribution network interconnection lines for the integrated photovoltaic storage and charging system model; It is the intermediate state variable in the linear transformation process of the capacity constraint of the distribution network interconnection line in the integrated photovoltaic storage and charging system model; It is a large-valued variable in the intermediate process of the linear transformation of the capacity constraint of the distribution network interconnection line in the integrated photovoltaic storage and charging system model.

3. The multi-time-scale energy-carbon optimization method for an integrated energy system with integrated photovoltaic storage and charging according to claim 1 is characterized in that: The gas turbine model includes: a gas turbine operation characteristic model and a gas turbine safe operation domain constraint; The expression of the gas turbine operation characteristic model is as follows: ； Where: For gas turbines at the moment of electrical power; For gas turbines at the moment power generation efficiency; For gas turbines at the moment Fuel input; For gas turbines at the moment Thermal power; is the energy loss rate of the gas turbine; For gas turbines at the moment natural gas consumption rate; The calorific value of natural gas when burning natural gas in a gas turbine; For gas turbines at the moment The electrical load rate; is the polynomial coefficient of the gas turbine power generation efficiency characteristic curve, where the superscript is a polynomial power; For gas turbines at the moment The Boolean variable of the operating state of the gas turbine is 1 when the gas turbine is running and 0 when the gas turbine is stopped; For gas turbines at the moment operating costs; For gas turbines at the moment natural gas prices; The expression of the gas turbine safe operation domain constraint is as follows: ； Where: For gas turbines at the moment of electrical power; For gas turbines at the moment The running status Boolean variable, where the Boolean variable value is 1 when running and 0 when stopped; is the cutting coefficient of the gas turbine; is the rated installed capacity of the gas turbine; is the ramp rate of the gas turbine under electrical power; is the electrical power ramp-up rate of the gas turbine; The upper limit of the number of gas turbine starts within the optimal scheduling cycle; To schedule the simulation run cycle; Control the step resolution for scheduling simulation runs; The expression of the supplementary combustion type waste heat boiler model is as follows: ； Where: For the supplementary burning waste heat boiler at time Heating power; For the supplementary burning waste heat boiler at time Heating power; is the heating efficiency of the supplementary-fired waste heat boiler; For the supplementary burning waste heat boiler at time Fuel input of supplementary natural gas; The comprehensive efficiency of flue gas recovery of supplementary-fired waste heat boiler; For the supplementary burning waste heat boiler at time The amount of recovered flue gas; For the supplementary burning waste heat boiler at time natural gas consumption rate; The calorific value of natural gas when burning natural gas in a supplementary-fired waste heat boiler; For the supplementary burning waste heat boiler at time The operating status Boolean variable, wherein the Boolean variable value is 1 when the supplementary-fired waste heat boiler is running, and the Boolean variable value is 0 when the supplementary-fired waste heat boiler is stopped; is the trip coefficient of the supplementary-fired waste heat boiler; is the rated installed capacity of the supplementary-fired waste heat boiler; is the ramp rate of the electric power of the supplementary-fired waste heat boiler; The electric power ramp-up rate of the supplementary-fired waste heat boiler; Control the step resolution for scheduling simulation runs; For the supplementary burning waste heat boiler at time operating costs; For the supplementary burning waste heat boiler at time natural gas prices; The wind turbine power generation model includes: a wind turbine power generation operation characteristic model and wind turbine power generation safety operation constraints; The expression of the wind turbine power generation operation characteristic model is as follows: ； Where: For wind turbines at time The maximum predicted output power; is the rated maximum output power of the wind turbine; For wind turbines at time Actual working wind speed; The minimum starting wind speed for the wind turbine; is the rated operating wind speed of the wind turbine; The maximum operating wind speed of the wind turbine; Different fitting coefficients for predicting output curves of wind turbines; The expression of the wind turbine power generation safety operation constraint is as follows: ； Where: For wind turbines at time The maximum predicted output power; Generating electricity for wind turbines at all times The actual power input into the electric-thermal interconnected integrated energy system model; is the penetration coefficient of wind turbine power generation; For the electric and thermal interconnected integrated energy system model at time Total power input power; To optimize the wind curtailment rate within the dispatch cycle; To optimize the maximum wind curtailment rate allowed within the dispatch cycle; is the upper limit of the permeability coefficient of wind turbine power generation; The expression of the electric energy coupling balance model is as follows: ； Where: For distribution network at all times Power input to the electric-thermal interconnected integrated energy system model; For the electric and thermal interconnected integrated energy system model at time Power delivered to the distribution network; For the electric and thermal interconnected integrated energy system model at time Meet the power requirements of the electrical load; It is the intermediate state variable in the linear transformation process of the interconnection line capacity constraint of the electric-thermal interconnected integrated energy system model; It is a large number value variable in the intermediate process of the linear transformation of the capacity constraint of the interconnection line of the electric-thermal interconnected integrated energy system model; The upper limit of power delivered to the distribution grid for the electric-thermal interconnected integrated energy system model; The upper limit of the power input from the distribution network to the electric and thermal interconnected integrated energy system model; The expression of the thermal energy coupling balance model is as follows: ; Where: For the electric and thermal interconnected integrated energy system model at time Meet the heat load power requirements.

4. The multi-time-scale energy-carbon optimization method for an integrated energy system with integrated photovoltaic storage and charging according to claim 1 is characterized in that: The above-mentioned method sets a day-ahead energy economic optimization scheduling strategy for the integrated energy system coupling relationship model, including: The scheduling simulation operation cycle of the day-ahead energy economic optimization scheduling of the integrated energy system coupling relationship model with integrated photovoltaic storage and charging is 24 hours a day, the scheduling simulation operation control step resolution is 1 hour, and a total of 24 control steps; The expression of the day-ahead energy economic optimization scheduling strategy of the integrated energy system coupling relationship model with integrated photovoltaic storage and charging is as follows: ； Where: The total economic cost of day-ahead energy economic optimization scheduling for a coupled relationship model of an integrated energy system including photovoltaic storage and charging; The total gas consumption cost of the day-ahead energy economic optimization scheduling of the coupled relationship model of the integrated energy system including photovoltaic storage and charging; The total grid-connected electricity purchase cost for the day-ahead energy economic optimization dispatch of the integrated energy system coupling relationship model including photovoltaic storage and charging integration; The total penalty cost of interrupted charging load in the day-ahead energy economic optimization scheduling of the integrated energy system coupling relationship model including photovoltaic storage and charging integration; A coupling relationship model for an integrated energy system with integrated photovoltaic, storage and charging, and the total revenue of charging services for day-ahead energy economic optimization scheduling; For gas turbines at the moment operating costs; For the supplementary burning waste heat boiler at time operating costs; A coupling relationship model of an integrated energy system with integrated photovoltaic storage and charging for day-ahead energy economic optimization scheduling at time Time-of-use electricity prices at the grid connection point; Transmit power to the grid connection line of the integrated energy system coupling relationship model including photovoltaic storage and charging integration; For charging pile clusters at all times The percentage factor of the maximum interruptible charging load; For charging pile clusters at all times The predicted charging load power; is the polynomial coefficient of the penalty characteristic curve for interrupting charging load, where the superscript is a polynomial power; The charging business of the integrated solar storage and charging system model is The charging electricity fee is the time-of-use electricity price; The charging business of the integrated solar storage and charging system model is Time-sharing price of service fee; For the integrated solar storage and charging system model at the moment Meet the actual charging pile cluster load power requirements; To schedule the simulation run cycle; Controls the step resolution for scheduling simulation runs.

5. The multi-time-scale energy-carbon optimization method for an integrated energy system with integrated photovoltaic storage and charging according to claim 1 is characterized in that: The intraday rolling energy-carbon optimization scheduling strategy is set for the integrated energy system coupling relationship model, including: The intraday rolling cycle of the intraday rolling energy-carbon optimization scheduling strategy of the integrated energy system coupling relationship model with integrated photovoltaic storage and charging is once every 4 hours. There are 6 rolling optimization schedulings in 24 hours a day. The scheduling simulation operation cycles of the 1st, 2nd, 3rd, 4th, 5th and 6th rolling optimization scheduling are 24 hours, 20 hours, 16 hours, 12 hours, 8 hours and 4 hours respectively. The control step resolution of each scheduling simulation operation is 15 minutes. The scheduling simulation operation cycles of the 1st, 2nd, 3rd, 4th, 5th and 6th rolling optimization scheduling are 96, 80, 64, 48, 32 and 16 control steps respectively. The scheduling simulation operation control step resolution of a day-ahead energy and economic optimization scheduling includes 4 intraday rolling energy and carbon optimization scheduling simulation operation control step resolutions. The intraday rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model containing integrated photovoltaic storage and charging performs rolling optimization scheduling on the basis of the results of the energy-economic optimization scheduling of the integrated energy system coupling relationship model containing integrated photovoltaic storage and charging on the day before. The intraday rolling energy-carbon optimization scheduling generally tracks the results of the energy-economic optimization scheduling on the day before. The results of the energy-economic optimization scheduling on the day before include the gas turbine output scheduling results, the grid connection point interconnection line transmission power scheduling results, the supplementary combustion type waste heat boiler heating power scheduling results, and the electric energy storage equipment storage capacity scheduling results. The intraday rolling energy-carbon optimization scheduling is only adjusted on the basis of the results of the energy-economic optimization scheduling on the day before, and the controllable unit equipment and the grid connection point power are adjusted to eliminate the power balance shortfall caused by the source-load power prediction error; The intraday rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with integrated photovoltaic storage and charging is updated every 4 hours to obtain the latest photovoltaic power generation, wind turbine power generation, electric load, thermal load, and charging pile cluster predicted power, and the latest source-load prediction data is input into the current rolling optimization scheduling. The control step resolution of the first 16 control steps of the scheduling simulation operation cycle of each rolling optimization scheduling is the latest source-load prediction data, and the scheduling result within the scheduling simulation operation cycle of the previous rolling optimization scheduling is used as the initial quantity of the next rolling optimization scheduling; The intraday rolling energy-carbon optimization scheduling strategy of the integrated energy system coupling relationship model with integrated photovoltaic storage and charging, while taking into account the energy economic operation cost, further considers the system carbon emission cost and rolling adjustment cost to perform energy-carbon coordinated optimization; The expression of the daily rolling energy-carbon optimization scheduling strategy of the integrated energy system coupling relationship model with integrated photovoltaic storage and charging is as follows: ； Where: The total carbon emission cost of the daily rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model including photovoltaic storage and charging; The total economic cost of daily rolling energy and carbon optimization scheduling for the coupled relationship model of the integrated energy system including photovoltaic storage and charging; Adjust the total cost of the daily rolling energy-carbon optimization scheduling plan for the integrated energy system coupling relationship model including photovoltaic storage and charging; The equivalent carbon emission coefficient generated by purchasing unit electricity for the integrated energy system coupling relationship model including photovoltaic storage and charging; The equivalent carbon emission coefficient generated by purchasing a unit of natural gas for the integrated energy system coupling relationship model including photovoltaic storage and charging; is the price per unit of equivalent carbon emissions; is the carbon emission intensity factor of the gas turbine; is the carbon emission quota factor per unit power generated by the gas turbine; is the carbon emission intensity factor of the supplementary-fired waste heat boiler; is the carbon emission quota factor per unit heating power of the combustion type waste heat boiler; The total economic cost of day-ahead energy economic optimization scheduling for a coupled relationship model of an integrated energy system including photovoltaic storage and charging; For the supplementary burning waste heat boiler at time Fuel input of supplementary natural gas; Adjust the cost factor per unit power of gas turbine power generation; For gas turbines at the moment of electrical power; The gas turbine is scheduled at time under the daily rolling energy-carbon optimization of electrical power; The adjustment cost coefficient for the unit power change of the transmission power of the tie line at the grid connection point; Transmit power to the grid connection line of the integrated energy system coupling relationship model including photovoltaic storage and charging integration; The transmission power of the interconnection line of the grid connection point is based on the coupling relationship model of the integrated energy system with integrated photovoltaic storage and charging under the daily rolling energy and carbon optimization scheduling; Adjust the cost coefficient per unit power of the heating output of the supplementary-fired waste heat boiler; For the supplementary burning waste heat boiler at time Heating power; The supplementary combustion waste heat boiler is scheduled at time under the daily rolling energy and carbon optimization Heating power; Adjusting the cost factor per unit capacity of electric energy storage equipment; For electrical energy storage equipment at all times of storage capacity; For the daily rolling energy and carbon optimization scheduling of electric energy storage equipment at time of storage capacity; The scheduling simulation operation cycle under the daily rolling energy and carbon optimization scheduling; Controls the step resolution for scheduling simulation runs.

6. A multi-time-scale energy-carbon optimization system for an integrated energy system with integrated photovoltaic storage and charging, characterized by: include: Data information acquisition module, which obtains the energy system operation initialization startup data information; The photovoltaic, storage and charging integrated system model construction module establishes the photovoltaic, storage and charging integrated system model based on the initial startup data information, including the photovoltaic power generation model, the electric energy storage model, the charging pile cluster model, and the photovoltaic, storage and charging integrated system energy coupling balance model; The electric-thermal interconnected integrated energy system model construction module establishes the electric-thermal interconnected integrated energy system model based on the initial startup data information, including the gas turbine model, the supplementary-fired waste heat boiler model, the fan power generation model, the electric energy coupling balance model, and the thermal energy coupling balance model; The coupling relationship model acquisition module couples and interconnects the photovoltaic storage and charging integrated system model with the electric and thermal interconnected comprehensive energy system model to form a coupling relationship model of the comprehensive energy system including photovoltaic storage and charging integration; The day-ahead energy and economic optimization scheduling strategy setting module sets the day-ahead energy and economic optimization scheduling strategy for the integrated energy system coupling relationship model; The intraday rolling energy-carbon optimization scheduling strategy setting module sets the intraday rolling energy-carbon optimization scheduling strategy for the integrated energy system coupling relationship model; The coupling connection condition setting module sets the coupling connection conditions between the intraday rolling energy-carbon optimization scheduling strategy and the day-ahead energy-economic optimization scheduling strategy. After the coupling connection conditions are set, a comprehensive energy system is formed. The result output module inputs the energy system operation initialization startup data information to the integrated energy system, and outputs the integrated energy system energy-carbon optimization scheduling result data information through the integrated energy system; The expression of the coupling relationship model of the integrated energy system with integrated photovoltaic storage and charging is as follows: ； Where: For the integrated solar storage and charging system model at the moment Power delivered to the distribution network; For the electric and thermal interconnected integrated energy system model at time Power delivered to the distribution network; Transmit power to the grid connection line of the integrated energy system coupling relationship model including photovoltaic storage and charging integration; The upper limit of transmission power of the interconnection line of the grid connection point of the coupling relationship model of the integrated energy system with integrated photovoltaic storage and charging; For the integrated solar storage and charging system model at the moment Power received from the distribution network; For distribution network at all times Power input to the electric-thermal interconnected integrated energy system model; For gas turbines at the moment Thermal power; For the supplementary burning waste heat boiler at time The amount of recovered flue gas; The coupling connection conditions for setting the intraday rolling energy-carbon optimization scheduling strategy and the day-ahead energy-economic optimization scheduling strategy include: Adjust quantity constraints, re-update the latest source-load forecast data input model, and transform the single-target intraday rolling energy-carbon optimization scheduling model; The expression of the adjustment constraint in the coupling connection condition is as follows: ； Where: For gas turbines at the moment of electrical power; The gas turbine is scheduled at time under the daily rolling energy-carbon optimization of electrical power; Adjust margin factors for intraday rolling of gas turbines; is the rated installed capacity of the gas turbine; Transmit power to the grid connection line of the integrated energy system coupling relationship model including photovoltaic storage and charging integration; The transmission power of the interconnection line of the grid connection point is based on the coupling relationship model of the integrated energy system with integrated photovoltaic storage and charging under the daily rolling energy and carbon optimization scheduling; The daily rolling adjustment margin coefficient for the transmission power of the grid connection line; The upper limit of transmission power of the interconnection line of the grid connection point of the coupling relationship model of the integrated energy system with integrated photovoltaic storage and charging; For the supplementary burning waste heat boiler at time Heating power; The supplementary combustion waste heat boiler is scheduled at time under the daily rolling energy and carbon optimization Heating power; It is the daily rolling adjustment margin coefficient of the supplementary-fired waste heat boiler; is the rated installed capacity of the supplementary-fired waste heat boiler; For electrical energy storage equipment at all times of storage capacity; For the daily rolling energy and carbon optimization scheduling of electric energy storage equipment at time of storage capacity; Adjust the margin factor for the daily rolling of electric energy storage equipment; is the rated capacity of the electric energy storage device; The expression for re-updating the latest source-load prediction data input model in the coupling connection condition is as follows: ； Where: For wind turbines at time The maximum predicted output power; For the electric and thermal interconnected integrated energy system model at time Meet the power requirements of the electrical load; For the electric and thermal interconnected integrated energy system model at time Meet the heat load power requirements; The photovoltaic array in the photovoltaic storage and charging integrated system model at time The predicted power generation capacity; For charging pile clusters at all times The predicted charging load power; In order to update and obtain the latest source load forecast data, the corresponding values ​​are assigned to the wind turbines at time The maximum predicted output power , electric and thermal interconnected integrated energy system model at the moment Meet the power demand of electrical load , electric and thermal interconnected integrated energy system model at the moment Meet the heat load power requirements , the photovoltaic array at the time Forecasted power generation and charging pile cluster at all times Predicted charging load power The resolution of the first 16 control steps of each rolling optimization scheduling simulation operation cycle; Reassign symbols after data update; A set of scheduling simulation run cycles for each rolling optimization schedule; The daily rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with integrated photovoltaic storage and charging is updated every 4 hours to obtain the latest source-load forecast power; The scheduling simulation operation cycle under the daily rolling energy and carbon optimization scheduling; The expression of the transformed single-objective intra-day rolling energy-carbon optimization scheduling model in the coupling connection condition is as follows: ； Where: The total carbon emission cost of the daily rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model including photovoltaic storage and charging; The total economic cost of daily rolling energy and carbon optimization scheduling for the coupled relationship model of the integrated energy system including photovoltaic storage and charging; Adjust the total cost of the daily rolling energy-carbon optimization scheduling plan for the integrated energy system coupling relationship model including photovoltaic storage and charging; are different weight coefficients corresponding to different single-objective optimization functions.

7. An electronic device, characterized in that It comprises a processor, a memory and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the multi-time-scale energy-carbon optimization method for an integrated energy system with integrated photovoltaic storage and charging as described in any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the multi-time-scale energy-carbon optimization method for an integrated energy system with integrated photovoltaic storage and charging as described in any one of claims 1 to 5.

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