Multi-time-scale energy-carbon optimization method for comprehensive energy system integrating light, storage and charging

Abstract

The invention relates to the technical field of energy-carbon scheduling of a comprehensive energy system, and provides a multi-time-scale energy-carbon optimization method for a comprehensive energy system with light, storage and charging integration, which comprises the following steps: establishing a light, storage and charging integration system model and an electric heating interconnection comprehensive energy system model, and constructing a coupling relation model of the comprehensive energy system with light, storage and charging integration; then, further setting day-ahead and intra-day multi-time scale optimization scheduling strategies, and setting a coupling connection condition of intra-day rolling energy carbon optimization scheduling and day-ahead energy economy optimization scheduling; and finally, through day-ahead and intra-day optimization scheduling calculation, outputting energy-carbon optimization scheduling result data information of the integrated energy system. According to the method, the light-storage-charging integrated electric heating comprehensive energy system fine-grained model and the day-ahead and intra-day optimization scheduling strategy are constructed, and reference and guidance can be provided for multi-time-scale operation optimization regulation and control management, energy conservation, emission reduction and cost reduction analysis, source load storage energy economy and carbon emission tracking analysis and the like of the comprehensive energy system.

Description

Technical Field

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

[0002] With the acceleration of the global energy transition and the increasing strictness of carbon emission control, integrated energy systems, as a system that can achieve efficient coupling and collaborative optimization of multiple energy forms, have received extensive attention. The integrated electro-thermal energy system with photovoltaic, energy storage and charging integration, as a new energy utilization mode, integrates resources such as photovoltaic, electrical energy storage, wind turbines, electro-thermal loads, gas turbines and charging pile clusters, realizes efficient energy utilization and flexible scheduling, and gradually becomes an important part of the future energy system. It can effectively solve the problem of difficult regulation caused by source and load prediction errors, and at the same time provide flexible charging services and supply electro-thermal energy, with significant energy-saving and emission-reduction potential and economic value.

[0003] How to ensure the collaborative optimization operation of the photovoltaic, energy storage and charging integration system and the integrated electro-thermal energy system, especially to achieve energy-carbon collaborative optimization on multiple time scales, has become an urgent technical problem to be solved. At present, the collaborative operation optimization of the photovoltaic, energy storage and charging integration system and the integrated electro-thermal energy system has not been fully studied, which challenges the energy balance and stable operation of the integrated energy system. Moreover, most of the existing research focuses on the optimization scheduling of a single time scale, lacking in-depth discussion on multi-time-scale collaborative optimization. In actual operation, the integrated energy system needs to be optimized and scheduled on different time scales such as day-ahead and intra-day. However, the existing technologies have the following problems: (1) There are deficiencies in the collaborative optimization operation, multi-time-scale optimization scheduling and energy-carbon collaborative optimization of the photovoltaic, energy storage and charging integration system and the integrated electro-thermal energy system, making it difficult to meet the requirements of the system for economic, efficient, stable and low-carbon operation; (2) The energy scheduling strategy on multiple time scales is not fully considered, resulting in the lack of flexibility and adaptability of the optimization scheduling strategy; (3) The carbon emission factor is ignored, lacking energy-carbon collaborative day-ahead and intra-day optimization scheduling strategies, ignoring the coupling relationship and dynamic change characteristics between multiple energy systems, limiting the overall efficiency of the energy system, and also making it difficult to meet the urgent need for energy conservation and emission reduction; (4) Most only focus on economic costs, insufficiently consider energy-carbon collaboration analysis, and lack a systematic solution for energy-carbon collaborative optimization. Summary of the Invention

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

[0005] To achieve the above purpose, the present invention provides a multi-time-scale energy-carbon optimization method for an integrated energy system with photovoltaic, energy storage and charging integration, including: Build a model of the integrated photovoltaic-energy storage-charging system, including a photovoltaic power generation model, an energy storage model, a charging pile cluster model, and an energy coupling balance model of the integrated photovoltaic-energy storage-charging system; Build a model of the integrated electric-thermal interconnected energy system, including a gas turbine model, a supplementary-firing waste heat boiler model, a fan power generation model, an electric energy coupling balance model, and a thermal energy coupling balance model; Couple and interconnect the model of the integrated photovoltaic-energy storage-charging system and the model of the integrated electric-thermal interconnected energy system to form a coupling relationship model of the integrated energy system with integrated photovoltaic-energy storage-charging; Set a day-ahead energy economic optimal dispatching strategy for the coupling relationship model of the integrated energy system; Set an intraday rolling energy-carbon optimal dispatching strategy for the coupling relationship model of the integrated energy system; Set the coupling connection conditions between the intraday rolling energy-carbon optimal dispatching strategy and the day-ahead energy economic optimal dispatching strategy. After the coupling connection conditions are set, an integrated energy system is formed; Input the initial start-up data information of the integrated energy system operation into the integrated energy system, and output the energy-carbon optimal dispatching result data information of the integrated energy system through the integrated energy system.

[0006] According to one aspect of the present invention, the photovoltaic power generation model includes: a single-piece photovoltaic module mathematical model, a photovoltaic array mathematical model, and a photovoltaic power generation safe operation domain model; The expression of the single-piece photovoltaic module mathematical model is as follows: ; In the formula: is the predicted power generation of the photovoltaic module at time ; is the power generation output of the photovoltaic module under the standard specification test environment, which can be regarded as the rated power; are respectively the light intensity when the photovoltaic module generates electricity at time and the light intensity of the working environment of the photovoltaic module generating electricity under the standard specification test environment; is the temperature change adjustment factor of the photovoltaic module power generation output, that is, the temperature adjustment coefficient; are respectively the temperature when the photovoltaic power generation works at time and the working environment temperature of the photovoltaic module generating electricity under the standard specification test environment; is the ambient temperature when the photovoltaic module generates electricity at time ; is the working rated temperature of the photovoltaic module power generation; The expression of the photovoltaic array mathematical model is as follows: ; In the formula: is the photovoltaic array at time The predicted power generation; is the total number of photovoltaic modules in the photovoltaic array; is the predicted power generation of the photovoltaic module at time ; is the average total power generation efficiency of the photovoltaic array; The expression of the safe operation domain model of the photovoltaic power generation is as follows: ; In the formula: is the predicted power generation of the photovoltaic array at time ; is the predicted power generation of the photovoltaic array at time ; is the actual power generation of the photovoltaic array at time ; is the maximum power generation of the photovoltaic array, which can be regarded as the installed capacity; is the maximum allowable light abandonment rate during the optimization scheduling period; is the scheduling simulation operation cycle; The electric energy storage model consists of an energy time domain relationship and an operation safety domain; The expression of the energy time domain relationship of the electric energy storage model is as follows: ; In the formula: is the stored electricity of the electric energy storage device at time ; is the stored electricity of the electric energy storage device at time ; is the self-discharge rate of the electric energy storage device; is the discharge power of the electric energy storage device at time ; is the charging power of the electric energy storage device at time ; is the charging efficiency of the electric energy storage device; is the discharge efficiency of the electric energy storage device; is the resolution of the scheduling simulation operation control step; is the intermediate process state variable in the linearization transformation process of the electric energy storage device model; is the intermediate process large number value variable in the linearization transformation process of the electric energy storage device model; The expression of the operation safety domain of the electric energy storage model is as follows: ; In the formula: is the discharge power of the electric energy storage device at time ; is the charging power of the electrical energy storage device at time ; is the upper limit of the discharging power of the electrical energy storage device; is the upper limit of the charging power of the electrical energy storage device; is the stored electrical energy of the electrical energy storage device at time ; is the lower limit factor of the real-time stored electrical energy of the electrical energy storage device; is the upper limit factor of the real-time stored electrical energy of the electrical energy storage device; is the rated capacity of the electrical energy storage device; is the initial stored electrical energy of the electrical energy storage device; is the stored electrical energy at the end of the electrical energy storage device, that is, the stored electrical energy after the end of a dispatching simulation operation cycle, and can also be represented by ; is the matching degree of the initial and final states of the stored electrical energy of the electrical energy storage device at the start and end of the dispatching simulation cycle. When the value is 0, it means there is no requirement. When the value is 1, it means a completely matching state. When other values are taken, it means an acceptable matching degree; The expression of the charging pile cluster model is as follows: ; In the formula: is the percentage coefficient of the maximum interruptible charging load of the charging pile cluster at time ; is that the integrated photovoltaic energy storage and charging system model meets the actual load power demand of the charging pile cluster at time ; is the predicted charging load power of the charging pile cluster at time ; is the maximum allowable interruptible charging load percentage coefficient within the optimization dispatching cycle; The expression of the energy coupling balance model of the integrated photovoltaic energy storage and charging system is as follows: ; In the formula: is the power received by the integrated photovoltaic energy storage and charging system model from the distribution network at time ; is the upper limit of the power received by the integrated photovoltaic energy storage and charging system model from the distribution network; is the power transmitted by the integrated photovoltaic energy storage and charging system model to the distribution network at time ; is the upper limit of the power transmitted by the integrated photovoltaic energy storage and charging system model to the distribution network; is the distribution network connection line capacity constraint of the integrated photovoltaic energy storage and charging system model; is the intermediate process state variable in the linearization transformation process of the distribution network connection line capacity constraint of the integrated photovoltaic energy storage and charging system model; It is a large number value variable in the intermediate process of the linearization transformation of the capacity constraint of the distribution network connection line in the integrated photovoltaic energy storage charging system model.

[0007] 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; The expression of the gas turbine operation characteristic model is as follows: ; In the formula: is the electric power of the gas turbine at time ; is the gas turbine at time power generation efficiency; is the gas turbine at time fuel input; is the gas turbine at time thermal power; is the energy loss rate of the gas turbine; is the gas turbine at time natural gas consumption rate; is the calorific value of natural gas when the gas turbine burns natural gas; is the gas turbine at time electrical load rate; is the polynomial coefficient of the gas turbine power generation efficiency characteristic curve, where the superscript is the polynomial power; is the gas turbine at time operation status Boolean variable, where the Boolean variable takes the value of 1 when the gas turbine is running and 0 when the gas turbine is shut down; is the gas turbine at time operation cost; is the natural gas price of the gas turbine at time ; The expression of the gas turbine safe operation domain constraint is as follows: ; In the formula: is the electric power of the gas turbine at time ; is the gas turbine at time operation status Boolean variable, where the Boolean variable takes the value of 1 when running and 0 when shut down; is the shedding coefficient of the gas turbine; is the rated installed capacity of the gas turbine; is the down-ramp rate of the electric power of the gas turbine; is the up-ramp rate of the electric power of the gas turbine; is the upper limit of the start-up times of the gas turbine within the optimization scheduling period; is the scheduling simulation operation cycle; is the resolution of the scheduling simulation operation control step size; The expression of the supplementary combustion type waste heat boiler model is as follows: ; In the formula: is the heat supply power of the supplementary combustion type waste heat boiler at time ; is the heat supply power of the supplementary combustion type waste heat boiler at time ; is the heating efficiency of the supplementary combustion type waste heat boiler; is the fuel input of the supplementary combustion natural gas of the supplementary combustion type waste heat boiler at time ; is the comprehensive efficiency of high temperature flue gas recovery of the supplementary combustion type waste heat boiler; is the recovered high temperature flue gas volume of the supplementary combustion type waste heat boiler at time ; is the natural gas consumption rate of the supplementary combustion type waste heat boiler at time ; is the natural gas calorific value when the supplementary combustion type waste heat boiler burns natural gas; is the operating state Boolean variable of the supplementary combustion type waste heat boiler at time , where the Boolean variable takes the value of 1 when the supplementary combustion type waste heat boiler is running and 0 when the supplementary combustion type waste heat boiler is shut down; is the unit tripping coefficient of the supplementary combustion type waste heat boiler; is the rated installed capacity of the supplementary combustion type waste heat boiler; is the down-ramp rate of the electric power of the supplementary combustion type waste heat boiler; is the up-ramp rate of the electric power of the supplementary combustion type waste heat boiler; is the resolution of the scheduling simulation operation control step size; is the operating cost of the supplementary combustion type waste heat boiler at time ; is the natural gas price of the supplementary combustion type waste heat boiler at time ; The fan power generation model includes: a fan power generation operation characteristic model and a fan power generation safe operation constraint; The expression of the fan power generation operation characteristic model is as follows: ; In the formula: is the maximum predicted output power of the wind turbine at time ; is the rated maximum output power of the wind turbine; is the actual working wind speed of the wind turbine at time ; is the minimum starting operating wind speed of the wind turbine; is the rated operating wind speed of the wind turbine; is the limit operating wind speed of the wind turbine; are the different fitting coefficients of the predicted output power curve of the wind turbine; The expression of the safety operation constraint of the wind turbine power generation is as follows: ; In the formula: is the maximum predicted output power of the wind turbine at time ; is the power actually input into the electro-thermal interconnected integrated energy system model by the wind turbine power generation at time ; is the penetration coefficient of the wind turbine power generation; is the total power input of the electro-thermal interconnected integrated energy system model at time ; is the wind curtailment rate within the optimization dispatching period; is the maximum allowable wind curtailment rate within the optimization dispatching period; is the upper limit value of the penetration coefficient of the wind turbine power generation; The expression of the electric energy coupling balance model is as follows: ; In the formula: is the power input by the distribution network into the electro-thermal interconnected integrated energy system model at time ; is the power transmitted by the electro-thermal interconnected integrated energy system model to the distribution network at time ; is the electrical load power demand satisfied by the electro-thermal interconnected integrated energy system model at time ; is the intermediate process state variable in the linearization transformation process of the tie line capacity constraint of the electro-thermal interconnected integrated energy system model; is the intermediate process large number value variable in the linearization transformation process of the tie line capacity constraint of the electro-thermal interconnected integrated energy system model; is the upper limit of the power transmitted by the electro-thermal interconnected integrated energy system model to the distribution network; is the upper limit of the power input by the distribution network into the electro-thermal interconnected integrated energy system model; The expression of the thermal energy coupling balance model is as follows: ; In the formula: is the thermal load power demand satisfied by the electro-thermal interconnected integrated energy system model at time ;

[0008] According to one aspect of the present invention, the expression of the coupling relationship model of the integrated energy system including optical storage and charging is as follows: ; In the formula: is the power transmitted by the integrated optical storage and charging system model to the distribution network at time ; is the power transmitted by the integrated electric and thermal energy system model to the distribution network at time ; is the transmission power of the connecting line at the connection point of the coupling relationship model of the integrated energy system including optical storage and charging; is the upper limit of the transmission power of the connecting line at the connection point of the coupling relationship model of the integrated energy system including optical storage and charging; is the power received by the integrated optical storage and charging system model from the distribution network at time ; is the power input by the distribution network to the integrated electric and thermal energy system model at time ; is the thermal power of the gas turbine at time ; is the recovered high-temperature flue gas volume of the supplementary combustion type waste heat boiler at the moment.

[0009] According to one aspect of the present invention, a day-ahead energy economic optimization scheduling strategy is set for the coupling relationship model of the integrated energy system, including: The scheduling simulation operation period of the day-ahead energy economic optimization scheduling of the coupling relationship model of the integrated energy system including optical storage and charging is 24 hours a day, and the resolution of the scheduling simulation operation control step is 1 hour, with a total of 24 control steps; The expression of the day-ahead energy economic optimization scheduling strategy of the coupling relationship model of the integrated energy system including optical storage and charging is as follows: ; In the formula: is the total economic cost of the day-ahead energy economic optimization scheduling of the coupling relationship model of the integrated energy system including optical storage and charging; is the total gas consumption cost of the day-ahead energy economic optimization scheduling of the coupling relationship model of the integrated energy system including optical storage and charging; is the total power purchase cost at the connection point of the day-ahead energy economic optimization scheduling of the coupling relationship model of the integrated energy system including optical storage and charging; is the total penalty cost of the interrupted charging load in the day-ahead energy economic optimization scheduling of the coupling relationship model of the integrated energy system including optical storage and charging; The total revenue of the charging service in the day-ahead energy economic optimization scheduling of the coupling relationship model of the integrated energy system including optical storage and charging; is the gas turbine at time The operating cost; For the supplementary firing type waste heat boiler at time The operating cost; The coupling relationship model of the integrated energy system including optical storage and charging, and the day-ahead energy economic optimal scheduling at time The time-of-use electricity price at the grid connection point; For the transmission power of the connecting line at the grid connection point of the coupling relationship model of the integrated energy system including optical storage and charging; For the charging pile cluster at time The percentage coefficient of the maximum interruptible charging load; For the predicted charging load power of the charging pile cluster at time For the polynomial coefficients of the penalty characteristic curve of the interrupted charging load, where the superscript Is the polynomial power; For the charging service of the integrated optical storage and charging at time The time-of-use electricity price of the charging electricity fee; For the charging service of the integrated optical storage and charging at time The time-of-use price of the service fee; For the integrated optical storage and charging system model at time Meet the load power demand of the actual charging pile cluster; For the scheduling simulation operation cycle; For the resolution of the scheduling simulation operation control step size.

[0010] According to one aspect of the present invention, an intraday rolling energy-carbon optimization scheduling strategy is set for the coupling relationship model of the integrated energy system, including: The intraday rolling cycle of the intraday rolling energy-carbon optimization scheduling of the coupling relationship model of the integrated energy system including optical storage and charging is once every 4 hours, and a total of 6 times of rolling optimization scheduling are carried out within 24 hours a day. The scheduling simulation operation cycles of the 1st, 2nd, 3rd, 4th, 5th, and 6th rolling optimization schedulings are 24 hours, 20 hours, 16 hours, 12 hours, 8 hours, and 4 hours respectively. The resolution of each scheduling simulation operation control step size is 15 minutes. The scheduling simulation operation cycles of the 1st, 2nd, 3rd, 4th, 5th, and 6th rolling optimization schedulings are 96, 80, 64, 48, 32, and 16 control step sizes respectively. The resolution of a scheduling simulation operation control step size of a day-ahead energy economic optimization scheduling includes 4 resolution of the scheduling simulation operation control step size of the intraday rolling energy-carbon optimization scheduling; The day-ahead rolling energy-carbon optimization scheduling of the coupling relationship model of the integrated solar, energy storage, charging and integrated energy system is based on the results of the day-ahead energy-economic optimization scheduling of the coupling relationship model of the integrated solar, energy storage, charging and integrated energy system. The day-ahead rolling energy-carbon optimization scheduling generally tracks the results of the day-ahead energy-economic optimization scheduling. The results of the day-ahead energy-economic optimization scheduling include the scheduling results of the gas turbine output, the transmission power of the grid connection point tie line, the heating power scheduling results of the supplementary combustion waste heat boiler, and the storage power scheduling results of the electrical energy storage device. The day-ahead rolling energy-carbon optimization scheduling only makes adjustments based on the results of the day-ahead energy-economic optimization scheduling, and adjusts the controllable unit equipment and the grid connection point power to eliminate the power balance deficit caused by the source-load power prediction error; The day-ahead rolling energy-carbon optimization scheduling of the coupling relationship model of the integrated solar, energy storage, charging and integrated energy system re-obtains the latest predicted power of photovoltaic power generation, wind power generation, electrical load, heat load, and charging pile cluster every 4 hours, and inputs the latest source-load prediction data into the current rolling optimization scheduling. The resolution of the first 16 control steps in the scheduling simulation operation cycle of each rolling optimization scheduling is the latest source-load prediction data, and the scheduling results within the scheduling simulation operation cycle of the previous rolling optimization scheduling are used as the initial quantity for the next rolling optimization scheduling; The day-ahead rolling energy-carbon optimization scheduling strategy of the coupling relationship model of the integrated solar, energy storage, charging and integrated energy system further considers the system carbon emission cost and the rolling adjustment cost on the premise of considering the energy-economic operation cost, and conducts energy-carbon collaborative optimization; The expression of the day-ahead rolling energy-carbon optimization scheduling strategy of the coupling relationship model of the integrated solar, energy storage, charging and integrated energy system is as follows: ; In the formula: is the total carbon emission cost of the day-ahead rolling energy-carbon optimization scheduling of the coupling relationship model of the integrated solar, energy storage, charging and integrated energy system; is the total economic cost of the day-ahead rolling energy-carbon optimization scheduling of the coupling relationship model of the integrated solar, energy storage, charging and integrated energy system; is the total cost of the scheduling plan adjustment of the day-ahead rolling energy-carbon optimization scheduling of the coupling relationship model of the integrated solar, energy storage, charging and integrated energy system; is the equivalent carbon emission coefficient generated by purchasing unit electrical energy of the coupling relationship model of the integrated solar, energy storage, charging and integrated energy system; is the equivalent carbon emission coefficient generated by purchasing unit natural gas of the coupling relationship model of the integrated solar, energy storage, charging and integrated energy system; is the unit price of the equivalent carbon emission; is the carbon emission intensity factor of the gas turbine; is the carbon emission quota factor per unit power generation of the gas turbine; is the carbon emission intensity factor of the supplementary combustion waste heat boiler; is the carbon emission quota factor per unit heating power of the supplementary combustion type waste heat boiler; is the total economic cost of the day-ahead energy economic optimal dispatch of the integrated energy system coupling relationship model including photovoltaics, energy storage and charging; For the supplementary combustion type waste heat boiler at time is the fuel input of the supplementary combustion natural gas; is the unit power adjustment cost coefficient of the gas turbine power generation output; For the gas turbine at time is the electric power; For the gas turbine at time under the intraday rolling carbon optimization dispatch is the electric power; is the unit power adjustment cost coefficient of the change in the transmission power of the grid connection tie line; is the transmission power of the grid connection tie line of the integrated energy system coupling relationship model including photovoltaics, energy storage and charging; For the integrated energy system coupling relationship model including photovoltaics, energy storage and charging at time under the intraday rolling carbon optimization dispatch is the transmission power of the grid connection tie line; For the supplementary combustion type waste heat boiler at time is the heating power; For the supplementary combustion type waste heat boiler at time under the intraday rolling carbon optimization dispatch is the heating power; is the unit capacity adjustment cost coefficient of the electric energy storage device; For the electric energy storage device at time is the stored electricity; For the electric energy storage device at time under the intraday rolling carbon optimization dispatch is the stored electricity; For the intraday rolling carbon optimization dispatch, it is the dispatching simulation operation cycle; is the dispatching simulation operation control step resolution.

[0011] According to one aspect of the present invention, the coupling connection conditions for setting the intraday rolling carbon optimization dispatch strategy and the day-ahead energy economic optimization dispatch strategy include: Adjustment quantity constraint, re-update to obtain the latest source-load prediction data and input it into the model, and the transformed single-objective intraday rolling carbon optimization dispatch model; The expression of the adjustment quantity constraint in the coupling connection conditions is as follows: ; In the formula: is the electric power of the gas turbine at time ; For the gas turbine at time The electric power is the intra-day rolling adjustment margin coefficient of the gas turbine is the rated installed capacity of the gas turbine is the transmission power of the connection line at the connection point of the integrated energy system coupling relationship model with photovoltaics, energy storage and charging is the transmission power of the connection line at the connection point of the integrated energy system coupling relationship model with photovoltaics, energy storage and charging under the intra-day rolling carbon-optimized scheduling is the intra-day rolling adjustment margin coefficient of the transmission power of the connection line is the upper limit of the transmission power of the connection line at the connection point of the integrated energy system coupling relationship model with photovoltaics, energy storage and charging is the heat supply power of the supplementary firing waste heat boiler at time is the heat supply power of the supplementary firing waste heat boiler at time under the intra-day rolling carbon-optimized scheduling is the intra-day rolling adjustment margin coefficient of the supplementary firing waste heat boiler is the rated installed capacity of the supplementary firing waste heat boiler is the stored electricity of the electric energy storage device at time is the stored electricity of the electric energy storage device at time under the intra-day rolling carbon-optimized scheduling is the intra-day rolling adjustment margin coefficient of the electric energy storage device is the rated capacity of the electric energy storage device The expression for re-updating and obtaining the latest source-load prediction data and inputting it into the model in the coupling connection condition is as follows ; In the formula is the maximum predicted output power of the wind turbine at time is the electric load power demand satisfied by the electro-thermal interconnected integrated energy system model at time is the heat load power demand satisfied by the electro-thermal interconnected integrated energy system model at time is the predicted power generation of the photovoltaic array in the integrated photovoltaic, energy storage and charging system model at time is the predicted charging load power of the charging pile cluster at time is to re-update and obtain the latest source-load prediction data, and assign values respectively to the maximum predicted output power of the wind turbine at time and the electro-thermal interconnected integrated energy system model at time​​​​​​​​ Satisfied electrical load power demand , the electro-thermal interconnected integrated energy system model at time Satisfied thermal load power demand , the photovoltaic array at time Predicted power generation power and the charging pile cluster at time Predicted charging load power in the first 16 control step resolutions of the scheduling simulation operation cycle of each rolling optimal scheduling; Is the symbol re-assigned after data update; Is the set of scheduling simulation operation cycles of each rolling optimal scheduling; Is to re-update and obtain the latest source-load predicted power every 4 hours for the integrated energy system with photovoltaics, energy storage and charging integrated within-day rolling energy-carbon optimization scheduling; Is the scheduling simulation operation cycle under the within-day rolling energy-carbon optimization scheduling; In the transformed single-objective within-day rolling energy-carbon optimization scheduling model in the coupling connection condition, the expression is as follows: ; In the formula: Is the total carbon emission cost of the within-day rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with photovoltaics, energy storage and charging integrated; Is the total economic cost of the within-day rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with photovoltaics, energy storage and charging integrated; Is the total cost of schedule adjustment of the within-day rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with photovoltaics, energy storage and charging integrated; Are different weight coefficients corresponding to different single-objective optimization functions.

[0012] To achieve the above object, the present invention also provides a multi-time-scale energy-carbon optimization system for an integrated energy system with photovoltaics, energy storage and charging integrated, including: Data information acquisition module, which acquires the initial start-up data information of the energy system operation; Photovoltaic, energy storage and charging integrated system model construction module, which establishes a photovoltaic, energy storage and charging integrated system model based on the initial start-up data information, including a photovoltaic power generation model, an electrical energy storage model, a charging pile cluster model, and a photovoltaic, energy storage and charging integrated system energy coupling balance model; Electro-thermal interconnected integrated energy system model construction module, which establishes an electro-thermal interconnected integrated energy system model based on the initial start-up data information, including a gas turbine model, a supplementary combustion waste heat boiler model, a wind turbine power generation model, an electrical energy coupling balance model, and a thermal energy coupling balance model; The coupling relationship model acquisition module couples and interconnects the integrated photovoltaic, energy storage and charging system model and the integrated electric - heat interconnected energy system model to form an integrated energy system coupling relationship model with an integrated photovoltaic, energy storage and charging system; The day - ahead energy - economic optimal scheduling strategy setting module sets a day - ahead energy - economic optimal scheduling strategy for the integrated energy system coupling relationship model; The intra - day rolling energy - carbon optimal scheduling strategy setting module sets an intra - day rolling energy - carbon optimal scheduling strategy for the integrated energy system coupling relationship model; The coupling connection condition setting module sets the coupling connection conditions between the intra - day rolling energy - carbon optimal scheduling strategy and the day - ahead energy - economic optimal scheduling strategy. After the coupling connection conditions are set, an integrated energy system is formed; The result output module inputs the initial startup data information of the energy system operation into the integrated energy system and outputs the energy - carbon optimal scheduling result data information of the integrated energy system through the integrated energy system.

[0013] To achieve the above - mentioned purpose, the present invention also provides an electronic device, including a processor, a memory, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, it implements the multi - time - scale energy - carbon optimization method of the integrated energy system with an integrated photovoltaic, energy storage and charging system as described above.

[0014] To achieve the above - mentioned purpose, the present invention also provides a computer - readable storage medium. A computer program is stored on the computer - readable storage medium. When the computer program is executed by a processor, it implements the multi - time - scale energy - carbon optimization method of the integrated energy system with an integrated photovoltaic, energy storage and charging system as described above.

[0015] According to the solution of the present invention, the present invention fully considers the multi - time - scale energy - carbon collaborative operation scenarios of the integrated photovoltaic, energy storage and charging system and the integrated electric - heat energy system, and establishes fine - grained mathematical models for photovoltaic power generation, electrical energy storage, wind turbine power generation, charging pile clusters, gas turbines, supplementary - firing waste heat boilers, grid connection points, etc., which is helpful for the engineering application promotion and real - time refined analysis of the operating state of the integrated electric - heat energy system with an integrated photovoltaic, energy storage and charging system; According to the actual requirements of energy conservation, cost reduction and carbon reduction in engineering applications, the present invention proposes day - ahead and intra - day optimal scheduling strategies for the integrated electric - heat energy system with an integrated photovoltaic, energy storage and charging system, and effectively solves the technical problems of collaborative multi - scenario optimal operation, energy - carbon operation characteristic analysis, and multi - time - scale fine - grained model construction of the integrated photovoltaic, energy storage and charging system and the integrated electric - heat energy system; The present invention realizes the provision of reference and guidance for the multi-time scale operation optimization control management, energy conservation, emission reduction and cost reduction analysis, and energy economy and carbon emission tracking analysis of the source, load and storage of the integrated energy system with photovoltaic energy storage and charging through the construction of a detailed overall full-process plan for the equipment unit model, coupling relationship model, coupling connection condition model, day-ahead energy economic optimization dispatching strategy, and intra-day rolling energy-carbon optimization dispatching strategy of the integrated photovoltaic energy storage and charging system and the integrated electric and thermal energy system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Schematically shows a flowchart of a multi-time scale energy-carbon optimization method for an integrated energy system with photovoltaic energy storage and charging according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] The content of the present invention will now be described with reference to exemplary embodiments. It should be understood that the described embodiments are only for enabling those of ordinary skill in the art to better understand and thus implement the content of the present invention, rather than implying any limitation to the scope of the present invention.

[0018] As used herein, the term "comprising" and its variants are to be construed as open-ended terms meaning "including but not limited to". The term "based on" is to be construed as "at least partially based on". The terms "one embodiment" and "an embodiment" are to be construed as "at least one embodiment".

[0019] Figure 1 Schematically shows a flowchart of a multi-time scale energy-carbon optimization method for an integrated energy system with photovoltaic energy storage and charging according to an embodiment of the present invention. As Figure 1 shown, in the present embodiment, the multi-time scale energy-carbon optimization method for the integrated energy system with photovoltaic energy storage and charging, as Figure 1 shown, includes the following steps: (1) Establish an integrated photovoltaic energy storage and charging system model; The integrated photovoltaic energy storage and charging system model includes a photovoltaic power generation model, an electrical energy storage model, a charging pile cluster model, and an energy coupling balance model of the integrated photovoltaic energy storage and charging system; (1a) Photovoltaic power generation model; The photovoltaic power generation model includes a single-piece photovoltaic module mathematical model, a photovoltaic array mathematical model, and a safe operation domain model of photovoltaic power generation.

[0020] (1a-1) Single-piece photovoltaic module mathematical model; The expression of the single-piece photovoltaic module mathematical model is as follows: ; In the formula: is the predicted power generation of the photovoltaic module at time ; For the power output of a photovoltaic module under a standard specification test environment, it can be regarded as the rated power; are respectively the light intensity at the moment when the photovoltaic module generates electricity and the light intensity of the working environment of the photovoltaic module generating electricity under the standard specification test environment; is the temperature change adjustment factor for the power output of the photovoltaic module, that is, the temperature adjustment coefficient; are respectively the temperatures at the moment when the photovoltaic power generation works and the working environment temperature of the photovoltaic module generating electricity under the standard specification test environment; is the ambient temperature at the moment when the photovoltaic module generates electricity works; is the rated working temperature of the photovoltaic module generating electricity; (1a - 2) Photovoltaic array mathematical model; The expression of the photovoltaic array mathematical model is as follows: ; In the formula: is the predicted power generation of the photovoltaic array at the moment ; is the total number of photovoltaic modules in the photovoltaic array; is the predicted power generation of the photovoltaic module at the moment ; is the average total power generation efficiency of the photovoltaic array; (1a - 3) Photovoltaic power generation safe operation domain model; The expression of the photovoltaic power generation safe operation domain model is as follows: ; In the formula: is the predicted power generation of the photovoltaic array in the photovoltaic - storage - charging integrated system model at the moment ; is the predicted power generation of the photovoltaic array at the moment ; is the actual working power generation of the photovoltaic array at the moment ; is the maximum power generation of the photovoltaic array, which can be regarded as the installed capacity; is the maximum allowable light curtailment rate within the optimization scheduling period; is the scheduling simulation operation period; (1b) Electrical energy storage model; The electrical energy storage model consists of an energy time - domain relationship and an operation safety domain.

[0021] The expression of the energy time - domain relationship of the electrical energy storage model is as follows: ; In the formula: is the stored electricity of the electrical energy storage device at time ; is the stored electricity of the electrical energy storage device at time ; is the self-discharge rate of the electrical energy storage device; is the discharge power of the electrical energy storage device at time ; is the charging power of the electrical energy storage device at time ; is the charging efficiency of the electrical energy storage device; is the discharge efficiency of the electrical energy storage device; is the resolution of the scheduling simulation operation control step; is the intermediate process state variable in the linearization transformation process of the electrical energy storage device model; is the intermediate process large number value variable in the linearization transformation process of the electrical energy storage device model; The operation safety domain expression of the electrical energy storage model is as follows: ; In the formula: is the discharge power of the electrical energy storage device at time ; is the charging power of the electrical energy storage device at time ; is the upper limit of the discharge power of the electrical energy storage device; is the upper limit of the charging power of the electrical energy storage device; is the stored electricity of the electrical energy storage device at time ; is the lower limit factor of the real-time stored electricity of the electrical energy storage device; is the upper limit factor of the real-time stored electricity of the electrical energy storage device; is the rated capacity of the electrical energy storage device; is the stored electricity of the electrical energy storage device at the initial time; is the stored electricity at the end of the electrical energy storage device, that is, the stored electricity after the end of a scheduling simulation operation cycle, and can also be represented by ; is the matching degree of the initial and final states of the stored electricity of the electrical energy storage device at the beginning and end of the scheduling simulation cycle. When the value is 0, it means no requirement. When the value is 1, it means a completely matching state. When the value is other data, it means an acceptable matching degree; (1c) Charging pile cluster model; The expression of the charging pile cluster model is as follows: ; In the formula: is the percentage coefficient of the maximum interruptible charging load of the charging pile cluster at time ; For the integrated solar energy storage and charging system model at time Meet the load power demand of the actual charging pile cluster; For the charging pile cluster at time The predicted charging load power; Is the maximum allowable percentage coefficient of interrupted charging load within the optimization scheduling period; (1d) Integrated solar energy storage and charging system energy coupling balance model; The expression of the integrated solar energy storage and charging system energy coupling balance model is as follows: ; In the formula: Is the actual working power generation of the photovoltaic array at time ; Is the discharge power of the electrical energy storage device at time ; Is the power received from the distribution network by the integrated solar energy storage and charging system model at time ; Is the upper limit of the power received from the distribution network by the integrated solar energy storage and charging system model; Is the charging power of the electrical energy storage device at time ; Is the power transmitted to the distribution network by the integrated solar energy storage and charging system model at time ; Is the upper limit of the power transmitted to the distribution network by the integrated solar energy storage and charging system model; Is the integrated solar energy storage and charging system model at time Meet the load power demand of the actual charging pile cluster; Is the distribution network tie line capacity constraint of the integrated solar energy storage and charging system model; Is the intermediate process state variable in the linearization transformation process of the distribution network tie line capacity constraint of the integrated solar energy storage and charging system model; Is the intermediate process large number value variable in the linearization transformation process of the distribution network tie line capacity constraint of the integrated solar energy storage and charging system model.

[0022] (2) Establish an integrated electric-thermal energy system model; The integrated electric-thermal energy system model includes a gas turbine model, a supplementary combustion waste heat boiler model, a wind turbine power generation model, an electrical energy coupling balance model, and a thermal energy coupling balance model.

[0023] (2a) Gas turbine model; The gas turbine model includes a gas turbine operation characteristic model and a gas turbine safe operation domain constraint.

[0024] The expression of the gas turbine operation characteristic model is as follows: ; In the formula: is the electric power of the gas turbine at time ; is the power generation efficiency of the gas turbine at time ; is the fuel input of the gas turbine at time ; is the thermal power of the gas turbine at time ; is the energy loss rate of the gas turbine; is the natural gas consumption rate of the gas turbine at time ; is the calorific value of natural gas when the gas turbine burns natural gas; is the electric load rate of the gas turbine at time ; is the polynomial coefficient of the power generation efficiency characteristic curve of the gas turbine, where the superscript is the polynomial power; is the operating state Boolean variable of the gas turbine at time , where the Boolean variable takes the value of 1 when the gas turbine is running and 0 when the gas turbine is shut down; is the operating cost of the gas turbine at time ; is the natural gas price of the gas turbine at time ; The expression of the safe operating region constraint of the gas turbine is as follows: ; In the formula: is the operating state Boolean variable of the gas turbine at time , where the Boolean variable takes the value of 1 when running and 0 when shut down; is the operating state Boolean variable of the gas turbine at time , where the Boolean variable takes the value of 1 when running and 0 when shut down; is the generator tripping coefficient of the gas turbine; is the rated installed capacity of the gas turbine; is the electric power of the gas turbine at time ; is the down-ramp rate of the electric power of the gas turbine; is the up-ramp rate of the electric power of the gas turbine; is the upper limit of the number of starts of the gas turbine within the optimization scheduling period; is the scheduling simulation operation period; is the resolution of the scheduling simulation operation control step; (2b)Supplementary firing type waste heat boiler model; The expression of the supplementary firing type waste heat boiler model is as follows: ; In the formula: is the heating power of the supplementary firing type waste heat boiler at time ; is the heating efficiency of the supplementary firing type waste heat boiler; is the fuel input of the supplementary combustion natural gas of the supplementary firing type waste heat boiler at time ; is the comprehensive efficiency of high-temperature flue gas recovery of the supplementary firing type waste heat boiler; is the recovered high-temperature flue gas volume of the supplementary firing type waste heat boiler at time ; is the natural gas consumption rate of the supplementary firing type waste heat boiler at time ; is the calorific value of natural gas when the supplementary firing type waste heat boiler burns natural gas; is the operating state Boolean variable of the supplementary firing type waste heat boiler at time , where the Boolean variable takes the value of 1 when the supplementary firing type waste heat boiler is running and 0 when the supplementary firing type waste heat boiler is shut down; is the unit tripping coefficient of the supplementary firing type waste heat boiler; is the rated installed capacity of the supplementary firing type waste heat boiler; is the down-ramp rate of the electric power of the supplementary firing type waste heat boiler; is the up-ramp rate of the electric power of the supplementary firing type waste heat boiler; is the resolution of the dispatching simulation operation control step; is the operating cost of the supplementary firing type waste heat boiler at time ; is the natural gas price of the supplementary firing type waste heat boiler at time ; (2c)Fan power generation model; The fan power generation model includes a fan power generation operation characteristic model and a fan power generation safe operation constraint.

[0025] The expression of the fan power generation operation characteristic model is as follows: ; In the formula: is the maximum predicted output power of the wind turbine at time ; is the rated maximum output power of the wind turbine; is the actual working wind speed of the wind turbine at time ; is the minimum starting working wind speed of the wind turbine; is the rated operating wind speed of the wind turbine; is the extreme operating wind speed of the wind turbine; are the different fitting coefficients of the predicted output power curve of the wind turbine; The expression for the safe operation constraint of wind power generation is as follows: ; In the formula: is the maximum predicted output power of the wind turbine at time ; is the power actually input into the electro-thermal interconnected integrated energy system model by wind power generation at time ; is the penetration coefficient of wind power generation; is the total power input of the electro-thermal interconnected integrated energy system model at time ; is the wind curtailment rate during the optimization scheduling period; is the maximum allowable wind curtailment rate during the optimization scheduling period; is the upper limit value of the penetration coefficient of wind power generation; is the scheduling simulation operation period; (2d) Electrical energy coupling balance model; The expression of the electrical energy coupling balance model is as follows: ; In the formula: is the electrical power of the gas turbine at time ; is the power input from the distribution network to the electro-thermal interconnected integrated energy system model at time ; is the power transmitted from the electro-thermal interconnected integrated energy system model to the distribution network at time ; is the electrical load power demand satisfied by the electro-thermal interconnected integrated energy system model at time ; is the intermediate process state variable in the linearization transformation process of the tie line capacity constraint of the electro-thermal interconnected integrated energy system model; is the intermediate process large number value variable in the linearization transformation process of the tie line capacity constraint of the electro-thermal interconnected integrated energy system model; is the upper limit of the power transmitted from the electro-thermal interconnected integrated energy system model to the distribution network; is the upper limit of the power input from the distribution network to the electro-thermal interconnected integrated energy system model; (2e) Thermal energy coupling balance model; The expression of the thermal energy coupling balance model is as follows: ; In the formula: is the supplementary combustion type waste heat boiler at time The heating power; For the electro-thermal interconnected integrated energy system model at time To meet the heat load power demand.

[0026] (3)Construct a coupling relationship model of the integrated energy system with integrated photovoltaics, energy storage, and charging; The coupling relationship model of the integrated energy system with integrated photovoltaics, energy storage, and charging is to organically couple and interconnect the integrated photovoltaics, energy storage, and charging system model and the electro-thermal interconnected integrated energy system model to form an overall multi-energy system; The expression of the coupling relationship model of the integrated energy system with integrated photovoltaics, energy storage, and charging is as follows: ; In the formula: Is the power transmitted by the integrated photovoltaics, energy storage, and charging system model to the distribution network at time ; Is the power transmitted by the electro-thermal interconnected integrated energy system model to the distribution network at time ; Is the transmission power of the connecting line at the connection point of the integrated energy system model with integrated photovoltaics, energy storage, and charging; Is the upper limit of the transmission power of the connecting line at the connection point of the integrated energy system model with integrated photovoltaics, energy storage, and charging; Is the power received from the distribution network by the integrated photovoltaics, energy storage, and charging system model at time ; Is the power input by the distribution network to the electro-thermal interconnected integrated energy system model at time ; Is the thermal power of the gas turbine at time ; Is the recovered high-temperature flue gas volume of the supplementary combustion type waste heat boiler at time ;

[0027] (4)Set the day-ahead energy economic optimal dispatching strategy for the integrated energy system coupling relationship model; The dispatching simulation operation period of the day-ahead energy economic optimal dispatching strategy of the integrated energy system coupling relationship model with integrated photovoltaics, energy storage, and charging is 24 hours a day, and the dispatching simulation operation control step resolution is 1 hour, with a total of 24 control steps; The expression of the day-ahead energy economic optimal dispatching strategy of the integrated energy system coupling relationship model with integrated photovoltaics, energy storage, and charging is as follows: ; In the formula: Is the total economic cost of the day-ahead energy economic optimal dispatching of the integrated energy system coupling relationship model with integrated photovoltaics, energy storage, and charging; Is the total gas consumption cost of the day-ahead energy economic optimal dispatching of the integrated energy system coupling relationship model with integrated photovoltaics, energy storage, and charging; For the integrated energy system coupling relationship model with photovoltaics, energy storage, charging, the total grid connection point power purchase cost for the day-ahead energy economic optimal dispatch; For the integrated energy system coupling relationship model with photovoltaics, energy storage, charging, the total penalty cost of interrupted charging load for the day-ahead energy economic optimal dispatch; The total revenue of the charging service for the day-ahead energy economic optimal dispatch of the integrated energy system coupling relationship model with photovoltaics, energy storage, charging; For the operating cost of the gas turbine at time ; For the operating cost of the supplementary firing waste heat boiler at time ; The time-of-use electricity price at the grid connection point for the day-ahead energy economic optimal dispatch of the integrated energy system coupling relationship model with photovoltaics, energy storage, charging at time ; For the transmission power of the tie line at the grid connection point of the integrated energy system coupling relationship model with photovoltaics, energy storage, charging; For the percentage coefficient of the maximum interruptible charging load of the charging pile cluster at time ; For the predicted charging load power of the charging pile cluster at time ; For the polynomial coefficients of the penalty characteristic curve of the interrupted charging load, where the superscript is the polynomial power; For the time-of-use electricity price of the charging electricity fee of the charging service of the integrated photovoltaic, energy storage and charging system model at time ; For the time-of-use price of the service fee of the charging service of the integrated photovoltaic, energy storage and charging system model at time ; For the integrated photovoltaic, energy storage and charging system model to meet the actual charging load power demand of the charging pile cluster at time ; For the dispatching simulation operation cycle; For the dispatching simulation operation control step resolution.

[0028] (5) Set the intraday rolling carbon optimization dispatch strategy for the integrated energy system coupling relationship model; The intraday rolling period of the carbon-optimized scheduling strategy for the coupling relationship model of the integrated energy system with photovoltaics, energy storage, and charging is once every 4 hours. There are a total of 6 rolling optimizations within 24 hours of a day. The scheduling simulation operation periods of the 1st, 2nd, 3rd, 4th, 5th, and 6th rolling optimizations are 24 hours, 20 hours, 16 hours, 12 hours, 8 hours, and 4 hours respectively. The resolution of the regulation step size for each scheduling simulation operation is 15 minutes. The scheduling simulation operation periods of the 1st, 2nd, 3rd, 4th, 5th, and 6th rolling optimizations are 96, 80, 64, 48, 32, and 16 regulation step sizes respectively. The resolution of the regulation step size for the scheduling simulation operation of a day-ahead energy economic optimization scheduling contains 4 resolution of the regulation step size for the intraday rolling carbon-optimized scheduling simulation operation; The intraday rolling carbon-optimized scheduling of the coupling relationship model of the integrated energy system with photovoltaics, energy storage, and charging is based on the results of the day-ahead energy economic optimization scheduling of the coupling relationship model of the integrated energy system with photovoltaics, energy storage, and charging. The intraday rolling carbon-optimized scheduling generally tracks the results of the day-ahead energy economic optimization scheduling. The results of the day-ahead energy economic optimization scheduling include the scheduling results of the gas turbine output, the transmission power of the grid connection point tie line, the heating power scheduling results of the supplementary combustion waste heat boiler, and the storage power scheduling results of the electrical energy storage device. The intraday rolling carbon-optimized scheduling only makes adjustments based on the results of the day-ahead energy economic optimization scheduling, and adjusts the controllable unit equipment and the power of the grid connection point to eliminate the power balance deficit caused by the prediction error of the source-load power; The intraday rolling carbon-optimized scheduling of the integrated energy system with photovoltaics, energy storage, and charging updates and obtains the latest predicted power of photovoltaic power generation, wind power generation, electrical load, heat load, and charging pile cluster every 4 hours, and inputs the latest source-load prediction data into the current rolling optimization scheduling. The first 16 regulation step size resolutions of the scheduling simulation operation period of each rolling optimization scheduling are the latest source-load prediction data, and the scheduling results within the scheduling simulation operation period of the previous rolling optimization scheduling are used as the initial quantity for the next rolling optimization scheduling; On the premise of considering the energy economic operation cost, the intraday rolling carbon-optimized scheduling strategy for the coupling relationship model of the integrated energy system with photovoltaics, energy storage, and charging further considers the system carbon emission cost and the rolling adjustment cost to carry out energy-carbon collaborative optimization; The expression of the intraday rolling carbon-optimized scheduling strategy for the coupling relationship model of the integrated energy system with photovoltaics, energy storage, and charging is as follows: ; In the formula: is the total carbon emission cost of the intraday rolling carbon-optimized scheduling for the coupling relationship model of the integrated energy system with photovoltaics, energy storage, and charging; is the total economic cost of the intraday rolling carbon-optimized scheduling for the coupling relationship model of the integrated energy system with photovoltaics, energy storage, and charging; is the total cost of adjusting the intraday rolling carbon optimization scheduling plan for the integrated energy system coupling relationship model with photovoltaic energy storage and charging; is the equivalent carbon emission coefficient generated per unit of purchased electric energy for the integrated energy system coupling relationship model with photovoltaic energy storage and charging; is the equivalent carbon emission coefficient generated per unit of purchased natural gas for the integrated energy system coupling relationship model with photovoltaic energy storage and charging; is the unit price of the equivalent carbon emission; is the carbon emission intensity factor of the gas turbine; is the carbon emission quota factor per unit of power generation of the gas turbine; is the carbon emission intensity factor of the supplementary combustion waste heat boiler; is the carbon emission quota factor per unit of heating power of the supplementary combustion waste heat boiler; is the total economic cost of the day-ahead energy economic optimization scheduling for the integrated energy system coupling relationship model with photovoltaic energy storage and charging; is the supplementary combustion natural gas fuel input of the supplementary combustion waste heat boiler at time ; is the adjustment cost coefficient per unit of power of the gas turbine power generation output; is the electric power of the gas turbine at time ; is the electric power of the gas turbine at time under the intraday rolling carbon optimization scheduling; is the adjustment cost coefficient per unit of power change of the power transmission of the grid connection tie line; is the power transmission of the grid connection tie line of the integrated energy system coupling relationship model with photovoltaic energy storage and charging; is the power transmission of the grid connection tie line of the integrated energy system coupling relationship model with photovoltaic energy storage and charging under the intraday rolling carbon optimization scheduling; is the adjustment cost coefficient per unit of power of the heating output of the supplementary combustion waste heat boiler; is the heating power of the supplementary combustion waste heat boiler at time ; is the heating power of the supplementary combustion waste heat boiler at time under the intraday rolling carbon optimization scheduling; is the adjustment cost coefficient per unit of capacity of the electrical energy storage device; is the stored electricity of the electrical energy storage device at time ; is the stored electricity of the electrical energy storage device at time under the intraday rolling carbon optimization scheduling; is the scheduling simulation operation cycle under the intraday rolling carbon optimization scheduling; is the resolution of the scheduling simulation operation control step size.

[0029] (6) Set the coupling and connection conditions between the intraday rolling energy-carbon optimization scheduling strategy and the day-ahead energy-economic optimization scheduling strategy; Setting the coupling and connection conditions between the intraday rolling energy-carbon optimization scheduling strategy and the day-ahead energy-economic optimization scheduling strategy includes: adjustment quantity constraint, re-updating to obtain the latest source-load prediction data and input it into the model, and the transformed single-objective intraday rolling energy-carbon optimization scheduling model; The expression of the adjustment quantity constraint in the coupling and connection conditions is as follows: ; In the formula: is the electric power of the gas turbine at time ; is the electric power of the gas turbine at time under the intraday rolling energy-carbon optimization scheduling; is the intraday rolling adjustment margin coefficient of the gas turbine; is the rated installed capacity of the gas turbine; is the transmission power of the connecting line at the connection point of the integrated energy system coupling relationship model including photovoltaic, energy storage and charging; is the transmission power of the connecting line at the connection point of the integrated energy system coupling relationship model including photovoltaic, energy storage and charging under the intraday rolling energy-carbon optimization scheduling; is the intraday rolling adjustment margin coefficient of the transmission power of the connecting line; is the upper limit of the transmission power of the connecting line at the connection point of the integrated energy system coupling relationship model including photovoltaic, energy storage and charging; is the heating power of the supplementary combustion type waste heat boiler at time ; is the heating power of the supplementary combustion type waste heat boiler at time under the intraday rolling energy-carbon optimization scheduling; is the intraday rolling adjustment margin coefficient of the supplementary combustion type waste heat boiler; is the rated installed capacity of the supplementary combustion type waste heat boiler; is the stored electricity of the electric energy storage device at time ; is the stored electricity of the electric energy storage device at time under the intraday rolling energy-carbon optimization scheduling; is the intraday rolling adjustment margin coefficient of the electric energy storage device; is the rated capacity of the electric energy storage device; The expression of re-updating to obtain the latest source-load prediction data and input it into the model in the coupling and connection conditions is as follows: ; In the formula: is the maximum predicted output power of the wind turbine at time ; is the electrical load power demand satisfied by the electro-thermal integrated energy system model at time ; is the thermal load power demand satisfied by the electro-thermal integrated energy system model at time ; is the predicted power generation of the photovoltaic array in the integrated energy system model of photovoltaic energy storage and charging at time ; is the predicted charging load power of the charging pile cluster at time ; is to re-update and obtain the latest source-load prediction data, and assign values to the maximum predicted output power of the wind turbine at time respectively, the electrical load power demand satisfied by the electro-thermal integrated energy system model at time , the thermal load power demand satisfied by the electro-thermal integrated energy system model at time , the predicted power generation of the photovoltaic array at time , the predicted charging load power of the charging pile cluster at time in the first 16 control step resolutions of each rolling optimization scheduling simulation operation cycle of ; ; and the predicted charging load power of the charging pile cluster at time ; ; is the symbol re-assigned after data update; is the set of scheduling simulation operation cycles of each rolling optimization scheduling; is to re-update and obtain the latest source-load predicted power every 4 hours for the intra-day rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with photovoltaic energy storage and charging; is the scheduling simulation operation cycle under the intra-day rolling energy-carbon optimization scheduling; The intra-day rolling energy-carbon optimization scheduling model of the integrated energy system coupling relationship model with photovoltaic energy storage and charging is a multi-objective optimization problem. Each optimization objective function is to solve the problem of minimizing economy, and the dimension units are consistent. It is linearly weighted and transformed into a single-objective optimization model. The expression of the transformed single-objective intra-day rolling energy-carbon optimization scheduling model in the coupling connection condition is as follows: ; In the formula: is the total carbon emission cost of the intra-day rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with photovoltaic energy storage and charging; is the total economic cost of the intra-day rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with photovoltaic energy storage and charging; is the total cost of schedule adjustment for the intra-day rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with photovoltaic energy storage and charging; They are different weight coefficients corresponding to different single-objective optimization functions.

[0030] (7) Input the initial start-up data information of the integrated energy system operation into the integrated energy system, and output the energy-carbon optimization dispatch result data information of the integrated energy system through the integrated energy system; The input initial start-up data information of the integrated energy system operation includes: single-piece photovoltaic module parameters, photovoltaic array parameters, maximum power generation of the photovoltaic array, allowable maximum light curtailment rate, charging efficiency of the electrical energy storage device, discharging efficiency of the electrical energy storage device, upper limit of the discharging power of the electrical energy storage device, upper limit of the charging power of the electrical energy storage device, initial stored electricity of the electrical energy storage device, percentage coefficient of the maximum interruptible charging load that the charging pile cluster can have at each moment, allowable maximum interruptible charging load percentage coefficient during the optimization dispatch period, upper limit of the power transmitted by the integrated photovoltaic-energy storage-charging system model to the distribution network, upper limit of the power received by the integrated photovoltaic-energy storage-charging system model from the distribution network, energy loss rate of the gas turbine, polynomial coefficients of the gas turbine power generation efficiency characteristic curve, natural gas price of the gas turbine at each moment, tripping coefficient of the gas turbine, rated installed capacity of the gas turbine, electrical power of the gas turbine at each moment, downward ramp rate of the electrical power of the gas turbine, upward ramp rate of the electrical power of the gas turbine, upper limit of the start-up times of the gas turbine during the optimization dispatch period, heating efficiency of the supplementary-fired waste heat boiler, comprehensive high-temperature flue gas recovery efficiency of the supplementary-fired waste heat boiler, tripping coefficient of the supplementary-fired waste heat boiler, rated installed capacity of the supplementary-fired waste heat boiler, downward ramp rate of the electrical power of the supplementary-fired waste heat boiler, upward ramp rate of the electrical power of the supplementary-fired waste heat boiler, natural gas price of the supplementary-fired waste heat boiler at each moment, rated maximum output power of the wind turbine, minimum start-up working wind speed of the wind turbine, rated working wind speed of the wind turbine, ultimate working wind speed of the wind turbine, different fitting coefficients of the wind turbine predicted output curve, penetration coefficient of wind power generation, wind curtailment rate during the optimization dispatch period, allowable maximum wind curtailment rate during the optimization dispatch period, upper limit value of the penetration coefficient of wind power generation, upper limit of the power transmitted by the integrated electric-thermal energy system model to the distribution network, upper limit of the power input by the distribution network to the integrated electric-thermal energy system model, upper limit of the transmission power of the connecting line at the connection point of the integrated photovoltaic-energy storage-charging system coupling relationship model, time-of-use electricity price at the connection point at each moment of the day-ahead energy-economic optimization dispatch of the integrated photovoltaic-energy storage-charging system coupling relationship model, percentage coefficient of the maximum interruptible charging load that the charging pile cluster can have at each moment, polynomial coefficients of the penalty characteristic curve of the interrupted charging load, time-of-use electricity price of the charging service of the integrated photovoltaic-energy storage-charging system model at each moment, time-of-use service price of the charging service of the integrated photovoltaic-energy storage-charging system model at each moment, equivalent carbon emission coefficient, equivalent carbon emission unit price, carbon emission intensity factor, carbon emission quota factor, unit power adjustment cost coefficient, intraday rolling adjustment margin coefficient, different weight coefficients corresponding to different single-objective optimization functions, and other information.

[0031] The output of the energy-carbon optimization dispatch result data information of the integrated energy system includes: the actual power generation power of the photovoltaic array at each moment, the stored electricity of the electrical energy storage device at each moment, the discharge power of the electrical energy storage device at each moment, the charging power of the electrical energy storage device at each moment, the photovoltaic-storage-charging integrated system model meeting the power demand of the actual charging pile cluster at each moment, the power received from the distribution network by the photovoltaic-storage-charging integrated system model at each moment, the power transmitted to the distribution network by the photovoltaic-storage-charging integrated system model at each moment, the electrical 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, the numerical value of the operating state Boolean variable of the gas turbine at each moment, the heating power of the supplementary-firing waste heat boiler at each moment, the fuel input of the supplementary-firing natural gas of the supplementary-firing waste heat boiler at each moment, the amount of recovered high-temperature flue gas of the supplementary-firing waste heat boiler at each moment, the numerical value of the operating state Boolean variable of the supplementary-firing waste heat boiler at each moment, the operating cost of the supplementary-firing waste heat boiler at each moment, the actual power input into the integrated energy system by the fan power generation at each moment, the power input into the electro-thermal interconnected integrated energy system model by the distribution network at each moment, the power transmitted from the electro-thermal interconnected integrated energy system model to the distribution network at each moment, the transmission power of the connecting line of the integrated energy system coupling relationship model with photovoltaic-storage-charging integration, the total economic cost of the day-ahead energy-economic optimization dispatch of the integrated energy system coupling relationship model with photovoltaic-storage-charging integration, the total gas consumption cost of the day-ahead energy-economic optimization dispatch of the integrated energy system coupling relationship model with photovoltaic-storage-charging integration, the total power purchase cost at the connection point of the day-ahead energy-economic optimization dispatch of the integrated energy system coupling relationship model with photovoltaic-storage-charging integration, the total penalty cost of interrupting the charging load of the day-ahead energy-economic optimization dispatch of the integrated energy system coupling relationship model with photovoltaic-storage-charging integration, the total revenue of the charging business of the day-ahead energy-economic optimization dispatch of the integrated energy system coupling relationship model with photovoltaic-storage-charging integration, the total carbon emission cost of the intraday rolling energy-carbon optimization dispatch of the integrated energy system coupling relationship model with photovoltaic-storage-charging integration, the total economic cost of the intraday rolling energy-carbon optimization dispatch of the integrated energy system coupling relationship model with photovoltaic-storage-charging integration, the total cost of the plan adjustment of the intraday rolling energy-carbon optimization dispatch, the electrical power of the gas turbine at each moment under the intraday rolling energy-carbon optimization dispatch, the transmission power of the connecting line of the integrated energy system coupling relationship model with photovoltaic-storage-charging integration under the intraday rolling energy-carbon optimization dispatch, the heating power of the supplementary-firing waste heat boiler at each moment under the intraday rolling energy-carbon optimization dispatch, the stored electricity of the electrical energy storage device at each moment under the intraday rolling energy-carbon optimization dispatch, the information such as the transformed single-objective intraday rolling energy-carbon optimization dispatch result.

[0032] According to the above solution of the present invention, the present invention fully considers the multi-time-scale energy-carbon collaborative operation scenarios of the integrated photovoltaic energy storage charging system and the integrated electric and thermal energy system, and establishes fine-grained mathematical models for photovoltaic power generation, electrical energy storage, wind power generation, charging pile clusters, gas turbines, supplementary combustion waste heat boilers, grid connection points, etc., which is helpful for the engineering application promotion and real-time refined analysis of the operating status of the integrated electric and thermal energy system including the integrated photovoltaic energy storage charging system; According to the actual requirements of energy conservation, cost reduction and carbon reduction in engineering applications, the present invention proposes day-ahead and intra-day optimal scheduling strategies for the integrated electric and thermal energy system including the integrated photovoltaic energy storage charging system, effectively solving the technical problems of collaborative multi-scenario optimal operation of the integrated photovoltaic energy storage charging system and the integrated electric and thermal energy system, analysis of energy-carbon operation characteristics, and construction of multi-time-scale fine-grained models; By constructing a detailed overall full-process solution for the equipment unit model, coupling relationship model, coupling connection condition model, day-ahead energy economic optimal scheduling strategy, and intra-day rolling energy-carbon optimal scheduling strategy of the integrated photovoltaic energy storage charging system and the integrated electric and thermal energy system, the present invention realizes that it can provide reference and guidance for the multi-time-scale operation optimization regulation and management of the integrated energy system including the integrated photovoltaic energy storage charging system, energy conservation, emission reduction and cost reduction analysis, and energy economy and carbon emission tracking analysis of the source-load-storage.

[0033] Furthermore, to achieve the above object, the present invention also provides a multi-time-scale energy-carbon optimization system for an integrated energy system including integrated photovoltaic energy storage charging, comprising: A data information acquisition module, which acquires the initial startup data information of the energy system operation; An integrated photovoltaic energy storage charging system model construction module, which establishes an integrated photovoltaic energy storage charging system model based on the initial startup data information, including a photovoltaic power generation model, an electrical energy storage model, a charging pile cluster model, and an energy coupling balance model of the integrated photovoltaic energy storage charging system; An integrated electric and thermal interconnected energy system model construction module, which establishes an integrated electric and thermal interconnected energy system model based on the initial startup data information, including a gas turbine model, a supplementary combustion waste heat boiler model, a wind power generation model, an electrical energy coupling balance model, and a thermal energy coupling balance model; A coupling relationship model acquisition module, which couples and interconnects the integrated photovoltaic energy storage charging system model and the integrated electric and thermal interconnected energy system model to form an integrated energy system coupling relationship model including integrated photovoltaic energy storage charging; A day-ahead energy economic optimal scheduling strategy setting module, which sets a day-ahead energy economic optimal scheduling strategy for the integrated energy system coupling relationship model; An intra-day rolling energy-carbon optimal scheduling strategy setting module, which sets an intra-day rolling energy-carbon optimal 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 initial startup data information of the energy system operation into the comprehensive energy system and outputs the energy-carbon optimization scheduling result data information of the comprehensive energy system through the comprehensive energy system.

[0034] According to the above multi-time scale energy-carbon optimization system of the integrated energy system with photovoltaics, energy storage and charging integration of the present invention, the above multi-time scale energy-carbon optimization method of the integrated energy system with photovoltaics, energy storage and charging integration can be realized. The specific process steps are as described above and will not be elaborated here.

[0035] Furthermore, to achieve the above object, the present invention also provides an electronic device, including a processor, a memory, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, the above multi-time scale energy-carbon optimization method of the integrated energy system with photovoltaics, energy storage and charging integration is realized.

[0036] Furthermore, to achieve the above object, 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 above multi-time scale energy-carbon optimization method of the integrated energy system with photovoltaics, energy storage and charging integration is realized.

[0037] Those of ordinary skill in the art can realize that the modules and algorithm steps described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0038] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the above-described devices and equipment can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated here.

[0039] In the embodiments provided in the present 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 only a logical function division. In actual implementation, there may be other division methods. For example, 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 displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or modules can be in electrical, mechanical or other forms.

[0040] The modules described as separate components may or may not be physically separated. The components shown as modules may or may not be physical modules, that is, they can be located in one place or distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of the embodiments of the present invention.

[0041] In addition, each functional module in the embodiments of the present invention can be integrated in a processing module, or each module can exist physically alone, or two or more modules can be integrated in one module.

[0042] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method for sending / receiving energy-saving signals in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical discs that can store program codes.

[0043] The above description is only a preferred embodiment of the present application and an explanation of the applied technical principles. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the technical solutions formed by mutually replacing the above features with the (but not limited to) technical features with similar functions disclosed in the present application.

[0044] It should be understood that the magnitude of the sequence numbers of the steps in the summary of the invention and the embodiments of the present invention does not absolutely indicate the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

Claims

1. Multi-time scale energy-carbon optimization method for integrated energy system with photovoltaic energy storage and charging, characterized in that, Including: Establishing a photovoltaic-storage-charging integrated system model, including a photovoltaic power generation model, an electrical energy storage model, a charging pile cluster model, and a photovoltaic-storage-charging integrated system energy coupling balance model; Establishing a thermal-electric interconnected integrated energy system model, including a gas turbine model, a supplementary-fired waste heat boiler model, a wind turbine power generation model, an electrical energy coupling balance model, and a thermal energy coupling balance model; Coupling and interconnecting the photovoltaic-storage-charging integrated system model and the thermal-electric interconnected integrated energy system model to form an integrated energy system coupling relationship model with photovoltaic-storage-charging integration; Setting a day-ahead energy economic optimal dispatch strategy for the integrated energy system coupling relationship model; Setting an intra-day rolling energy-carbon optimal dispatch strategy for the integrated energy system coupling relationship model; Setting the coupling connection conditions between the intra-day rolling energy-carbon optimal dispatch strategy and the day-ahead energy economic optimal dispatch strategy. After the coupling connection conditions are set, an integrated energy system is formed; Inputting the integrated energy system operation initialization start data information into the integrated energy system, and outputting the integrated energy system energy-carbon optimal dispatch result data information through the integrated energy system.

2. The multi-time scale energy-carbon optimization method for the integrated energy system with photovoltaics, energy storage and charging according to claim 1, characterized in that, The photovoltaic power generation model includes: a single-piece photovoltaic module mathematical model, a photovoltaic array mathematical model, and a photovoltaic power generation safe operation domain model; The expression of the mathematical model of the single-piece photovoltaic module is as follows: ; Where: is the predicted power generation of the photovoltaic module at time ; is the power generation output of the photovoltaic module under the standard test environment, which can be regarded as the rated power; are respectively the light intensity when the photovoltaic module generates electricity at time and the light intensity of the working environment of the photovoltaic module for power generation under the standard test environment; is the temperature change adjustment factor for the power generation output of the photovoltaic module, that is, the temperature adjustment coefficient; are respectively the temperature when the photovoltaic power generation is at time and the working environment temperature of the photovoltaic module for power generation under the standard test environment; is the ambient temperature when the photovoltaic module generates electricity at time ; is the rated working temperature of the photovoltaic module for power generation; The expression of the mathematical model of the photovoltaic array is as follows: ; Wherein: is the predicted power generation of the photovoltaic array at time ; is the total number of photovoltaic modules in the photovoltaic array; is the predicted power generation of the photovoltaic module at time ; 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: ; Wherein: is the predicted power generation of the photovoltaic array at time ; is the predicted power generation of the photovoltaic array at time ; is the actual power generation of the photovoltaic array at time ; is the maximum power generation of the photovoltaic array, which can be regarded as the installed capacity; is the maximum allowable light curtailment rate within the optimization scheduling period; is the scheduling simulation operation period; The electrical energy storage model consists of an energy time-domain relationship and an operation safety domain; The energy time-domain relationship expression of the electric energy storage model is as follows: ; Where: is the stored power of the electrical energy storage device at time ; is the stored power of the electrical energy storage device at time ; is the self-discharge rate of the electrical energy storage device; is the discharge power of the electrical energy storage device at time ; is the charging power of the electrical energy storage device at time ; is the charging efficiency of the electrical energy storage device; is the discharge efficiency of the electrical energy storage device; is the resolution of the scheduling simulation operation control step; is the intermediate process state variable in the linearization transformation process of the electrical energy storage device model; is the intermediate process large number value variable in the linearization transformation process of the electrical energy storage device model; The operating safety domain expression of the electric energy storage model is as follows: ; Where: is the discharge power of the electrical energy storage device at time ; is the charging power of the electrical energy storage device at time ; is the upper limit of the discharge power of the electrical energy storage device; is the upper limit of the charging power of the electrical energy storage device; is the stored electrical energy of the electrical energy storage device at time ; is the lower limit factor of the real-time stored electrical energy of the electrical energy storage device; is the upper limit factor of the real-time stored electrical energy of the electrical energy storage device; is the rated capacity of the electrical energy storage device; is the initial stored electrical energy of the electrical energy storage device; is the stored electrical energy at the end of the electrical energy storage device, that is, the stored electrical energy after the end of a dispatching simulation operation cycle, and can also be represented by ; is the matching degree of the initial and final states of the stored electrical energy of the electrical energy storage device at the start and end of the dispatching simulation cycle. When the value is 0, it means there is no requirement. When the value is 1, it means a completely matching state. When the value is other data, it means an acceptable matching degree; The expression of the charging pile cluster model is as follows: ; Wherein: is the percentage coefficient of the maximum interruptible charging load of the charging pile cluster at time ; is the integrated photovoltaic energy storage charging system model at time meeting the actual load power demand of the charging pile cluster; is the predicted charging load power of the charging pile cluster at time ; is the maximum allowable interruptible charging load percentage coefficient within the optimization scheduling period. The expression of the energy coupling balance model of the integrated photovoltaic-energy storage-charging system is as follows: ; Where: is the power received from the distribution network by the integrated solar-storage-charging system model at time ; is the upper limit of the power received from the distribution network by the integrated solar-storage-charging system model; is the power transmitted to the distribution network by the integrated solar-storage-charging system model at time ; is the upper limit of the power transmitted to the distribution network by the integrated solar-storage-charging system model; is the capacity constraint of the distribution network connection line of the integrated solar-storage-charging system model; is the intermediate process state variable in the linearization transformation process of the capacity constraint of the distribution network connection line of the integrated solar-storage-charging system model; is the intermediate process large number value variable in the linearization transformation process of the capacity constraint of the distribution network connection line of the integrated solar-storage-charging system model.

3. The multi-time scale energy-carbon optimization method for the integrated energy system with photovoltaics, energy storage and charging according to claim 1, wherein The gas turbine model includes: a gas turbine operation characteristic model and a gas turbine safe operation domain constraint; The expression of the operating characteristic model of the gas turbine is as follows: ; Where: is the electric power of the gas turbine at time ; is the power generation efficiency of the gas turbine at time ; is the fuel input of the gas turbine at time ; is the thermal power of the gas turbine at time ; is the energy loss rate of the gas turbine; is the natural gas consumption rate of the gas turbine at time ; is the calorific value of natural gas when the gas turbine burns natural gas; is the electrical load rate of the gas turbine at time ; is the polynomial coefficient of the power generation efficiency characteristic curve of the gas turbine, where the superscript is the polynomial power; is the operating state Boolean variable of the gas turbine at time , where the Boolean variable takes the value of 1 when the gas turbine is running and 0 when the gas turbine is shut down; is the operating cost of the gas turbine at time ; is the natural gas price of the gas turbine at time ; The expression for the constraint of the safe operating range of the gas turbine is as follows: ; Wherein: is the electric power of the gas turbine at time ; is the operating state Boolean variable of the gas turbine at time , where the Boolean variable takes the value of 1 during operation and 0 during shutdown; is the load shedding coefficient of the gas turbine; is the rated installed capacity of the gas turbine; is the down-ramp rate of the electric power of the gas turbine; is the up-ramp rate of the electric power of the gas turbine; is the upper limit of the start-up times of the gas turbine within the optimization scheduling period; is the scheduling simulation operation period; is the resolution of the scheduling simulation operation control step size; The expression of the supplementary combustion type waste heat boiler model is as follows: ; Wherein: is the heating power of the supplementary firing waste heat boiler at time ; is the heating power of the supplementary firing waste heat boiler at time ; is the heating efficiency of the supplementary firing waste heat boiler; is the fuel input of the supplementary combustion natural gas of the supplementary firing waste heat boiler at time ; is the comprehensive efficiency of high-temperature flue gas recovery of the supplementary firing waste heat boiler; is the recovered high-temperature flue gas volume of the supplementary firing waste heat boiler at time ; is the natural gas consumption rate of the supplementary firing waste heat boiler at time ; is the calorific value of natural gas when the supplementary firing waste heat boiler burns natural gas; is the operating state Boolean variable of the supplementary firing waste heat boiler at time , where the Boolean variable takes the value of 1 when the supplementary firing waste heat boiler is running and 0 when the supplementary firing waste heat boiler is shut down; is the unit tripping coefficient of the supplementary firing waste heat boiler; is the rated installed capacity of the supplementary firing waste heat boiler; is the down-ramp rate of the electric power of the supplementary firing waste heat boiler; is the up-ramp rate of the electric power of the supplementary firing waste heat boiler; is the resolution of the dispatching simulation operation control step; is the operating cost of the supplementary firing waste heat boiler at time ; is the natural gas price of the supplementary firing waste heat boiler at time ; The wind turbine power generation model includes: a wind turbine power generation operation characteristic model and a wind turbine power generation safe operation constraint; The expression of the operating characteristic model of the fan for power generation is as follows: ; Wherein: is the maximum predicted output power of the wind turbine at time ; is the rated maximum output power of the wind turbine; is the actual working wind speed of the wind turbine at time ; is the minimum starting working wind speed of the wind turbine; is the rated working wind speed of the wind turbine; is the limit working wind speed of the wind turbine; are the different fitting coefficients of the predicted output curve of the wind turbine; The expression for the safe operation constraint of the fan power generation is as follows: ; Wherein: is the maximum predicted output power of the wind turbine at time ; is the power actually input into the electro-thermal integrated energy system model by the wind turbine power generation at time ; is the penetration coefficient of the wind turbine power generation; is the total power input of the electro-thermal integrated energy system model at time ; is the wind curtailment rate during the optimization scheduling period; is the maximum allowable wind curtailment rate during the optimization scheduling period; is the upper limit value of the penetration coefficient of the wind turbine power generation; The expression of the electric energy coupling balance model is as follows: ; Where: is the power input by the distribution network to the electro-thermal integrated energy system model at time ; is the power transmitted by the electro-thermal integrated energy system model to the distribution network at time ; is the electrical load power demand satisfied by the electro-thermal integrated energy system model at time ; is the intermediate process state variable in the linearization transformation process of the tie-line capacity constraint of the electro-thermal integrated energy system model; is the intermediate process large number value variable in the linearization transformation process of the tie-line capacity constraint of the electro-thermal integrated energy system model; is the upper limit of the power transmitted by the electro-thermal integrated energy system model to the distribution network; is the upper limit of the power input by the distribution network to the electro-thermal integrated energy system model. The expression of the thermal energy coupling equilibrium model is as follows: ; In the formula: is the thermal load power demand satisfied by the electro-thermal integrated energy system model at time .

4. The multi-time scale energy-carbon optimization method for the integrated energy system with photovoltaics, energy storage and charging according to claim 1, characterized in that The expression of the integrated energy system coupling relationship model with photovoltaic-storage-charging integration is as follows: ； Wherein: is the power transmitted by the integrated solar energy storage and charging system model to the distribution network at time ; is the power transmitted by the integrated electric and thermal energy system model to the distribution network at time ; is the transmission power of the connecting line at the connection point of the integrated energy system coupling relationship model with integrated solar energy storage and charging; is the upper limit of the transmission power of the connecting line at the connection point of the integrated energy system coupling relationship model with integrated solar energy storage and charging; is the power received by the integrated solar energy storage and charging system model from the distribution network at time ; is the power input by the distribution network to the integrated electric and thermal energy system model at time ; is the thermal power of the gas turbine at time ; is the recovered high-temperature flue gas volume of the supplementary combustion type waste heat boiler at time .

5. The multi-time scale energy-carbon optimization method for the integrated energy system with photovoltaics, energy storage and charging according to claim 1, characterized in that, Setting the day-ahead energy economic optimal dispatch strategy for the integrated energy system coupling relationship model, including: The dispatch simulation operation cycle of the day-ahead energy economic optimal dispatch of the integrated energy system coupling relationship model with photovoltaic-storage-charging integration is 24 hours a day, and the dispatch simulation operation regulation step resolution is 1 hour, with a total of 24 regulation steps; The expression of the day-ahead energy economic optimal dispatch strategy of the integrated energy system coupling relationship model with photovoltaic-storage-charging integration is as follows: ； Wherein: is the total economic cost of the day-ahead energy economic optimal dispatch of the integrated energy system coupling relationship model with photovoltaic, energy storage, charging and discharging; is the total gas consumption cost of the day-ahead energy economic optimal dispatch of the integrated energy system coupling relationship model with photovoltaic, energy storage, charging and discharging; is the total grid-connected power purchase cost of the day-ahead energy economic optimal dispatch of the integrated energy system coupling relationship model with photovoltaic, energy storage, charging and discharging; is the total penalty cost of the interrupted charging load of the day-ahead energy economic optimal dispatch of the integrated energy system coupling relationship model with photovoltaic, energy storage, charging and discharging; The total revenue of the charging service of the day-ahead energy economic optimal dispatch of the integrated energy system coupling relationship model with photovoltaic, energy storage, charging and discharging; is the operating cost of the gas turbine at time ; is the operating cost of the supplementary firing waste heat boiler at time ; The time-of-use electricity price at the grid connection point of the day-ahead energy economic optimal dispatch of the integrated energy system coupling relationship model with photovoltaic, energy storage, charging and discharging at time ; is the transmission power of the connecting line at the grid connection point of the integrated energy system coupling relationship model with photovoltaic, energy storage, charging and discharging; is the percentage coefficient of the maximum interruptible charging load of the charging pile cluster at time ; is the predicted charging load power of the charging pile cluster at time ; is the polynomial coefficient of the penalty characteristic curve of the interrupted charging load, where the superscript is the polynomial power; is the time-of-use electricity price of the charging electricity fee of the charging service of the photovoltaic, energy storage and charging integrated system model at time ; is the time-of-use price of the service fee of the charging service of the photovoltaic, energy storage and charging integrated system model at time ; is to meet the actual charging load power demand of the charging pile cluster at time of the photovoltaic, energy storage and charging integrated system model; is the dispatching simulation operation cycle; is the dispatching simulation operation control step resolution.

6. The multi-time scale energy-carbon optimization method for the integrated energy system with photovoltaics, energy storage and charging according to claim 1, characterized in that Setting the intra-day rolling energy-carbon optimal dispatch strategy for the integrated energy system coupling relationship model, including: The intra-day rolling cycle of the intra-day rolling energy-carbon optimal dispatch strategy of the integrated energy system coupling relationship model with photovoltaic-storage-charging integration is once every 4 hours. There are a total of 6 rolling optimal dispatches within 24 hours a day. The dispatch simulation operation cycles of the 1st, 2nd, 3rd, 4th, 5th, and 6th rolling optimal dispatches are 24 hours, 20 hours, 16 hours, 12 hours, 8 hours, and 4 hours respectively. The dispatch simulation operation regulation step resolution for each time is 15 minutes. The dispatch simulation operation cycles of the 1st, 2nd, 3rd, 4th, 5th, and 6th rolling optimal dispatches are 96, 80, 64, 48, 32, and 16 regulation steps respectively. One dispatch simulation operation regulation step resolution of the day-ahead energy economic optimal dispatch contains 4 dispatch simulation operation regulation step resolutions of the intra-day rolling energy-carbon optimal dispatch. The intraday rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with photovoltaics, energy storage, and charging is based on the results of the day-ahead energy-economic optimization scheduling of the integrated energy system coupling relationship model with photovoltaics, energy storage, and charging. The intraday rolling energy-carbon optimization scheduling generally tracks the results of the day-ahead energy-economic optimization scheduling. The results of the day-ahead energy-economic optimization scheduling include the output scheduling results of the gas turbine, the transmission power scheduling results of the grid connection tie line, the heating power scheduling results of the supplementary combustion waste heat boiler, and the stored electricity scheduling results of the electrical energy storage device. The intraday rolling energy-carbon optimization scheduling only makes adjustments based on the results of the day-ahead energy-economic optimization scheduling, and adjusts the controllable unit equipment and the grid connection point power to eliminate the power balance deficit caused by the source-load power prediction error; The intraday rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with photovoltaics, energy storage, and charging re-updates and obtains the latest predicted power of photovoltaic power generation, wind power generation, electrical load, heat load, and charging pile cluster every 4 hours, and inputs the latest source-load prediction data into the current rolling optimization scheduling. The resolution of the first 16 control steps in the scheduling simulation operation cycle of each rolling optimization scheduling is the latest source-load prediction data, and the scheduling results within the scheduling simulation operation cycle of the previous rolling optimization scheduling are used as the initial quantity for the next rolling optimization scheduling; The intraday rolling energy-carbon optimization scheduling strategy of the integrated energy system coupling relationship model with photovoltaics, energy storage, and charging further considers the system carbon emission cost and the rolling adjustment cost on the premise of considering the energy-economic operation cost, and conducts energy-carbon collaborative optimization; The expression of the intraday rolling energy-carbon optimization scheduling strategy of the integrated energy system coupling relationship model with photovoltaics, energy storage, and charging is as follows: ； In the formula: is the total carbon emission cost of the day-ahead rolling energy-carbon optimization scheduling for the integrated energy system coupling relationship model with photovoltaics, energy storage, charging, and discharging; is the total economic cost of the day-ahead rolling energy-carbon optimization scheduling for the integrated energy system coupling relationship model with photovoltaics, energy storage, charging, and discharging; is the total cost of the plan adjustment for the day-ahead rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with photovoltaics, energy storage, charging, and discharging; is the equivalent carbon emission coefficient generated by purchasing a unit of electric energy for the integrated energy system coupling relationship model with photovoltaics, energy storage, charging, and discharging; is the equivalent carbon emission coefficient generated by purchasing a unit of natural gas for the integrated energy system coupling relationship model with photovoltaics, energy storage, charging, and discharging; is the unit price of the equivalent carbon emission; is the carbon emission intensity factor of the gas turbine; is the carbon emission quota factor per unit of power generation of the gas turbine; is the carbon emission intensity factor of the supplementary firing waste heat boiler; is the carbon emission quota factor per unit of heating power of the supplementary firing waste heat boiler; is the total economic cost of the day-ahead energy-economic optimization scheduling for the integrated energy system coupling relationship model with photovoltaics, energy storage, charging, and discharging; is the fuel input of the supplementary combustion natural gas of the supplementary firing waste heat boiler at time ; is the adjustment cost coefficient per unit of power for the power output adjustment of the gas turbine; is the electric power of the gas turbine at time ; is the electric power of the gas turbine at time under the day-ahead rolling energy-carbon optimization scheduling; is the adjustment cost coefficient per unit of power for the change in the transmission power of the grid connection tie line; is the transmission power of the grid connection tie line for the integrated energy system coupling relationship model with photovoltaics, energy storage, charging, and discharging; is the transmission power of the grid connection tie line for the integrated energy system coupling relationship model with photovoltaics, energy storage, charging, and discharging under the day-ahead rolling energy-carbon optimization scheduling; is the adjustment cost coefficient per unit of power for the heating output adjustment of the supplementary firing waste heat boiler; is the heating power of the supplementary firing waste heat boiler at time ; is the heating power of the supplementary firing waste heat boiler at time under the day-ahead rolling energy-carbon optimization scheduling; is the adjustment cost coefficient per unit of capacity of the electric energy storage device; is the stored electricity of the electric energy storage device at time ; For the stored electricity of the electric energy storage device at time under the intraday rolling energy-carbon optimized scheduling; For the scheduling simulation operation cycle under the intraday rolling energy-carbon optimized scheduling; For the scheduling simulation operation regulation step resolution.

7. The multi-time-scale energy-carbon optimization method for the integrated energy system with photovoltaics, energy storage and charging according to claim 1, characterized in that The setting of the coupling connection conditions between the intraday rolling energy-carbon optimization scheduling strategy and the day-ahead energy-economic optimization scheduling strategy includes: Adjustment amount constraint, re-update and obtain the latest source-load prediction data and input it into the model, and the transformed single-objective intraday rolling energy-carbon optimization scheduling model; The expression of the adjustment amount constraint in the coupling connection conditions is as follows: ； Wherein: is the electric power of the gas turbine at time ; is the electric power of the gas turbine at time under the day-ahead rolling energy-carbon optimized scheduling; is the day-ahead rolling adjustment margin coefficient of the gas turbine; is the rated installed capacity of the gas turbine; is the transmission power of the connecting line at the connection point of the integrated energy system coupling relationship model including photovoltaics, energy storage and charging; is the transmission power of the connecting line at the connection point of the integrated energy system coupling relationship model including photovoltaics, energy storage and charging under the day-ahead rolling energy-carbon optimized scheduling; is the day-ahead rolling adjustment margin coefficient of the transmission power of the connecting line; is the upper limit of the transmission power of the connecting line at the connection point of the integrated energy system coupling relationship model including photovoltaics, energy storage and charging; is the heating power of the supplementary-firing waste heat boiler at time ; is the heating power of the supplementary-firing waste heat boiler at time under the day-ahead rolling energy-carbon optimized scheduling; is the day-ahead rolling adjustment margin coefficient of the supplementary-firing waste heat boiler; is the rated installed capacity of the supplementary-firing waste heat boiler; is the stored electricity of the electric energy storage device at time ; is the stored electricity of the electric energy storage device at time under the day-ahead rolling energy-carbon optimized scheduling; is the day-ahead rolling adjustment margin coefficient of the electric energy storage device; is the rated capacity of the electric energy storage device; The expression of re-updating and obtaining the latest source-load prediction data and inputting it into the model in the coupling connection conditions is as follows: ； Wherein: is the maximum predicted output power of the wind turbine at time ; is the electrical load power demand satisfied by the electro-thermal interconnected integrated energy system model at time ; is the thermal load power demand satisfied by the electro-thermal interconnected integrated energy system model at time ; is the predicted power generation of the photovoltaic array in the integrated photovoltaic energy storage and charging system model at time ; is the predicted charging load power of the charging pile cluster at time ; is to re-update and obtain the latest source-load prediction data, and respectively assign values to the maximum predicted output power of the wind turbine at time ; the electrical load power demand satisfied by the electro-thermal interconnected integrated energy system model at time ; the thermal load power demand satisfied by the electro-thermal interconnected integrated energy system model at time ; the predicted power generation of the photovoltaic array at time ; and the predicted charging load power of the charging pile cluster at time in the first 16 control step resolutions of each rolling optimization scheduling simulation operation cycle; ; is the re-assignment symbol after data update; is the set of scheduling simulation operation cycles for each rolling optimization scheduling; is to re-update and obtain the latest source-load predicted power every 4 hours for the intra-day rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with integrated photovoltaic energy storage and charging; is the scheduling simulation operation cycle under the intra-day rolling energy-carbon optimization scheduling; The expression of the transformed single-objective intraday rolling energy-carbon optimization scheduling model in the coupling connection conditions is as follows: ； Wherein: is the total carbon emission cost of the day-ahead rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with photovoltaics, energy storage and charging; is the total economic cost of the day-ahead rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with photovoltaics, energy storage and charging; is the total cost of the plan adjustment of the day-ahead rolling energy-carbon optimization scheduling of the integrated energy system coupling relationship model with photovoltaics, energy storage and charging; are different weight coefficients corresponding to different single-objective optimization functions.

8. Multi-time scale energy-carbon optimization system for integrated energy system with photovoltaic energy storage and charging integration, characterized in that, Including: Data information acquisition module, which acquires the initial start-up data information of the energy system operation; Photovoltaic-energy storage-charging integrated system model construction module, which establishes a photovoltaic-energy storage-charging integrated system model based on the initial start-up data information, including a photovoltaic power generation model, an electrical energy storage model, a charging pile cluster model, and a photovoltaic-energy storage-charging integrated system energy coupling balance model; Electro-thermal interconnected integrated energy system model construction module, which establishes an electro-thermal interconnected integrated energy system model based on the initial start-up data information, including a gas turbine model, a supplementary combustion waste heat boiler model, a wind power generation model, an electrical energy coupling balance model, and a heat energy coupling balance model; Coupling relationship model acquisition module, which couples and interconnects the photovoltaic-energy storage-charging integrated system model and the electro-thermal interconnected integrated energy system model to form an integrated energy system coupling relationship model with photovoltaics, energy storage, and charging; The day-ahead energy economic optimal dispatch strategy setting module sets the day-ahead energy economic optimal dispatch strategy for the integrated energy system coupling relationship model; The intra-day rolling energy-carbon optimal dispatch strategy setting module sets the intra-day rolling energy-carbon optimal dispatch strategy for the integrated energy system coupling relationship model; The coupling connection condition setting module sets the coupling connection conditions between the intra-day rolling energy-carbon optimal dispatch strategy and the day-ahead energy economic optimal dispatch strategy. After the coupling connection conditions are set, an integrated energy system is formed; The result output module inputs the initial start data information of the energy system operation into the integrated energy system and outputs the energy-carbon optimal dispatch result data information of the integrated energy system through the integrated energy system.

9. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, it implements the multi-time scale energy-carbon optimal method for the integrated energy system with integrated photovoltaics, energy storage, and charging as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium. When the computer program is executed by the processor, it implements the multi-time scale energy-carbon optimal method for the integrated energy system with integrated photovoltaics, energy storage, and charging as described in any one of claims 1-7.

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