Method, system and equipment for optimizing integrated energy system under dual-carbon background

Abstract

The invention discloses a method, a system and equipment for optimizing an integrated energy system under a dual-carbon background, and relates to the technical field of energy scheduling of the integrated energy system. Acquiring operation data of a cogeneration unit, operation data of an absorption refrigerator, operation data of an electric refrigerator or operation data of an electricity storage device; the operation result of the cogeneration unit, the operation result of the absorption refrigerator, the operation result of the electric refrigerator and the operation result of the electricity storage device are obtained; obtaining daily operation cost data; obtaining carbon dioxide emission data; a comprehensive energy system optimization strategy is obtained; obtaining output and energy storage processing data of a cogeneration unit, output and energy storage processing data of an absorption refrigerator, output and energy storage processing data of an electric refrigerator and output and energy storage processing data of an electricity storage device; and obtaining an optimized daily scheduling plan of the integrated energy system. According to the invention, the accuracy of the scheduling plan during load line crossing is improved.

Description

Technical Field

[0001] This invention relates to the field of energy dispatching technology for integrated energy systems, and in particular to an optimization method, system, and equipment for integrated energy systems under a dual-carbon background. Background Technology

[0002] Integrated Energy Systems (IES) achieve cascaded energy utilization through the coupling of various energy forms. The coupling degree between distributed energy and renewable energy will gradually increase, improving system reliability and flexibility while posing new research challenges for the scheduling and optimization of related systems.

[0003] Compared to the optimal power flow problem in a power system, the integrated energy system requires consideration of the differences in response time in daily economic dispatch due to the different physical characteristics of energy sources. In addition, the addition of coupling elements makes the constraints more complex, the optimization space smaller, and the solution more difficult.

[0004] Compared to traditional optimization algorithms, which have higher requirements for the mathematical model and often require classification and transformation of the optimization problem, different algorithms are needed to solve it. For integrated energy systems, the components and equipment are complex, especially with the increasing number of loads and energy storage devices utilizing different energy types in the network. Classifying the system's state variables becomes cumbersome, and it cannot be guaranteed that the optimization algorithm used will be applicable to other networks with different structures. Summary of the Invention

[0005] The purpose of this invention is to provide a method, system, and device for optimizing an integrated energy system under a dual-carbon background, so as to improve the accuracy of scheduling schemes when load exceeds the limit.

[0006] To achieve the above objectives, embodiments of the present invention provide the following solutions:

[0007] A comprehensive energy system optimization method under a dual-carbon background includes:

[0008] Obtain the necessary operational data from both the supply and demand sides of the integrated energy system; specifically, the operational data includes: operating data of combined heat and power units, operating data of absorption chillers, operating data of electric chillers, or operating data of energy storage devices;

[0009] The operating data of the combined heat and power (CHP) unit are calculated using a mathematical model of the CHP unit to obtain the operating results of the CHP unit; the operating data of the absorption chiller are calculated using a mathematical model of the absorption chiller to obtain the operating results of the absorption chiller; the operating data of the electric chiller are calculated using a mathematical model of the electric chiller to obtain the operating results of the electric chiller; and the operating data of the energy storage device are calculated using a mathematical model of the energy storage device to obtain the operating results of the energy storage device.

[0010] The daily operating cost data is obtained by calculating the operating data of the cogeneration unit, the absorption chiller, the electric chiller, or the energy storage device using a daily operating cost target model.

[0011] Carbon dioxide emission data are obtained by calculating the operating data of the combined heat and power unit, the absorption chiller, the electric chiller, or the energy storage device using a carbon dioxide emission target model.

[0012] The multi-objective whale optimization algorithm is used to solve the scheduling model to calculate daily operating cost data and carbon dioxide emission data, thereby obtaining an integrated energy system optimization strategy; and the energy of the energy network is scheduled according to the integrated energy system optimization strategy.

[0013] The multi-objective whale optimization algorithm was used to calculate the operating results of the combined heat and power (CHP) unit, obtaining the CHP unit's output and energy storage processing data; the multi-objective whale optimization algorithm was also used to calculate the operating results of the absorption chiller, obtaining the absorption chiller's output and energy storage processing data; the multi-objective whale optimization algorithm was used to calculate the operating results of the electric chiller, obtaining the electric chiller's output and energy storage processing data; and the multi-objective whale optimization algorithm was used to calculate the operating results of the energy storage device, obtaining the energy storage device's output and energy storage processing data.

[0014] Based on the combined heat and power unit output and energy storage processing data, absorption chiller output and energy storage processing data, electric chiller output and energy storage processing data, energy storage device output and energy storage processing data, and integrated energy system optimization strategy, the integrated energy system optimization daily scheduling plan under the dual-carbon background is obtained.

[0015] Optionally, the mathematical model for a combined heat and power (CHP) unit specifically includes:

[0016]

[0017] in, These represent the input gas power of the gas turbine and the gas internal combustion engine during time period t, respectively. Let be the output electrical power of the gas turbine and the gas internal combustion engine at time t, respectively. Let η be the output thermal power of the gas turbine and the gas internal combustion engine at time t. GT,e η GE,e The power generation efficiency, η, represents the power generation efficiency of the gas turbine and the gas internal combustion engine, respectively. GT,h η GE,h These are the heat production efficiencies of gas turbines and gas internal combustion engines, respectively. Let η be the output thermal power of the waste heat boiler at time t. WHB For heat recovery efficiency; Let t be the input gas power of the gas boiler. Let η be the output thermal power of the gas-fired boiler at time t. GB The heat production efficiency of a gas-fired boiler;

[0018] The mathematical model of the absorption chiller specifically includes:

[0019] in, The input thermal power of the waste heat boiler at time t; η is the AC output cooling power at time t; AC The coefficient of performance (COP) for AC cooling.

[0020] The mathematical model of the electric chiller specifically includes:

[0021] in, Let t be the input electrical power; η is the output cooling power at time t; EC Coefficient of performance (COP) for electric cooling;

[0022] The mathematical model of the energy storage device specifically includes:

[0023] in, This indicates the energy storage capacity of the energy storage device at time t-1. This represents the energy storage capacity of the energy storage device at time t; The charging power of the energy storage device at all times. Let t be the discharge power of the energy storage device; To improve the charging efficiency of energy storage devices, This refers to the discharge efficiency of the energy storage device.

[0024] Optionally, the daily operating cost target model specifically includes:

[0025] F1 = F yw +C G +C GB +C ge -C me ;

[0026] Where F1 is the daily operating cost of the integrated energy system; F ywIndicates IES operation and maintenance costs; C G The cost of purchasing natural gas for gas-fired internal combustion engines and gas turbines; C GB C is the cost of purchasing natural gas for gas-fired boilers; ge C is the cost of purchasing electricity from the grid. gm To generate revenue from selling electricity to the power grid.

[0027] Optionally, the carbon dioxide emission target model specifically includes: F2 = C G-C +C GB-C ;

[0028] Where F2 represents the carbon dioxide emissions of the IES; C G-C Carbon dioxide produced by gas internal combustion engines and gas turbines; C GB-C This refers to the carbon emissions from gas-fired boilers.

[0029] Optionally, the electrical, cooling, and heating constraints of the daily operating cost target model or the carbon dioxide emission target model specifically include:

[0030] Electrical load balance: E load =P PV +P wind +P GT +P GE +E dis -E ch -P EC +P BUY -P SELL ;

[0031] Among them, E load P represents electrical load. PV P represents the photovoltaic power generation capacity. wind P represents the power generation capacity of the wind turbine. GT P represents the power generation capacity of a gas turbine. GE P represents the power generation capacity of a gas-fired internal combustion engine. EC P represents the power consumption of the electric chiller. BUY P represents the electricity purchased by the integrated energy system. SELL This indicates the electricity sales volume of the integrated energy system;

[0032] Heat load balance: H load =H WHB +H GB -H AC ;

[0033] Among them, H load H represents the heat load. WHB H represents the output thermal power of the waste heat boiler. GB H represents the output thermal power of a gas-fired boiler. AC This indicates the heat consumption power of the absorption chiller;

[0034] Cooling load balance: L load =C EC +C AC ;

[0035] Among them, L load For cooling load, C EC C represents the output cooling power of the electric chiller. AC This indicates the output cooling power of the absorption chiller.

[0036] Optionally, the output constraints of each device within the integrated energy system are as follows:

[0037]

[0038] Where N is the set of all devices within the integrated energy system, and P i P represents the output of the i-th type of equipment within the integrated energy system. i,max P represents the upper limit of the output of the i-th type of equipment within the integrated energy system. i,min This is the lower limit of the output of the i-th type of equipment within the integrated energy system.

[0039] Optionally, the multi-objective whale optimization algorithm specifically includes:

[0040]

[0041] in, This represents the optimal strategy for an integrated energy system; This represents the current optimization strategy for the i-th integrated energy system; and Indicates the enclosing step size; where:

[0042] A=2a·rand1-a; C=2rand2;

[0043] Where rand1 and rand2 represent random numbers in the range [0,1]; a represents the convergence factor; t max Indicates the maximum number of iterations;

[0044]

[0045] To achieve the above objectives, embodiments of the present invention also provide the following solutions:

[0046] A comprehensive energy system optimization system under a dual-carbon background, comprising:

[0047] The data acquisition module is used to acquire the operational data required by the supply side and demand side of the integrated energy system; the operational data specifically includes: operating data of cogeneration units, operating data of absorption chillers, operating data of electric chillers, or operating data of energy storage devices;

[0048] The result calculation module, connected to the data acquisition module, is used for:

[0049] The operating data of the combined heat and power (CHP) unit are calculated using a mathematical model of the CHP unit to obtain the operating results of the CHP unit; the operating data of the absorption chiller are calculated using a mathematical model of the absorption chiller to obtain the operating results of the absorption chiller; the operating data of the electric chiller are calculated using a mathematical model of the electric chiller to obtain the operating results of the electric chiller; and the operating data of the energy storage device are calculated using a mathematical model of the energy storage device to obtain the operating results of the energy storage device.

[0050] The daily operating cost data calculation module is connected to the data acquisition module and is used to calculate the daily operating cost data by using the daily operating cost target model on the operating data of the cogeneration unit, the operating data of the absorption chiller, the operating data of the electric chiller or the operating data of the energy storage device.

[0051] A carbon dioxide emission data calculation module, connected to the data acquisition module, is used to calculate carbon dioxide emission data by using a carbon dioxide emission target model on the operating data of the cogeneration unit, the operating data of the absorption chiller, the operating data of the electric chiller, or the operating data of the energy storage device.

[0052] The integrated energy system optimization strategy module is connected to the daily operating cost data calculation module and the carbon dioxide emission data calculation module, respectively. It is used to calculate the daily operating cost data and carbon dioxide emission data by solving the scheduling model using the multi-objective whale optimization algorithm to obtain the integrated energy system optimization strategy; and to schedule the energy of the energy network using the integrated energy system optimization strategy.

[0053] The multi-objective whale optimization module is connected to both the operation result calculation module and the integrated energy system optimization strategy module, and is used for:

[0054] The multi-objective whale optimization algorithm was used to calculate the operating results of the combined heat and power (CHP) unit, obtaining the CHP unit's output and energy storage processing data; the multi-objective whale optimization algorithm was also used to calculate the operating results of the absorption chiller, obtaining the absorption chiller's output and energy storage processing data; the multi-objective whale optimization algorithm was used to calculate the operating results of the electric chiller, obtaining the electric chiller's output and energy storage processing data; and the multi-objective whale optimization algorithm was used to calculate the operating results of the energy storage device, obtaining the energy storage device's output and energy storage processing data.

[0055] Based on the combined heat and power unit output and energy storage processing data, absorption chiller output and energy storage processing data, electric chiller output and energy storage processing data, energy storage device output and energy storage processing data, and integrated energy system optimization strategy, the integrated energy system optimization daily scheduling plan under the dual-carbon background is obtained.

[0056] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the integrated energy system optimization method under a dual-carbon background.

[0057] A non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed, implements the integrated energy system optimization method under a dual-carbon background.

[0058] In this invention embodiment, the integrated energy system optimization method under a dual-carbon background is highly versatile and simple in process. It can solve the problems of poor convergence and difficulty in selecting initial values ​​in traditional optimization algorithms, effectively address the energy allocation problem of integrated energy systems, and provide an energy optimization strategy with the objective functions of minimizing daily operating costs and daily carbon emissions. This strategy enables interconnection and interoperability among various energy sources, promotes optimal energy utilization within the system, and reduces carbon emissions while considering overall costs, thereby improving the system's reliability, economy, and greenness. This invention embodiment achieves a balance between environmental friendliness and economic benefits, and is of great significance for the coordinated operation of integrated energy systems, low-carbon environmental protection, and reliable and economical supply to users. Attached Figure Description

[0059] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0060] Figure 1 A flowchart illustrating the integrated energy system optimization method under a dual-carbon background provided in an embodiment of the present invention;

[0061] Figure 2 A schematic diagram of the structure of the integrated energy system optimization method under a dual-carbon background provided in an embodiment of the present invention;

[0062] Figure 3 A coupled network diagram of an integrated energy system under a dual-carbon background is provided for embodiments of the present invention.

[0063] Figure 4 A flowchart illustrating the solution process for the integrated energy system optimization scheduling model provided in this embodiment of the invention;

[0064] Figure 5 The integrated energy system optimization scheduling strategy provided in the embodiments of the present invention;

[0065] Figure 6 This is a diagram showing the results of optimized power load scheduling provided in an embodiment of the present invention.

[0066] Figure 7 This is a diagram showing the optimized cooling load scheduling results provided in an embodiment of the present invention.

[0067] Figure 8 The diagram shows the results of optimized heat load scheduling provided in an embodiment of the present invention.

[0068] Symbol explanation:

[0069] Data acquisition module-1, operation result calculation module-2, daily operating cost data calculation module-3, carbon dioxide emission data calculation module-4, integrated energy system optimization strategy module-5, multi-objective whale optimization module-6. Detailed Implementation

[0070] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0071] The purpose of this invention is to provide a method, system, and device for optimizing an integrated energy system under a dual-carbon background, in order to solve the problem of low accuracy in existing load overload scheduling schemes.

[0072] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0073] Figure 1 An exemplary process for the aforementioned integrated energy system optimization method under a dual-carbon background is shown. The steps are described in detail below.

[0074] This invention fully considers the coupling relationships among various power-output devices in an integrated energy system, while also taking into account the low-carbon and economical aspects of the operating system. A collaborative scheduling model for the integrated energy system is established, with daily operating cost and carbon dioxide emissions as the optimization objective functions. The output of each device in the integrated energy system for each time period is set as the optimization variable. Using an "electricity-driven heat" approach, the output power of each device in the integrated energy system is calculated according to constraints. With daily operating cost and carbon dioxide emissions as the optimization objective functions, a compromise solution to a set of optimization problems is finally found through a multi-objective whale optimization algorithm. For the demand-side electrical load of the integrated energy system, the output of wind turbines, photovoltaic arrays, gas turbines, and gas-fired internal combustion engines is used to meet the demand, with any shortfall supplemented by energy storage devices and the external power grid. The heat load is provided by waste heat boilers and gas-fired boilers through heat exchangers. The cooling load is provided by absorption chillers and electric chillers.

[0075] Step S1: Obtain the necessary data for operation of the integrated energy system supply side and integrated energy system demand side; the necessary data for operation specifically includes: operating data of cogeneration units, operating data of absorption chillers, operating data of electric chillers or operating data of energy storage devices;

[0076] Step S2: Calculate the operating data of the combined heat and power (CHP) unit using a mathematical model to obtain the operating results of the CHP unit; calculate the operating data of the absorption chiller using a mathematical model to obtain the operating results of the absorption chiller; calculate the operating data of the electric chiller using a mathematical model to obtain the operating results of the electric chiller; calculate the operating data of the energy storage device using a mathematical model to obtain the operating results of the energy storage device.

[0077] In one example, a user load and energy coupling network model is established. The required data for the operation of the integrated energy system's supply and demand sides are input to determine the relationship between energy output demand and energy input in each region. Figure 3 As shown.

[0078] The supply side of an integrated energy system includes: wind turbines, photovoltaic arrays, power grid, and natural gas grid;

[0079] Energy conversion equipment includes: gas turbines, gas internal combustion engines, gas boilers, waste heat boilers, electric chillers, absorption chillers, and heat exchangers;

[0080] Energy storage equipment includes: energy storage devices;

[0081] The demand side of a comprehensive energy system includes: electrical load, cooling load, and heating load.

[0082] Input parameters for the operation of wind power, photovoltaic systems, gas turbines, and gas internal combustion engines on the supply side of the integrated energy system; various load data on the demand side of the integrated energy system; and operating costs of the integrated energy system. Based on the different equipment components in each region of the system, determine the energy conversion methods and the relationship between input and output in each region.

[0083] The mathematical model for the combined heat and power unit specifically includes:

[0084]

[0085] in, These represent the input gas power of the gas turbine and the gas internal combustion engine during time period t, respectively. Let be the output electrical power of the gas turbine and the gas internal combustion engine at time t, respectively. Let η be the output thermal power of the gas turbine and the gas internal combustion engine at time t. GT,e η GE,e The power generation efficiency, η, represents the power generation efficiency of the gas turbine and the gas internal combustion engine, respectively. GT,h η GE,h These are the heat production efficiencies of gas turbines and gas internal combustion engines, respectively. Let η be the output thermal power of the waste heat boiler at time t. WHB For heat recovery efficiency; Let t be the input gas power of the gas boiler. Let η be the output thermal power of the gas-fired boiler at time t. GB The heat production efficiency of a gas-fired boiler;

[0086] The mathematical model of the absorption chiller specifically includes:

[0087] in, The input thermal power of the waste heat boiler at time t; η is the AC output cooling power at time t; AC The coefficient of performance (COP) for AC cooling.

[0088] The mathematical model of the electric chiller specifically includes:

[0089] in, Let t be the input electrical power; η is the output cooling power at time t; EC Coefficient of performance (COP) for electric cooling;

[0090] The mathematical model of the energy storage device specifically includes:

[0091] in, This indicates the energy storage capacity of the energy storage device at time t-1. This represents the energy storage capacity of the energy storage device at time t; The charging power of the energy storage device at time t Let t be the discharge power of the energy storage device; To improve the charging efficiency of energy storage devices, This refers to the discharge efficiency of the energy storage device.

[0092] In one example, a combined heat and power (CHP) unit consists of a gas turbine, a gas internal combustion engine, and a waste heat boiler.

[0093] Step S3: Calculate the daily operating cost data by using the daily operating cost target model on the operating data of the cogeneration unit, the absorption chiller, the electric chiller, or the energy storage device.

[0094] The daily operating cost target model specifically includes: F1 = F yw +C G +C GB +C ge -C me ;

[0095] Where F1 represents the daily operating cost of the Integrated Energy System (IES); F yw Indicates IES operation and maintenance costs; C G The cost of purchasing natural gas for gas-fired internal combustion engines and gas turbines; C GB C is the cost of purchasing natural gas for gas-fired boilers; ge The cost of purchasing electricity from the grid, C gm To generate revenue from selling electricity to the power grid.

[0096] Step S4: Calculate the carbon dioxide emission data using the carbon dioxide emission target model based on the operating data of the combined heat and power unit, the operating data of the absorption chiller, the operating data of the electric chiller, or the operating data of the energy storage device.

[0097] The carbon dioxide emission target model specifically includes: F2 = C G-C +C GB-C ;

[0098] Where F2 represents the carbon dioxide emissions of the IES; C G-C Carbon dioxide produced by gas internal combustion engines and gas turbines; C GB-C This refers to the carbon emissions from gas-fired boilers.

[0099] The specific electrical, cooling, and heating constraints of the daily operating cost target model or the carbon dioxide emission target model include:

[0100] Electrical load balance: E load =P PV+P wind +P GT +P GE +E dis -E ch -P EC +P BUY -P SELL ;

[0101] Among them, E load P represents electrical load. PV P represents the photovoltaic power generation capacity. wind P represents the power generation capacity of the wind turbine. GT P represents the power generation capacity of a gas turbine. GE P represents the power generation capacity of a gas-fired internal combustion engine. EC P represents the power consumption of the electric chiller. BUY P represents the electricity purchased by the integrated energy system. SELL This indicates the electricity sales volume of the integrated energy system;

[0102] Heat load balance: H load =H WHB +H GB -H AC ;

[0103] Among them, H load H represents the heat load. WHB H represents the output thermal power of the waste heat boiler. GB H represents the output thermal power of a gas-fired boiler. AC This indicates the heat consumption power of the absorption chiller;

[0104] Cooling load balance: L load =C EC +C AC ;

[0105] Among them, L load For cooling load, C EC C represents the output cooling power of the electric chiller. AC This indicates the output cooling power of the absorption chiller.

[0106] The output constraints of each device within the integrated energy system are as follows:

[0107] Where N is the set of all devices within the integrated energy system, and P i P represents the output of the i-th type of equipment within the integrated energy system. i,max P represents the upper limit of the output of the i-th type of equipment within the integrated energy system. i,min This is the lower limit of the output of the i-th type of equipment within the integrated energy system.

[0108] In one example, constraints are set: a multi-objective optimization problem is to find the optimal values ​​of multiple objective functions within a given region. The constraints are defined within the given region. See [link to relevant documentation]. Figure 5 .

[0109] Step S5: The multi-objective whale optimization algorithm is used to solve the scheduling model to calculate the daily operating cost data and carbon dioxide emission data, thereby obtaining the integrated energy system optimization strategy; and the energy of the energy network is scheduled according to the integrated energy system optimization strategy.

[0110] The multi-objective whale optimization algorithm specifically includes:

[0111] in, This represents the optimal strategy for an integrated energy system; This represents the current optimization strategy for the i-th integrated energy system; and Indicates the bounding step size; where: A = 2a·rand1 - a; C = 2rand2;

[0112] Where rand1 and rand2 represent random numbers in the range [0,1]; a represents the convergence factor; t max Indicates the maximum number of iterations;

[0113]

[0114] In one example, the multi-objective whale optimization algorithm is used to solve the scheduling model, obtain the optimization strategy of the integrated energy system, and use this strategy to schedule the energy of the energy network. According to the multi-objective whale optimization algorithm, under the premise of meeting the minimum cost and minimum carbon emissions, the optimal allocation of different forms of energy and the unit output scheme are achieved; the optimal charging and discharging strategy of the energy storage system is obtained; and the energy storage and energy supply of the integrated energy system are coordinated.

[0115] In the whale optimization algorithm, whale predation behavior can be described in two ways: by introducing the occurrence probability p to implement a shrinking encirclement mechanism and a spiral position update for the whale.

[0116] a) Shrinking encirclement mechanism: This is achieved by continuously encircling the convergence factor value in the prey;

[0117] b) Spiral position update: First, calculate the distance between the current individual and the optimal solution position, and then move closer to the optimal solution position in a spiral manner.

[0118]

[0119] In the search for food, when At this time, the whale will move away from the reference target to search for a better prey. The mathematical model is shown in the following formula:

[0120]

[0121]

[0122] This represents a random solution.

[0123] Based on the results of the multi-objective whale optimization algorithm, the output and energy storage capacity of each device in the integrated energy system are obtained. For example... Figure 6 , Figure 7 and Figure 8 .

[0124] Please see Figure 4 The main steps of the improved multi-objective whale optimization algorithm are as follows:

[0125] (1) Set control parameters such as the number of whales, the maximum number of iterations, the search range, and the parameters of the external population;

[0126] (2) Initialization of the whale population. Individual whales are then generated and their compliance with electrical, cold, and heat constraints is checked until a sufficient number of qualified individuals are generated.

[0127] (3) Perform non-dominated sorting and crowding calculation on the initial population, and randomly select prey positions from the first Pareto non-dominant front to guide the direction of population position movement.

[0128] (4) Update the position of each individual in the population using the above formula based on the values ​​of |A| and p and the judgment conditions;

[0129] (5) Random dimension variation is performed on the whale population to update the whale position, and non-dominated sorting and crowding calculation are performed on the population. An elite strategy is used to select whale populations to enter the next generation.

[0130] (6) Determine whether the maximum number of iterations has been reached. If yes, output the result and end the process. Otherwise, repeat steps (3) and (4).

[0131] Step S6: Calculate the operating results of the cogeneration unit using the multi-objective whale optimization algorithm to obtain the cogeneration unit's output and energy storage processing data; calculate the operating results of the absorption chiller using the multi-objective whale optimization algorithm to obtain the absorption chiller's output and energy storage processing data; calculate the operating results of the electric chiller using the multi-objective whale optimization algorithm to obtain the electric chiller's output and energy storage processing data; calculate the operating results of the energy storage device using the multi-objective whale optimization algorithm to obtain the energy storage device's output and energy storage processing data.

[0132] Step S7: Based on the output and energy storage processing data of the cogeneration unit, the output and energy storage processing data of the absorption chiller, the output and energy storage processing data of the electric chiller, the output and energy storage processing data of the energy storage device, and the integrated energy system optimization strategy, the daily scheduling plan for the integrated energy system under the dual-carbon background is obtained, as shown in Tables 1 and 2 below.

[0133] Table 1

[0134]

[0135]

[0136]

[0137] Table 2

[0138]

[0139]

[0140] In summary, the integrated energy system optimization method under a dual-carbon background presented in this invention is highly versatile and simple in process. It can solve problems such as poor convergence and difficulty in selecting initial values ​​in traditional optimization algorithms, effectively addressing the energy allocation problem in integrated energy systems. Furthermore, it provides an energy optimization strategy with the objective functions of minimizing daily operating costs and daily carbon emissions, enabling interconnection and interoperability among various energy sources, promoting optimal energy utilization within the system, and reducing carbon emissions while considering overall costs. This improves the system's reliability, economy, and greenness. This invention achieves a balance between environmental friendliness and economic benefits, and is of great significance for the coordinated operation of integrated energy systems, low-carbon environmental protection, and reliable economic supply to users.

[0141] To achieve the above objectives, embodiments of the present invention also provide the following solutions:

[0142] Please see Figure 2 A comprehensive energy system optimization system under a dual-carbon background, comprising:

[0143] The data acquisition module 1 is used to acquire the operational data required by the supply side and demand side of the integrated energy system; the operational data specifically includes: operating data of cogeneration units, operating data of absorption chillers, operating data of electric chillers, or operating data of energy storage devices;

[0144] The result calculation module 2 is connected to the data acquisition module 1, and the result calculation module 2 is used for:

[0145] The operating data of the combined heat and power (CHP) unit are calculated using a mathematical model of the CHP unit to obtain the operating results of the CHP unit; the operating data of the absorption chiller are calculated using a mathematical model of the absorption chiller to obtain the operating results of the absorption chiller; the operating data of the electric chiller are calculated using a mathematical model of the electric chiller to obtain the operating results of the electric chiller; and the operating data of the energy storage device are calculated using a mathematical model of the energy storage device to obtain the operating results of the energy storage device.

[0146] The daily operating cost data calculation module 3 is connected to the data acquisition module 1. The daily operating cost data calculation module 3 is used to calculate the daily operating cost data by using the daily operating cost target model on the operating data of the cogeneration unit, the operating data of the absorption chiller, the operating data of the electric chiller or the operating data of the energy storage device.

[0147] The carbon dioxide emission data calculation module 4 is connected to the data acquisition module 1. The carbon dioxide emission data calculation module 4 is used to calculate the carbon dioxide emission data by using the carbon dioxide emission target model on the operating data of the cogeneration unit, the operating data of the absorption chiller, the operating data of the electric chiller or the operating data of the energy storage device.

[0148] The integrated energy system optimization strategy module 5 is connected to the daily operating cost data calculation module 3 and the carbon dioxide emission data calculation module 4, respectively. The integrated energy system optimization strategy module 5 is used to calculate the daily operating cost data and carbon dioxide emission data by using the multi-objective whale optimization algorithm to solve the scheduling model, so as to obtain the integrated energy system optimization strategy; and to schedule the energy of the energy network using the integrated energy system optimization strategy.

[0149] The multi-objective whale optimization module 6 is connected to both the operation result calculation module 2 and the integrated energy system optimization strategy module 5. The multi-objective whale optimization module 6 is used for:

[0150] The multi-objective whale optimization algorithm was used to calculate the operating results of the combined heat and power (CHP) unit, obtaining the CHP unit's output and energy storage processing data; the multi-objective whale optimization algorithm was also used to calculate the operating results of the absorption chiller, obtaining the absorption chiller's output and energy storage processing data; the multi-objective whale optimization algorithm was used to calculate the operating results of the electric chiller, obtaining the electric chiller's output and energy storage processing data; and the multi-objective whale optimization algorithm was used to calculate the operating results of the energy storage device, obtaining the energy storage device's output and energy storage processing data.

[0151] Based on the combined heat and power unit output and energy storage processing data, absorption chiller output and energy storage processing data, electric chiller output and energy storage processing data, energy storage device output and energy storage processing data, and integrated energy system optimization strategy, the integrated energy system optimization daily scheduling plan under the dual-carbon background is obtained.

[0152] In one example, an integrated energy system under a dual-carbon background includes wind turbines, photovoltaic arrays, gas-fired internal combustion engine units, gas turbine units, gas boilers, a waste heat recovery system, battery banks, a refrigeration system, heat exchanger units, and an optimized dispatching system. The wind turbines and photovoltaic arrays provide renewable energy output for the integrated energy system, and the generated electricity is fed into the power grid, fully utilizing the park's clean energy resources. The gas-fired internal combustion engine units, gas turbine units, and gas boilers are the power generation and heating systems of the integrated energy system. The system heats by purchasing natural gas, which is more economical and environmentally friendly than electric heating, while also avoiding resource waste. A waste heat recovery system is installed to recover the waste heat remaining from thermal power generation, and uses absorption refrigeration and heat exchangers to achieve cooling and heating for the system respectively. The battery banks serve as a backup power source for the integrated energy system, contributing power to the system at any time while implementing optimized dispatching, considering the system's economic efficiency and low-carbon nature. The refrigeration system is the source of cooling load for the integrated energy system, using electricity purchased from the grid and converted through the refrigeration system to achieve cooling. The optimized scheduling system is a comprehensive energy system optimization system under a dual-carbon background. First, it inputs data on power, cooling and heating loads, new energy output, gas turbine and other operating system data. Then, it uses a multi-objective whale optimization algorithm to solve for the optimal operating data. Combined with the power generation data of photovoltaic arrays and wind turbines, it determines the amount of electricity and gas to be purchased, thereby achieving an operating mode that balances low carbon emissions and economic efficiency.

[0153] Furthermore, the present invention also provides an electronic device, which may include: a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other via the communication bus. The processor can call a computer program stored in the memory to execute the aforementioned integrated energy system optimization method under a dual-carbon background.

[0154] Furthermore, when the computer program in the aforementioned memory is implemented as a software functional unit and sold or used as an independent product, it 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 the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory, random access memory, magnetic disks, or optical disks.

[0155] Furthermore, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed, implements the comprehensive energy system optimization method under a dual-carbon background.

[0156] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0157] This document uses specific examples to illustrate the principles and implementation methods of the embodiments of the present invention. The descriptions of the embodiments above are only for the purpose of helping to understand the methods and core ideas of the embodiments of the present invention. At the same time, for those skilled in the art, there will be changes in specific implementation methods and application scope based on the ideas of the embodiments of the present invention. In summary, the content of this specification should not be construed as a limitation on the embodiments of the present invention.

Claims

1. A method for optimizing a comprehensive energy system under a dual-carbon background, characterized in that, include: To obtain the necessary data for the operation of the integrated energy system on both the supply and demand sides; The specific data required for operation includes: operating data of cogeneration units, operating data of absorption chillers, operating data of electric chillers, or operating data of energy storage devices. The operating data of the combined heat and power (CHP) unit are calculated using a mathematical model of the CHP unit to obtain the operating results of the CHP unit; the operating data of the absorption chiller are calculated using a mathematical model of the absorption chiller to obtain the operating results of the absorption chiller; the operating data of the electric chiller are calculated using a mathematical model of the electric chiller to obtain the operating results of the electric chiller; and the operating data of the energy storage device are calculated using a mathematical model of the energy storage device to obtain the operating results of the energy storage device. The daily operating cost data is obtained by calculating the operating data of the cogeneration unit, the absorption chiller, the electric chiller, or the energy storage device using a daily operating cost target model. Carbon dioxide emission data are obtained by calculating the operating data of the combined heat and power unit, the absorption chiller, the electric chiller, or the energy storage device using a carbon dioxide emission target model. The multi-objective whale optimization algorithm is used to solve the scheduling model to calculate daily operating cost data and carbon dioxide emission data, thereby obtaining an integrated energy system optimization strategy; and the energy of the energy network is scheduled according to the integrated energy system optimization strategy. The multi-objective whale optimization algorithm was used to calculate the operating results of the combined heat and power (CHP) unit, obtaining the CHP unit's output and energy storage processing data; the multi-objective whale optimization algorithm was also used to calculate the operating results of the absorption chiller, obtaining the absorption chiller's output and energy storage processing data; the multi-objective whale optimization algorithm was used to calculate the operating results of the electric chiller, obtaining the electric chiller's output and energy storage processing data; and the multi-objective whale optimization algorithm was used to calculate the operating results of the energy storage device, obtaining the energy storage device's output and energy storage processing data. Based on the combined heat and power unit output and energy storage processing data, absorption chiller output and energy storage processing data, electric chiller output and energy storage processing data, energy storage device output and energy storage processing data, and integrated energy system optimization strategy, the integrated energy system optimization daily scheduling plan under the dual-carbon background is obtained.

2. The method for optimizing a comprehensive energy system under a dual-carbon background according to claim 1, characterized in that, The mathematical model for the combined heat and power unit specifically includes: in, P represents the input gas power of the gas turbine and the gas internal combustion engine during time period t. t GT P t GE These represent the output electrical power of the gas turbine and the gas internal combustion engine at time t, respectively. Let η be the output thermal power of the gas turbine and the gas internal combustion engine at time t. GT,e η GE,e The power generation efficiency, η, represents the power generation efficiency of the gas turbine and the gas internal combustion engine, respectively. GT,h η GE,h These are the heat production efficiencies of gas turbines and gas internal combustion engines, respectively. Let η be the output thermal power of the waste heat boiler at time t. WHB For heat recovery efficiency; P t GB Let t be the input gas power of the gas boiler. Let η be the output thermal power of the gas-fired boiler at time t. GB The heat production efficiency of a gas-fired boiler; The mathematical model of the absorption chiller specifically includes: in, The input thermal power of the waste heat boiler at time t; η is the AC output cooling power at time t; AC The coefficient of performance (COP) for AC cooling. The mathematical model of the electric chiller specifically includes: Among them, P t EC Let t be the input electrical power; η is the output cooling power at time t; EC Coefficient of performance (COP) for electric cooling; The mathematical model of the energy storage device specifically includes: in, This indicates the energy storage capacity of the energy storage device at time t-1. This represents the energy storage capacity of the energy storage device at time t; The charging power of the energy storage device at time t Let t be the discharge power of the energy storage device; To improve the charging efficiency of energy storage devices, This refers to the discharge efficiency of the energy storage device.

3. The method for optimizing a comprehensive energy system under a dual-carbon background according to claim 1, characterized in that, The daily operating cost target model specifically includes: F1=F yw +C G +C GB +C ge -C me ; Where F1 is the daily operating cost of the integrated energy system; F yw Indicates IES operation and maintenance costs; C G The cost of purchasing natural gas for gas-fired internal combustion engines and gas turbines; C GB C is the cost of purchasing natural gas for gas-fired boilers; ge C is the cost of purchasing electricity from the grid. gm To generate revenue from selling electricity to the power grid.

4. The method for optimizing a comprehensive energy system under a dual-carbon background according to claim 3, characterized in that, The carbon dioxide emission target model specifically includes: F2 = C G-C +C GB-C ; Where F2 represents the carbon dioxide emissions of the IES; C G-C Carbon dioxide produced by gas internal combustion engines and gas turbines; C GB-C This refers to the carbon emissions from gas-fired boilers.

5. The method for optimizing a comprehensive energy system under a dual-carbon background according to claim 4, characterized in that, The specific electrical, cooling, and heating constraints of the daily operating cost target model or the carbon dioxide emission target model include: Electrical load balance: E load =P PV +P wind +P GT +P GE +E dis -E ch -P EC +P BUY -P SELL ; Among them, E load P represents electrical load. PV P represents the photovoltaic power generation capacity. wind P represents the power generation capacity of the wind turbine. GT P represents the power generation capacity of a gas turbine. GE P represents the power generation capacity of a gas-fired internal combustion engine. EC P represents the power consumption of the electric chiller. BUY P represents the electricity purchased by the integrated energy system. SELL This indicates the electricity sales volume of the integrated energy system; Heat load balance: H load =H WHB +H GB -H AC ; Among them, H load H represents the heat load. WHB H represents the output thermal power of the waste heat boiler. GB H represents the output thermal power of a gas-fired boiler. AC This indicates the heat consumption power of the absorption chiller; Cooling load balance: L load =C EC +C AC ; Among them, L load For cooling load, C EC C represents the output cooling power of the electric chiller. AC This indicates the output cooling power of the absorption chiller.

6. The method for optimizing a comprehensive energy system under a dual-carbon background according to claim 5, characterized in that, The output constraints of each device within the integrated energy system are as follows: Where N is the set of all devices within the integrated energy system, and P i P represents the output of the i-th type of equipment within the integrated energy system. i,max P represents the upper limit of the output of the i-th type of equipment within the integrated energy system. i,min This is the lower limit of the output of the i-th type of equipment within the integrated energy system.

7. The method for optimizing a comprehensive energy system under a dual-carbon background according to claim 1, characterized in that, The multi-objective whale optimization algorithm specifically includes: in, This represents the optimal strategy for an integrated energy system; This represents the current optimization strategy for the i-th integrated energy system; and Indicates the enclosing step size; where: A=2a·rand1-a; C=2rand2; Where rand1 and rand2 represent random numbers in the range [0,1]; a represents the convergence factor; t max Indicates the maximum number of iterations; 8. A comprehensive energy system optimization system under a dual-carbon background, characterized in that, include: The data acquisition module is used to acquire the operational data required by the supply side and demand side of the integrated energy system. The specific data required for operation includes: operating data of cogeneration units, operating data of absorption chillers, operating data of electric chillers, or operating data of energy storage devices. The result calculation module, connected to the data acquisition module, is used for: The operating data of the combined heat and power (CHP) unit are calculated using a mathematical model of the CHP unit to obtain the operating results of the CHP unit; the operating data of the absorption chiller are calculated using a mathematical model of the absorption chiller to obtain the operating results of the absorption chiller; the operating data of the electric chiller are calculated using a mathematical model of the electric chiller to obtain the operating results of the electric chiller; and the operating data of the energy storage device are calculated using a mathematical model of the energy storage device to obtain the operating results of the energy storage device. The daily operating cost data calculation module is connected to the data acquisition module and is used to calculate the daily operating cost data by using the daily operating cost target model on the operating data of the cogeneration unit, the operating data of the absorption chiller, the operating data of the electric chiller or the operating data of the energy storage device. A carbon dioxide emission data calculation module, connected to the data acquisition module, is used to calculate carbon dioxide emission data by using a carbon dioxide emission target model on the operating data of the cogeneration unit, the operating data of the absorption chiller, the operating data of the electric chiller, or the operating data of the energy storage device. The integrated energy system optimization strategy module is connected to the daily operating cost data calculation module and the carbon dioxide emission data calculation module, respectively. It is used to calculate the daily operating cost data and carbon dioxide emission data by solving the scheduling model using the multi-objective whale optimization algorithm to obtain the integrated energy system optimization strategy; and to schedule the energy of the energy network using the integrated energy system optimization strategy. The multi-objective whale optimization module is connected to both the operation result calculation module and the integrated energy system optimization strategy module, and is used for: The multi-objective whale optimization algorithm was used to calculate the operating results of the combined heat and power (CHP) unit, obtaining the CHP unit's output and energy storage processing data; the multi-objective whale optimization algorithm was also used to calculate the operating results of the absorption chiller, obtaining the absorption chiller's output and energy storage processing data; the multi-objective whale optimization algorithm was used to calculate the operating results of the electric chiller, obtaining the electric chiller's output and energy storage processing data; and the multi-objective whale optimization algorithm was used to calculate the operating results of the energy storage device, obtaining the energy storage device's output and energy storage processing data. Based on the combined heat and power unit output and energy storage processing data, absorption chiller output and energy storage processing data, electric chiller output and energy storage processing data, energy storage device output and energy storage processing data, and integrated energy system optimization strategy, the integrated energy system optimization daily scheduling plan under the dual-carbon background is obtained.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the integrated energy system optimization method under a dual-carbon background as described in claims 1-7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements the integrated energy system optimization method under a dual-carbon background as described in claims 1-7.

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