Comprehensive energy system operation optimization method and related equipment

Abstract

The invention discloses an integrated energy system operation optimization method and related equipment, relates to the technical field of energy system operation optimization, and mainly aims to solve the problem of unbalanced operation of an integrated energy system caused by traditional large-scale wind and light energy access. The method comprises the following steps: determining wind and light combined output data of a target area; calculating the load adjusting capability of the target area; and optimizing the integrated energy system based on the wind and light combined output data and the load regulation capability of the target area. The method is used for the operation optimization process of the integrated energy system.

Description

Technical Field

[0001] The present invention relates to the technical field of energy system operation optimization, and in particular to an integrated energy system operation optimization method and related equipment. Background Art

[0002] The integrated energy system organically integrates multiple energy sources such as wind power, photovoltaic power generation and traditional fossil energy. Through unified coordinated scheduling, it provides multiple energy sources for the load side while ensuring stable energy supply and large-scale consumption of new energy, thereby effectively reducing the emission of greenhouse gases and air pollutants. Focusing on the development of integrated energy systems has become an important starting point for the green transformation of today's energy industry. However, in actual operation, since wind and solar power generation are directly affected by the natural environment, the output shows a certain degree of randomness and volatility, which makes the system's prediction of power generation in the day-ahead scheduling plan and the actual power generation have a certain error, resulting in the traditional "source follows load" integrated energy system scheduling method has a certain risk of economic losses or supply and demand imbalance. Summary of the invention

[0003] In view of the above problems, the present invention provides an integrated energy system operation optimization method and related equipment, the main purpose of which is to solve the problem of imbalance in the operation of the integrated energy system caused by traditional large-scale wind and solar energy access.

[0004] In order to solve at least one of the above technical problems, in a first aspect, the present invention provides a method for optimizing the operation of an integrated energy system, the method comprising: Determine the wind and solar combined output data for the target area; Calculate the load regulation capacity of the target area; The integrated energy system is optimized based on the wind and solar combined output data and load regulation capability of the target area.

[0005] Optionally, the determining of the wind and solar power combined output data of the target area includes: Determine the marginal distribution function of wind and solar power generation based on historical data of wind and solar power generation in the target area; Determining unknown parameters of a standby function based on the marginal distribution function, wherein the standby function includes a normal-Copula function, a t-Copula function, a Calyton-Copula function, a Frank-Copula function, and a Gumbel-Copula function; Determine the rank correlation coefficient of the function to be used using Kendall and Spearman as evaluation indicators; Determining the optimal function among the standby functions based on the evaluation index calculation result, wherein the evaluation index calculation result is used to feedback the adaptability of the standby function to the target area; The wind and solar combined output data of the target area are determined by the optimal function in combination with the risk assessment factor.

[0006] Optionally, the calculating the load regulation capacity of the target area includes: An electrical parameter model and a thermal parameter model of the target area are constructed, wherein the electrical parameter model and the thermal parameter model are used to determine an air conditioning load regulation capability, and the air conditioning load regulation capability reflects the load regulation capability of the target area.

[0007] Optionally, constructing an electrical parameter model and a thermal parameter model of the target area includes: Determine the power consumption of the air conditioner based on the following formula:

[0008] The air conditioning power supply is determined based on the following formula:

[0009] Determine the room temperature where the air conditioner is located based on the following formula:

[0010] Among them, P w is the power consumption of the air conditioner, Q(t) is the power supply of the air conditioner at time t; Tr(t) is the indoor temperature of the air conditioner at time t, ℃; τ is the simulation setting time step; η is the energy supply efficiency of the variable frequency air conditioner; a, b, c, d are the simulation parameters of the variable frequency air conditioner energy supply; T ext (t) is the outdoor temperature at time t, °C; T set (t) is the set temperature of the air conditioner at time t, ℃; H is the thermal conductivity between the room where the air conditioner is located and the outdoors; E is the equivalent thermal mass of the room where the air conditioner is located.

[0011] Optionally, the optimizing the integrated energy system based on the wind and solar power combined output data and load regulation capability of the target area includes: Construct optimization models for the day-ahead phase and intraday phase; The integrated energy system is optimized based on the optimization model of the day-ahead stage and the optimization model of the intraday stage.

[0012] Optionally, constructing the optimization model for the day-ahead phase and the optimization model for the intraday phase includes: The optimization model of the day-ahead stage is constructed based on the following formula, wherein the objective function of the optimization model of the day-ahead stage is to minimize the global operating cost, maximize the consumption of new energy, and minimize the carbon emissions, and the constraints are the equipment output constraint and the supply-demand balance constraint:

[0013]

[0014]

[0015]

[0016] in, f 1max is the maximum value of the new energy consumption rate of the model, f 2min Minimum system operating cost, f 3min is the minimum carbon emission value, where P ne and P ne，max They are the new energy consumption and the maximum new energy consumption respectively; C C，i , C P，i and C CO2，i Respectively i The purchase price of the primary energy i The operating cost per unit energy output of the energy supply equipment and the i CO2 emissions from each primary energy source; Q i and P i Respectively i The consumption of primary energy i The energy output of a power supply device is represented by I, where I is the type of the power supply device.

[0017] Optionally, constructing the optimization model for the day-ahead phase and the optimization model for the intraday phase includes: The optimization model for the intraday stage is constructed based on the following formula, wherein the objective function of the optimization model for the intraday stage is to minimize the adjustment cost and the constraint condition is the adjustable power constraint:

[0018]

[0019] Among them, the optimization model of the intraday optimization stage f Depend on f 4 and f 5, among which, f 4 is the regulation cost of the storage device, Δ E d ( t ) and Δ E c ( t ) are respectively t The difference between the discharge and charge of the power storage device at any moment;R ( t ) is a parameter of 0 or 1. When the energy storage device is in the charging state, R ( t )=0, otherwise, R ( t )=1; f 5 is the response compensation cost of air conditioning load; C oc,1 Unit price for response compensation costs; The wind / solar output error of the optimization model of the day-ahead stage is corrected based on the optimization model of the intra-day stage.

[0020] In a second aspect, an embodiment of the present invention further provides a comprehensive energy system operation optimization device, comprising: A determination unit, used to determine wind and solar power combined output data of a target area; A calculation unit, used for calculating the load regulation capacity of the target area; The optimization unit is used to optimize the integrated energy system based on the wind and solar combined output data and load regulation capability of the target area.

[0021] In order to achieve the above-mentioned purpose, according to the third aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the above-mentioned program is executed by a processor, the steps of the above-mentioned integrated energy system operation optimization method are implemented.

[0022] In order to achieve the above-mentioned purpose, according to the fourth aspect of the present invention, there is provided an electronic device, comprising at least one processor and at least one memory connected to the processor; wherein the above-mentioned processor is used to call the program instructions in the above-mentioned memory to execute the steps of the above-mentioned integrated energy system operation optimization method.

[0023] Through the above technical scheme, the integrated energy system operation optimization method and related equipment provided by the present invention can solve the problem of imbalance in the operation of the integrated energy system caused by the access of traditional large-scale wind and solar energy. The present invention determines the wind and solar joint output data of the target area; calculates the load regulation capacity of the target area; and optimizes the integrated energy system based on the wind and solar joint output data and load regulation capacity of the target area. In the above scheme, the wind and solar joint output is effectively simulated, and the wind and solar output strategies under low default risk conditions are formulated. The rapid response characteristics of air conditioners and energy storage components are fully utilized to effectively compensate for the new energy output errors in the day-ahead operation strategy, and finally generate an integrated energy system operation plan under the optimal conditions of economy, low carbon and safety.

[0024] Correspondingly, the integrated energy system operation optimization device, equipment and computer-readable storage medium provided by the embodiments of the present invention also have the above-mentioned technical effects.

[0025] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings: Figure 1 A schematic diagram of a flow chart of a comprehensive energy system operation optimization method provided by an embodiment of the present invention is shown; Figure 2 A complete schematic diagram of a comprehensive energy system operation optimization method provided by an embodiment of the present invention is shown; Figure 3 A schematic block diagram showing the composition of a comprehensive energy system operation optimization device provided by an embodiment of the present invention is shown; Figure 4 A schematic block diagram of the composition of an integrated energy system operation optimization electronic device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0027] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present invention can be combined with each other without conflict.

[0028] The following detailed description is an exemplary description, which is intended to provide further detailed description of the present invention. Unless otherwise specified, all technical terms used in the present invention have the same meaning as those generally understood by those skilled in the art to which the present invention belongs. The terms used in the present invention are only for describing specific embodiments, and are not intended to limit the exemplary embodiments according to the present invention.

[0029] In order to solve the problem that the traditional large-scale wind and solar energy access leads to the imbalance of the operation of the integrated energy system, the embodiment of the present invention provides an integrated energy system operation optimization method, such as Figure 1-Figure 2 As shown, the method includes: S101, determining wind and solar power combined output data for a target area; The above-mentioned step S101 also includes S1011: determining the marginal distribution function of wind and photovoltaic power generation based on the historical data of wind and photovoltaic power generation in the target area; determining the unknown parameters of the standby function based on the marginal distribution function, wherein the standby function includes a normal-Copula function, a t-Copula function, a Calyton-Copula function, a Frank-Copula function and a Gumbel-Copula function; determining the rank correlation coefficient of the standby function using Kendall and Spearman as evaluation indicators; determining the optimal function among the standby functions based on the calculation results of the evaluation indicators, wherein the calculation results of the evaluation indicators are used to feedback the fitness of the standby function and the target area; and determining the wind and photovoltaic combined output data of the target area through the optimal function in combination with the risk assessment factor.

[0030] Specifically, firstly, the marginal distribution functions of wind and photovoltaic power generation in the study area are collected and integrated; secondly, on the basis of analyzing and calculating the above marginal distribution functions, the unknown parameter values ​​existing in the normal-Copula, t-Copula and three Archimedean Copula functions (including Calyton-Copula, Frank-Copula and Gumbel-Copula) are obtained; then, by introducing Kendall and Spearman as evaluation indicators, the rank correlation coefficients of the above five Copula functions are calculated; finally, by comparing and analyzing the calculation results of the evaluation indicators, the Copula function that best describes the study area in this paper, namely the above optimal function, is selected, and combined with the risk assessment factor to realize the deterministic simulation of the combined output of wind and photovoltaic.

[0031] Based on the above scheme, the Copula function is innovatively used to characterize the combined output curve of wind and solar energy, combined with the default risk factor, instead of the traditional idealized formula as the new energy output constraint in the comprehensive energy system optimization algorithm. It properly solves the problem that in the traditional optimization algorithm, only the wind and solar energy output are calculated separately, and it is impossible to deeply restore the power generation characteristics of wind and solar power stations under typical meteorological conditions such as "low wind speed on sunny days" and "strong sunlight on cloudy days".

[0032] S102, calculating the load regulation capacity of the target area; The above step S102 also includes S1021: constructing an electrical parameter model and a thermal parameter model of the target area, wherein the electrical parameter model and the thermal parameter model are used to determine the air conditioning load regulation capability, and the air conditioning load regulation capability reflects the load regulation capability of the target area.

[0033] The above step S1021 further includes S10211: determining the power consumption of the air conditioner based on the following formula: (1a) The air conditioning power supply is determined based on the following formula: (1b) Determine the indoor temperature of the air conditioner based on the following formula: (1c) Among them, P w is the power consumption of the air conditioner, Q(t) is the power supply of the air conditioner at time t; Tr(t) is the indoor temperature of the air conditioner at time t, ℃; τ is the simulation setting time step; η is the energy supply efficiency of the variable frequency air conditioner; a, b, c, d are the simulation parameters of the variable frequency air conditioner energy supply; T ext (t) is the outdoor temperature at time t, °C; T set (t) is the set temperature of the air conditioner at time t, ℃; H is the thermal conductivity between the room where the air conditioner is located and the outdoors; E is the equivalent thermal mass of the room where the air conditioner is located.

[0034] Based on the above scheme, energy storage elements and centralized air conditioning loads are innovatively used as adjustment means, based on a two-stage algorithm, combined with a demand response mechanism, to achieve multi-time scale operation optimization of the integrated energy system in the "load follows source" mode. It can not only effectively fill the simulation deviation in the calculation of wind and solar output, ensure the safety of the operation of the integrated energy system, but also deeply improve the economy and low carbon of the system operation by changing the output ratio of the energy supply unit.

[0035] S103: Optimize the integrated energy system based on the wind and solar power combined output data and load regulation capability of the target area.

[0036] In summary, this application uses a combination of Copula functions, an equivalent thermal parameter model (ETP, Equivalent Thermal Parameters Model) and a two-stage optimization algorithm to achieve wind and solar joint output simulation, combined with a multi-device simulation model of an integrated energy system, to achieve multi-time operation optimization of the integrated energy system under the new mode of "load follows source". It overcomes the problems that the existing methods cannot effectively realize the calculation of wind and solar joint output, and it is difficult to effectively characterize the output curves of wind and photovoltaic power stations in the same space-time dimension; the operation optimization algorithm cannot dynamically adjust the energy supply strategy of the integrated energy system, and timely compensate for the errors in wind and solar energy output.

[0037] The above step S103 also includes S1031: constructing an optimization model for the day-ahead stage and an optimization model for the intraday stage; and optimizing the integrated energy system based on the optimization model for the day-ahead stage and the optimization model for the intraday stage.

[0038] The above step S1031 also includes S10311 and S10312: S10311. Construct an optimization model for the day-ahead stage based on the following formula, wherein the objective function of the optimization model for the day-ahead stage is to minimize the global operating cost, maximize the consumption of new energy, and minimize the carbon emissions, and the constraints are the equipment output constraint and the supply-demand balance constraint: (1d) (1e) (1f) (1g) in, f 1max is the maximum value of the new energy consumption rate of the model, f 2min Minimum system operating cost, f 3min is the minimum carbon emission value, where P ne and P ne，max They are the new energy consumption and the maximum new energy consumption respectively; C C，i , C P，i and C CO2，i Respectively i The purchase price of the primary energy i The operating cost per unit energy output of the energy supply equipment and the i CO2 emissions from each primary energy source; Q i and P i Respectively i The consumption of primary energy i The energy output of a power supply device is represented by I, where I is the type of the power supply device.

[0039] S10312. Construct an optimization model for the intra-day stage based on the following formula, wherein the objective function of the optimization model for the intra-day stage is to minimize the adjustment cost, and the constraint condition is the adjustable power constraint:

[0040]

[0041] Among them, the optimization model of the intraday optimization stage f Depend on f 4 and f 5, among which, f 4 is the regulation cost of the storage device, Δ E d ( t) and Δ E c ( t ) are respectively t The difference between the discharge and charge of the power storage device at any moment; R ( t ) is a parameter of 0 or 1. When the energy storage device is in the charging state, R ( t )=0, otherwise, R ( t )=1; f 5 is the response compensation cost of air conditioning load; C oc,1 Unit price for response compensation costs; The wind / solar output error of the optimization model of the day-ahead stage is corrected based on the optimization model of the intra-day stage.

[0042] Specifically, during the intraday stage, based mainly on demand response technology, errors in the calculation of the combined output of wind and solar power are further corrected through adjustable loads and energy storage equipment.

[0043] Furthermore, the above constraints include: (1j) Formula (1j) is the combined power generation constraint of wind and solar energy based on the description of the optimal function Copula function; P wp and P pp (t) are t The planned power generation of the wind power station and the planned power generation of the photovoltaic power station at the moment, in kW; C -1 ( P i ) is the inverse function of the Copula function that describes the joint distribution of wind and solar output, P i is the risk level. The default level represents the default risk factor level of the planned output of wind and solar energy. The larger the value is, the higher the probability that the planned output is greater than the actual output.

[0044] (1k) in, Q i ( t )and Q i，max ( t ) are t Moment i The energy output of the energy supply equipment and the i The rated capacity of an energy supply device.

[0045] 1) Supply and demand balance constraints (1l) (1m) in, E i ( t )and C i ( t ) are respectively t The total power supply and cooling capacity of the system at all times; N e ( t )and N c ( t ) are the electricity and cooling demands on the load side respectively.

[0046] 2) Climbing constraints (1n) in, Q i ( t )and Q i ( t- 1) respectively t moment and the previous moment i The energy output of the energy supply equipment; Q i，lim ( t ) is the i The energy climbing constraint of a kind of energy supply equipment.

[0047] On the basis of the day-ahead constraints, new optimization constraints for intraday operation are added as follows: (1p) (1q) (1r) (1s) in, E DR ( t ) are respectively t The air conditioning load at each moment meets the adjustment power of the demand response; Δ E It is the difference between the actual wind and solar output during the day and the wind and solar output calculated the day before.

[0048] Through the above technical scheme, in view of the increased risk of imbalance between supply and demand of integrated energy system caused by the current large-scale access of wind and solar energy, and the inability of the traditional "source follows load" scheduling method to effectively make up for the calculation errors of wind and solar output, an integrated energy system operation optimization method considering the interactive characteristics of adjustable resources is proposed. Taking a certain integrated energy park as the research object, firstly, by collecting and integrating the historical data of wind and solar power generation in the study area, the marginal distribution function of wind and solar power generation is obtained, and the unknown parameter values ​​existing in the normal-Copula, t-Copula and three Archimedean Copula functions (including Calyton-Copula, Frank-Copula and Gumbel-Copula) are obtained. By introducing Kendall and Spearman as evaluation indicators, the calculation The rank correlation coefficients of the above five Copula functions are used to select the Copula function that is most suitable for describing the combined output of wind and solar power in the study area; secondly, based on the equivalent electrical parameter model and thermal parameter model of the variable frequency air conditioner, a centralized air conditioning load regulation capacity calculation model is established to obtain the adjustable power domain of the centralized air conditioning; finally, the optimal Copula function expression is used as the output constraint of wind and solar energy, and the centralized air conditioning load regulation capacity calculation model is used as the operation constraint of the adjustable load. Combined with the mechanism simulation model of each energy supply equipment in the integrated energy system, coupled with the demand response mechanism, with the minimization of global operating costs, maximization of new energy consumption, minimization of carbon emissions, and maximization of energy efficiency as the optimization goals, an integrated energy system operation optimization algorithm considering the interactive characteristics of adjustable resources is established, and finally the optimal operation plan of the integrated energy system day-ahead and day-intraday is obtained. The above scheme avoids the negative impact of the intermittent and random nature of wind and solar energy, makes full use of the flexible resources on the load side, fully mobilizes the interactive characteristics between "source-load", and proposes a "load follows source" scheduling mode that is more suitable for uncertain resources such as wind and light, thereby improving the economy, safety, stability and low carbon nature of the integrated energy system, laying an important foundation for the large-scale promotion of the integrated energy system.

[0049] Furthermore, as a response to the above Figure 1 In order to realize the method shown in the figure, the embodiment of the present invention also provides a comprehensive energy system operation optimization device for Figure 1 The device embodiment corresponds to the aforementioned method embodiment. For ease of reading, this device embodiment will not repeat the details of the aforementioned method embodiment one by one, but it should be clear that the device in this embodiment can correspond to all the contents of the aforementioned method embodiment. Figure 3 As shown, the device includes: a determination unit 21, a calculation unit 22 and an optimization unit 23, wherein A determination unit 21, used to determine wind and solar power combined output data of a target area; A calculation unit 22, used to calculate the load regulation capacity of the target area; The optimization unit 23 is used to optimize the integrated energy system based on the wind and solar power combined output data and load regulation capability of the target area.

[0050] The processor includes a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set, and a method for optimizing the operation of an integrated energy system can be implemented by adjusting kernel parameters, which can solve the problem of imbalance in the operation of the integrated energy system caused by the access of traditional large-scale wind and solar energy.

[0051] An embodiment of the present invention provides a computer-readable storage medium, which includes a stored program, and when the program is executed by a processor, the integrated energy system operation optimization method is implemented.

[0052] An embodiment of the present invention provides a processor, which is used to run a program, wherein the integrated energy system operation optimization method is executed when the program is running.

[0053] An embodiment of the present invention provides an electronic device, the electronic device comprising at least one processor and at least one memory connected to the processor; wherein the processor is used to call program instructions in the memory to execute the above-mentioned integrated energy system operation optimization method An embodiment of the present invention provides an electronic device 30, such as Figure 4 As shown, the electronic device includes at least one processor 301, and at least one memory 302 and a bus 303 connected to the processor; wherein the processor 301 and the memory 302 communicate with each other through the bus 303; the processor 301 is used to call the program instructions in the memory to execute the above-mentioned integrated energy system operation optimization method.

[0054] The intelligent electronic devices in this article can be PCs, PADs, mobile phones, etc.

[0055] The present application also provides a computer program product, which, when executed on a process management electronic device, is suitable for executing a program that initializes the steps of the above-mentioned integrated energy system operation optimization method.

[0056] It is known from common technical knowledge that the present invention can be implemented by other embodiments that do not deviate from its spirit or essential features. Therefore, the above disclosed embodiments are only illustrative in all respects and are not exclusive. All changes within the scope of the present invention or within the scope equivalent to the present invention are included in the present invention.

[0057] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0058] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0059] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0060] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0061] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for optimizing the operation of an integrated energy system, characterized in that: include: Determine the wind and solar combined output data for the target area; Calculate the load regulation capacity of the target area; The integrated energy system is optimized based on the wind and solar combined output data and load regulation capability of the target area.

2. The method according to claim 1, characterized in that The determination of the wind and solar power combined output data of the target area includes: Determine the marginal distribution function of wind and solar power generation based on historical data of wind and solar power generation in the target area; Determining unknown parameters of a standby function based on the marginal distribution function, wherein the standby function includes a normal-Copula function, a t-Copula function, a Calyton-Copula function, a Frank-Copula function, and a Gumbel-Copula function; Determine the rank correlation coefficient of the function to be used using Kendall and Spearman as evaluation indicators; Determining the optimal function among the standby functions based on the evaluation index calculation result, wherein the evaluation index calculation result is used to feedback the adaptability of the standby function to the target area; The wind and solar combined output data of the target area are determined by the optimal function in combination with the risk assessment factor.

3. The method according to claim 1, characterized in that The calculation of the load regulation capacity of the target area includes: An electrical parameter model and a thermal parameter model of the target area are constructed, wherein the electrical parameter model and the thermal parameter model are used to determine an air conditioning load regulation capability, and the air conditioning load regulation capability reflects the load regulation capability of the target area.

4. The method according to claim 3, characterized in that Constructing an electrical parameter model and a thermal parameter model of the target area, including: Determine the power consumption of the air conditioner based on the following formula: The air conditioning power supply is determined based on the following formula: Determine the indoor temperature of the air conditioner based on the following formula: Among them, P w is the power consumption of the air conditioner, Q(t) is the power supply of the air conditioner at time t; Tr(t) is the indoor temperature of the air conditioner at time t, ℃; τ is the simulation setting time step; η is the energy supply efficiency of the variable frequency air conditioner; a, b, c, d are the simulation parameters of the variable frequency air conditioner energy supply; T ext (t) is the outdoor temperature at time t, °C; T set (t) is the set temperature of the air conditioner at time t, ℃; H is the thermal conductivity between the room where the air conditioner is located and the outdoors; E is the equivalent thermal mass of the room where the air conditioner is located.

5. The method according to claim 1, characterized in that The integrated energy system optimization based on the wind and solar power combined output data and load regulation capability of the target area includes: Construct optimization models for the day-ahead phase and intraday phase; The integrated energy system is optimized based on the optimization model of the day-ahead stage and the optimization model of the intraday stage.

6. The method according to claim 5, characterized in that The construction of the optimization model for the day-ahead phase and the optimization model for the intraday phase includes: The optimization model of the day-ahead stage is constructed based on the following formula, wherein the objective function of the optimization model of the day-ahead stage is to minimize the global operating cost, maximize the consumption of new energy, and minimize the carbon emissions, and the constraints are the equipment output constraint and the supply-demand balance constraint: in, f 1max is the maximum value of the new energy consumption rate of the model, f 2min Minimum system operating cost, f 3min is the minimum carbon emission value, where P ne and P ne，max They are the new energy consumption and the maximum new energy consumption respectively; C C，i , C P，i and C CO2，i Respectively i The purchase price of the primary energy i The operating cost per unit energy output of the energy supply equipment and the i CO2 emissions from each primary energy source; Q i and P i Respectively i The consumption of primary energy i The energy output of a power supply device is represented by I, where I is the type of the power supply device.

7. The method according to claim 6, characterized in that The construction of the optimization model for the day-ahead phase and the optimization model for the intraday phase includes: The optimization model for the intraday stage is constructed based on the following formula, wherein the objective function of the optimization model for the intraday stage is to minimize the adjustment cost and the constraint condition is the adjustable power constraint: Among them, the optimization model of the intraday optimization stage f Depend on f 4 and f 5, among which, f 4 is the regulation cost of the storage device, Δ E d ( t ) and Δ E c ( t ) are respectively t The difference between the discharge and charge of the power storage device at any moment; R ( t ) is a parameter of 0 or 1. When the energy storage device is in the charging state, R ( t )=0, otherwise, R ( t )=1; f 5 is the response compensation cost of air conditioning load; C oc,1 Unit price for response compensation costs; The wind / solar output error of the optimization model of the day-ahead stage is corrected based on the optimization model of the intra-day stage.

8. An integrated energy system operation optimization device, characterized in that: Also includes: A determination unit, used to determine wind and solar power combined output data of a target area; A calculation unit, used for calculating the load regulation capacity of the target area; The optimization unit is used to optimize the integrated energy system based on the wind and solar combined output data and load regulation capability of the target area.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed by a processor, the steps of the integrated energy system operation optimization method according to any one of claims 1 to 7 are implemented.

10. An electronic device, characterized in that: The electronic device includes at least one processor and at least one memory connected to the processor; wherein the processor is used to call program instructions in the memory to execute the steps of the integrated energy system operation optimization method as described in any one of claims 1 to claim 7.

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