Dispatch Method and Device for Energy-Coupled Virtual Power Plant Based on Multiple Energy Storage Devices

Abstract

This application provides a scheduling method and apparatus for an energy-coupled virtual power plant based on multiple energy storage devices. The method includes: acquiring historical operating parameters, including power plant operating parameters and power plant cost parameters; constructing a power plant simulation model based on the operating parameters; constructing a power plant cost model based on the simulation model and the cost parameters; constructing a set of objective constraints to limit the range of values ​​for the operating parameters of the simulation model; and, under the constraints of the objective constraints, solving for the operating parameters of the simulation model using the maximum net profit of the virtual power plant as the objective function to obtain the power plant control parameters. This method addresses the problem in existing technologies where planning virtual power plants based on electricity as a link does not meet the actual operating conditions of current multi-energy coupling, leading to deviations in scheduling strategy benefits.

Description

Technical Field

[0001] This invention relates to the field of virtual power plant scheduling and planning technology, and more specifically, to a scheduling method, apparatus, computer-readable storage medium, processor, and virtual power plant scheduling system based on an energy-coupled virtual power plant with multiple energy storage devices. Background Technology

[0002] As a major source of carbon emissions in my country, the energy and power industry faces challenges such as the volatility and intermittency of renewable energy and the spatiotemporal heterogeneity of different energy sources. The coupling of multiple types of energy storage with energy systems will effectively solve these problems, further promote energy complementarity, and improve utilization efficiency.

[0003] Traditional virtual power plants use electricity as a link to connect distributed power sources, flexible resources, and loads, operating with the goals of flexible control and clean energy consumption. However, with the addition of combined heat and power units, gas turbine boilers, and power-to-gas conversion equipment, natural gas and heat are introduced on top of electricity, enriching the source and load resources of virtual power plants and improving their comprehensiveness and practicality.

[0004] However, existing virtual power plant scheduling and planning methods only consider electricity as the link and do not take into account the impact of equipment such as cogeneration units, gas turbine boilers, and power-to-gas conversion equipment, resulting in poor scheduling strategy results. Summary of the Invention

[0005] The main objective of this application is to provide a scheduling method, apparatus, computer-readable storage medium, processor, and virtual power plant scheduling system based on energy coupling virtual power plants with multiple energy storage devices, so as to at least solve the problem that the planning of virtual power plants based on electricity as a link in the prior art does not meet the actual operating state of current multi-energy coupling, resulting in deviations in the benefits of scheduling strategies.

[0006] To achieve the above objectives, according to one aspect of this application, a scheduling method for an energy-coupled virtual power plant based on multiple energy storage devices is provided, comprising: acquiring historical operating parameters, the historical operating parameters including power plant operating parameters and power plant cost parameters, the power plant operating parameters including operating parameters of each component of the virtual power plant, the power plant cost parameters including the operating costs of each component of the virtual power plant, the component including at least a WPP unit, a PV unit, a CHP unit, a gas boiler, a thermal storage tank, a gas storage tank, an electric energy storage device, and an electrical conversion device; the PV unit converts solar energy into electrical energy to supply electrical load; the WPP unit converts wind energy into electrical energy to supply the electrical load, the electrical conversion device, and the electric energy storage device; the CHP unit converts natural gas into electrical energy to supply the electric energy storage device and the electrical load, and the generated heat supplies a heat load; the gas boiler converts natural gas into heat energy to supply the heat load and the thermal storage tank; the thermal storage tank is used to store heat energy and supply the heat load; and the electrical conversion device is used to receive electrical energy and perform electrical conversion to generate natural gas. The system stores natural gas and supplies it to the gas storage tank, which is used to store natural gas and supply it to the CHP unit and the gas boiler. The electric energy storage device stores electrical energy and supplies it to the electrical conversion device. A power plant simulation model is constructed based on the power plant operating parameters. The power plant simulation model is used to simulate the energy flow between the various components. A power plant cost model is constructed based on the power plant simulation model and the power plant cost parameters. The power plant cost model is used to simulate the cost trend of the virtual power plant as a function of the operating parameters of the power plant simulation model. A set of target constraints is constructed to limit the range of values ​​of the operating parameters of the power plant simulation model. The set of target constraints includes at least power balance constraints, CHP unit output constraints, WPP unit output constraints, PV unit output constraints, CHP unit power constraints, and reserve capacity constraints. Under the constraints of the set of target constraints, the operating parameters of the power plant simulation model are solved to obtain the power plant control parameters, with the objective function being to maximize the net profit of the virtual power plant. The operation of the virtual power plant is controlled according to the power plant control parameters.

[0007] Optionally, constructing a power plant simulation model based on the power plant operating parameters includes: determining a first input power, a first power generation, and a first heat production power based on the power plant operating parameters; constructing a first target formula based on the first input power and the first power generation; and constructing a second target formula based on the first input power and the first heat production power. The first input power is the gas input power of the CHP unit, the first power generation is the power generation of the CHP unit, and the first heat production power is the heat production power of the CHP unit. The first target formula is used to simulate the changing trend of the first power generation with the first input power, and the second target formula is used to simulate the changing trend of the first heat production power with the first input power. The variation trend of the first input power; the first wind speed and the second power generation are determined according to the power plant operating parameters; a third target formula is constructed based on the first wind speed and the second power generation, where the first wind speed is the input wind speed of the WPP unit and the second power generation is the power generation of the WPP unit; the third target formula is used to simulate the variation trend of the second power generation with the first wind speed; the second input power, the target area, and the third power generation are determined according to the power plant operating parameters; a fourth target formula is constructed based on the second input power, the target area, and the third power generation, where the second input power is the solar input power of the PV unit and the target area is the photovoltaic area of ​​the PV unit. The total area of ​​the components; the third power generation is the power generation of the PV unit; the third target formula is used to simulate the changing trend of the third power generation with the second input power; the first input and the first output are determined according to the power plant operating parameters; the fifth target formula is constructed based on the first input and the first output, where the first input is the electrical energy input of the electrical conversion device and the first output is the natural gas output of the electrical conversion device; the fifth target formula is used to simulate the changing trend of the first output with the first input; the second input and the second output are determined according to the power plant operating parameters; the sixth target formula is constructed based on the second input and the second output. The second input is the natural gas input of the gas-fired boiler, and the second output is the heat output of the gas-fired boiler. The sixth target formula is used to simulate the trend of the second output with the second input. The third input power, the first output power, and the capacity are determined according to the power plant operating parameters. The seventh target formula is constructed according to the third input power, the first output power, and the capacity. The third input power is the charging power of the energy storage device, the first output power is the discharging power of the energy storage device, and the capacity is the stored energy of the energy storage device. The seventh target formula is used to simulate the trend of the capacity with the third input power and the first output power.Based on the power plant operating parameters, a fourth input power, a second output power, and a heat capacity are determined. An eighth target formula is constructed based on the fourth input power, the second output power, and the heat capacity. The fourth input power is the thermal energy input power of the thermal storage tank, the second output power is the thermal energy output power of the thermal storage tank, and the heat capacity is the stored thermal energy of the thermal storage tank. The eighth target formula is used to simulate the changing trend of the heat capacity with the fourth input power and the second output power. A third input quantity, a third output quantity, a fourth output quantity, and gas storage capacity are determined based on the power plant operating parameters. The third input, the third output, the fourth output, and the gas storage capacity are used to construct the ninth objective formula. The third input is the natural gas input to the gas storage tank, the third output is the natural gas output from the gas storage tank to the gas-fired boiler, and the fourth output is the natural gas output from the gas storage tank to the CHP unit. The power plant simulation model is obtained by simultaneously applying the first, second, third, fourth, fifth, sixth, seventh, eighth, and ninth objective formulas.

[0008] Optionally, a power plant cost model is constructed based on the power plant simulation model and the power plant cost parameters, including: determining a first coefficient, a second coefficient, a third coefficient, a first variable, and a first start-up cost based on the power plant cost parameters; constructing a tenth objective formula based on the first coefficient, the second coefficient, the third coefficient, and the first power generation; constructing an eleventh objective formula based on the first variable and the first start-up cost, wherein the first coefficient, the second coefficient, and the third coefficient are the energy consumption coefficients of the CHP unit; the tenth objective formula is used to simulate the trend of the fuel cost of the CHP unit changing with the first power generation; the first variable is a binary variable indicating whether the CHP unit generates electricity; the first start-up cost is the start-up cost of the CHP unit; and the eleventh objective formula is used to simulate the trend of the start-up and shutdown costs of the CHP unit changing with the first variable; determining a first operating cost and a first depreciation cost based on the power plant cost parameters; constructing a twelfth objective formula based on the first operating cost, the first depreciation cost, and the second power generation, wherein the first operating cost is the unit power generation cost of the WPP unit; the first depreciation cost is the loss cost of the WPP unit; and the twelfth objective formula is used to simulate the total cost of the WPP unit changing with the second power generation. The trend of change; the second operating cost and the second depreciation cost are determined according to the power plant cost parameters. A thirteenth target formula is constructed based on the second operating cost, the second depreciation cost, and the third power generation, where the second operating cost is the unit power generation cost of the PV unit, and the second depreciation cost is the loss cost of the PV unit. The thirteenth target formula is used to simulate the trend of change of the total cost of the PV unit with the third power generation. The third depreciation cost is determined according to the power plant cost parameters. A fourteenth target formula is constructed based on the second operating cost, the first input quantity, and the third depreciation cost. The third depreciation cost is the electrical... The loss cost of the conversion device is calculated using the fourteenth objective formula, which simulates the trend of the total cost of the electrical conversion device changing with the first input. A third operating cost is determined based on the power plant cost parameters. A fifteenth objective formula is constructed based on the third operating cost and the second input, where the third operating cost is the real-time electricity price of natural gas. This fifteenth objective formula simulates the trend of the total cost of the gas-fired boiler changing with the second input. The power plant cost model is obtained by simultaneously applying the tenth, eleventh, twelfth, thirteenth, fourteenth, and fifteenth objective formulas.

[0009] Optionally, the power plant cost model is obtained by simultaneously applying the tenth, eleventh, twelfth, thirteenth, fourteenth, and fifteenth objective formulas, including: determining a fourth depreciation cost based on the power plant cost parameters, wherein the fourth depreciation cost includes a fifth, sixth, and seventh depreciation cost, the fifth depreciation cost being the loss cost of the energy storage device, the sixth depreciation cost being the loss cost of the gas storage tank, and the seventh depreciation cost being the loss cost of the thermal storage tank; determining the first power generation, the first variable, the second power generation, the third power generation, the first input quantity, and the second input quantity as input parameters of the power plant cost model; and determining the sum of the calculation results of the tenth, eleventh, eleventh, twelfth, thirteenth, fourteenth, and fifteenth objective formulas and the sum of the fourth depreciation cost as output parameters of the power plant cost model, thereby obtaining the power plant cost model.

[0010] Optionally, before solving the operating parameters of the power plant simulation model to obtain the power plant control parameters with the net profit of the power plant cost model as the objective function, the method further includes: constructing a power plant revenue model based on the power plant simulation model, wherein the power plant revenue model is used to simulate the trend of the revenue of the virtual power plant changing with the operating parameters of the power plant simulation model.

[0011] Optionally, a power plant revenue model is constructed based on the power plant simulation model, including: obtaining a first unit price and a second unit price, where the first unit price is the electricity sales price of the virtual power plant and the second unit price is the heat sales price of the virtual power plant; constructing a sixteenth objective formula based on the first unit price, the second unit price, the first power generation capacity, and the first heat generation capacity, wherein the sixteenth objective formula is used to simulate the revenue trend of the CHP unit with the change of the first power generation capacity and the first heat generation capacity; constructing a seventeenth objective formula based on the first unit price, the second power generation capacity, and the third power generation capacity, wherein the seventeenth objective formula is used to simulate the total revenue trend of the WPP unit and the PV unit with the change of the second power generation capacity and the third power generation capacity; constructing an eighteenth objective formula based on the second unit price and the second output, wherein the eighteenth objective formula is used to simulate the revenue trend of the gas boiler with the change of the second output; and combining the sixteenth, seventeenth, and eighteenth objective formulas to obtain the power plant revenue model.

[0012] Optionally, constructing a target constraint group includes: constructing the power balance constraint of the virtual power plant corresponding to the power plant simulation model to obtain a first target constraint; constructing the CHP unit output constraint of the virtual power plant corresponding to the power plant simulation model to obtain a second target constraint; constructing the WPP unit output constraint of the virtual power plant corresponding to the power plant simulation model to obtain a third target constraint; constructing the PV unit output constraint of the virtual power plant corresponding to the power plant simulation model to obtain a fourth target constraint; constructing the CHP unit power constraint of the virtual power plant corresponding to the power plant simulation model to obtain a fifth target constraint; constructing the reserve capacity constraint of the virtual power plant corresponding to the power plant simulation model to obtain a sixth target constraint; and combining the first target constraint, the second target constraint, the third target constraint, the fourth target constraint, the fifth target constraint, and the sixth target constraint to obtain the target constraint group.

[0013] According to another aspect of this application, a scheduling device for an energy-coupled virtual power plant based on multiple energy storage devices is provided. The device includes: an acquisition unit for acquiring historical operating parameters, which include power plant operating parameters and power plant cost parameters. The power plant operating parameters include operating parameters of each component of the virtual power plant, and the power plant cost parameters include the operating costs of each component of the virtual power plant. The components include at least a WPP unit, a PV unit, a CHP unit, a gas boiler, a thermal storage tank, a gas storage tank, an electric energy storage device, and an electrical conversion device. The PV unit converts solar energy into electrical energy to supply the electrical load; the WPP unit converts wind energy into electrical energy to supply the electrical load; the electrical conversion device and the energy storage device; the CHP unit converts natural gas into electrical energy to supply the energy storage device and the electrical load, and the generated heat supplies the thermal load; the gas boiler converts natural gas into heat energy to supply the thermal load and the thermal storage tank; the thermal storage tank is used to store heat energy and supply the thermal load; the electrical conversion device is used to receive electrical energy, perform electrical conversion to generate natural gas, and supply it to the gas storage tank; the gas storage tank is used for... The system includes: a first construction unit for storing natural gas and supplying it to the CHP unit and the gas-fired boiler; an electric energy storage device for storing electrical energy and supplying it to the electrical conversion device; a second construction unit for constructing a power plant simulation model based on the power plant operating parameters, the simulation model simulating energy flow between the constituent components; a third construction unit for constructing a target constraint group for limiting the range of values ​​for the operating parameters of the power plant simulation model, including at least power balance constraints, CHP unit output constraints, WPP unit output constraints, PV unit output constraints, CHP unit power constraints, and reserve capacity constraints; and a calculation unit for solving the operating parameters of the power plant simulation model under the constraints of the target constraint group, using the maximum net profit of the virtual power plant as the objective function to obtain power plant control parameters, and controlling the operation of the virtual power plant according to the control parameters.

[0014] According to another aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform any of the methods described.

[0015] According to another aspect of this application, a virtual power plant dispatching system is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including methods for performing any one of the methods described.

[0016] Applying the technical solution of this application, in the above-mentioned scheduling method for an energy-coupled virtual power plant based on multiple energy storage devices, firstly, historical operating parameters are obtained. These historical operating parameters include power plant operating parameters and power plant cost parameters. The power plant operating parameters include the operating parameters of each component of the virtual power plant, and the power plant cost parameters include the operating costs of each component of the virtual power plant. The components include at least a WPP unit, a PV unit, a CHP unit, a gas boiler, a thermal storage tank, a gas storage tank, an electric energy storage device, and an electrical conversion device. The PV unit converts solar energy into electrical energy to supply the electrical load. The WPP unit converts wind energy into electrical energy to supply the electrical load, the electrical conversion device, and the electric energy storage device. The CHP unit converts natural gas into electrical energy to supply the electric energy storage device and the electrical load, and the generated heat supplies the heat load. The gas boiler converts natural gas into heat energy to supply the heat load and the thermal storage tank. The thermal storage tank stores heat energy and supplies the heat load. The electrical conversion device receives electrical energy, performs electrical conversion to generate natural gas, and supplies it to the gas storage tank. The gas storage tank is used to store natural gas and supply it to the aforementioned CHP unit and gas-fired boiler. The electric energy storage device is used to store electrical energy and supply it to the aforementioned electrical conversion device. Then, a power plant simulation model is constructed based on the aforementioned power plant operating parameters. This simulation model is used to simulate the energy flow between the aforementioned components. Next, a power plant cost model is constructed based on the aforementioned power plant simulation model and the aforementioned power plant cost parameters. This cost model is used to simulate the cost trend of the virtual power plant as a function of the operating parameters of the aforementioned power plant simulation model. Then, a set of target constraints is constructed to limit the range of values ​​for the operating parameters of the aforementioned power plant simulation model. This set of target constraints includes at least power balance constraints, CHP unit output constraints, WPP unit output constraints, PV unit output constraints, CHP unit power constraints, and reserve capacity constraints. Finally, under the constraints of the aforementioned target constraints, the operating parameters of the aforementioned power plant simulation model are solved to obtain the power plant control parameters, with the objective function being the maximum net profit of the aforementioned virtual power plant. The operation of the virtual power plant is then controlled based on these power plant control parameters. This application performs physical simulation modeling on WPP units, PV units, CHP units, gas-fired boilers, thermal storage tanks, gas storage tanks, electric energy storage devices, and electrical conversion devices, constructing corresponding models and establishing energy flow relationships between each model to obtain the aforementioned power plant simulation models. Based on the operating parameters of the power plant simulation models, a correlation between operating parameters and costs is constructed to obtain a power plant cost model. Then, under constraints, a solution is performed with net profit maximization as the objective function to obtain a control strategy, and the virtual power plant is scheduled based on the control strategy. This method solves the problem in existing technologies where planning virtual power plants based on electricity as a link does not meet the actual operating conditions of current multi-energy coupling, leading to deviations in the benefits of scheduling strategies. Attached Figure Description

[0017] Figure 1 A hardware structure block diagram of a mobile terminal for a scheduling method of an energy-coupled virtual power plant based on multiple energy storage devices, provided in an embodiment of this application, is shown.

[0018] Figure 2 A flowchart illustrating a scheduling method for an energy-coupled virtual power plant based on multiple energy storage devices, according to an embodiment of this application, is shown.

[0019] Figure 3 A structural block diagram of a dispatching device for an energy-coupled virtual power plant based on multiple energy storage devices, according to an embodiment of this application, is shown.

[0020] The above figures include the following reference numerals:

[0021] 102. Processor; 104. Memory; 106. Transmission device; 108. Input / output device. Detailed Implementation

[0022] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0023] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0024] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0025] As described in the background section, existing virtual power plant scheduling and planning methods only consider electricity as the link and do not take into account the impact of equipment such as cogeneration units, gas turbine boilers, and power-to-gas conversion equipment, resulting in poor scheduling strategy results. To address the problem that existing virtual power plant planning based on electricity does not meet the actual operating conditions of current multi-energy coupling, leading to deviations in scheduling strategy benefits, embodiments of this application provide a scheduling method, apparatus, computer-readable storage medium, processor, and virtual power plant scheduling system based on energy coupling virtual power plants with multiple energy storage devices.

[0026] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0027] The methods and embodiments provided in this application can be executed on a mobile terminal, computer terminal, or similar computing device. Taking running on a mobile terminal as an example, Figure 1 This is a hardware structure block diagram of a mobile terminal for a scheduling method of an energy coupling virtual power plant based on multiple energy storage devices, according to an embodiment of the present invention. Figure 1 As shown, a mobile terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the mobile terminal described above. For example, the mobile terminal may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0028] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the device information display method in this embodiment of the invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of the aforementioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. The transmission device 106 is used to receive or send data via a network. Specific examples of the aforementioned networks may include wireless networks provided by the mobile terminal's communication provider. In one example, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0029] This embodiment provides a scheduling method for an energy-coupled virtual power plant based on multiple energy storage devices, which runs on a mobile terminal, computer terminal, or similar computing device. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Also, although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than that shown here.

[0030] Figure 2 This is a flowchart of a scheduling method for an energy-coupled virtual power plant based on multiple energy storage devices, according to an embodiment of this application. Figure 2 As shown, the method includes the following steps:

[0031] Step S201: Obtain historical operating parameters, including power plant operating parameters and power plant cost parameters. The power plant operating parameters include the operating parameters of each component of the virtual power plant, and the power plant cost parameters include the operating costs of each component of the virtual power plant. The components include at least WPP units, PV units, CHP units, gas boilers, thermal storage tanks, gas storage tanks, energy storage devices, and electrical conversion devices. The PV units convert solar energy into electrical energy to supply the electrical load, and the WPP units convert wind energy into electrical energy to supply the electrical load. The aforementioned electrical conversion device and energy storage device are described. The CHP unit converts natural gas into electrical energy to supply the energy storage device and the electrical load, and the generated heat supplies the heat load. The gas boiler converts natural gas into heat energy to supply the heat load and the heat storage tank. The heat storage tank is used to store heat energy and supply the heat load. The electrical conversion device is used to receive electrical energy, perform electrical conversion to generate natural gas, and supply it to the gas storage tank. The gas storage tank is used to store natural gas and supply it to the CHP unit and the gas boiler. The energy storage device is used to store electrical energy and supply it to the electrical conversion device.

[0032] Specifically, in actual production, virtual power plants introduce carbon capture devices in addition to power operation, consider the flow of two types of energy, and utilize by-products to improve overall economic benefits. Therefore, in order to solve the problem that the revenue growth of the planning and dispatching strategy is lower than expected due to the fact that the existing virtual power plant dispatching method does not consider the equipment required for multi-energy integration and the related impact of carbon capture devices, this application proposes to first determine the structure of the virtual power plant, including generating units, energy storage devices, and flexible components.

[0033] In one embodiment, the aforementioned units include WPP units (wind turbines), PV units (photovoltaic turbines), and CHP units (cogeneration units). The aforementioned energy storage devices include thermal storage tanks, gas storage tanks, and electrical energy storage devices. The aforementioned flexibility components include power conversion devices and gas-fired boilers. Wind power, photovoltaic, and cogeneration units generate electricity as power sources. The electrical energy storage devices can store excess electricity and release it during peak load periods. Waste heat from the cogeneration units and heat generated by the gas-fired boilers can supply the heat load or be stored in thermal storage tanks. Furthermore, the cogeneration units and gas-fired boilers are driven by natural gas. Power-to-gas (P2G) equipment can catalytically produce methane from carbon dioxide. The generated methane can be supplied to the cogeneration units and gas turbines or stored in gas storage tanks, with its flow determined by the operating power of the cogeneration units and gas-fired boilers.

[0034] In addition, based on the operating characteristics of each of the above components, their costs are determined, including the operating costs of power sources and heat sources, the operating conditions of various energy storage devices, and the operating costs of electric-to-gas generator units.

[0035] Step S202: Construct a power plant simulation model based on the above power plant operating parameters. The power plant simulation model is used to simulate the energy flow between the above-mentioned components.

[0036] Specifically, based on the operating parameters of each component in the above historical operating parameters, the operating status of each component is simulated to obtain the above power plant simulation model.

[0037] Step S203: Construct a power plant cost model based on the above power plant simulation model and the above power plant cost parameters. The above power plant cost model is used to simulate the cost trend of the above virtual power plant as the operating parameters of the above power plant simulation model change.

[0038] Specifically, based on the relationship between the operating characteristics and operating costs of each of the above-mentioned components, a power plant cost model is constructed on the basis of the power plant simulation model, and the power plant simulation model and the power plant cost model are interconnected.

[0039] Step S204: Construct a target constraint group. The target constraint group is used to limit the range of values ​​of the operating parameters of the power plant simulation model. The target constraint group includes at least power balance constraints, CHP unit output constraints, WPP unit output constraints, PV unit output constraints, CHP unit power constraints, and reserve capacity constraints.

[0040] Specifically, to prevent the control results from not conforming to actual operation or damaging the components of the virtual power plant, this application sets the aforementioned target constraint group to limit the range of values ​​of the operating parameters of the power plant simulation model during the solution process, thereby ensuring the feasibility of the obtained scheduling strategy.

[0041] Step S205: Under the constraints of the above-mentioned target constraint group, with the maximum net profit of the above-mentioned virtual power plant as the objective function, the operating parameters of the above-mentioned power plant simulation model are solved to obtain the power plant control parameters, and the operation of the above-mentioned virtual power plant is controlled according to the above-mentioned power plant control parameters.

[0042] Specifically, under constraints, the operating parameters of the above-mentioned power plant simulation model are solved to obtain the power plant control parameters, with the objective function being to maximize the net profit of the virtual power plant. The operation of the virtual power plant is then controlled according to the above-mentioned power plant control parameters so that the virtual power plant can obtain the maximum profit.

[0043] In this embodiment, firstly, historical operating parameters are obtained. These historical operating parameters include power plant operating parameters and power plant cost parameters. The power plant operating parameters include the operating parameters of each component of the virtual power plant, and the power plant cost parameters include the operating costs of each component of the virtual power plant. The components include at least a WPP unit, a PV unit, a CHP unit, a gas boiler, a thermal storage tank, a gas storage tank, an electric energy storage device, and an electrical conversion device. The PV unit converts solar energy into electrical energy to supply the electrical load. The WPP unit converts wind energy into electrical energy to supply the electrical load, the electrical conversion device, and the electric energy storage device. The CHP unit converts natural gas into electrical energy to supply the electric energy storage device and the electrical load, and the generated heat supplies the heat load. The gas boiler converts natural gas into heat energy to supply the heat load and the thermal storage tank. The thermal storage tank stores heat energy and supplies the heat load. The electrical conversion device receives electrical energy, performs electrical conversion to generate natural gas, and supplies it to the gas storage tank. The gas storage tank stores natural gas and supplies it to the power plant. The CHP unit and the gas-fired boiler are described above. The electric energy storage device is used to store electrical energy and supply it to the electrical conversion device. Then, a power plant simulation model is constructed based on the power plant operating parameters. The power plant simulation model is used to simulate the energy flow between the various components. Next, a power plant cost model is constructed based on the power plant simulation model and the power plant cost parameters. The power plant cost model is used to simulate the cost trend of the virtual power plant as a function of the operating parameters of the power plant simulation model. Then, a set of target constraints is constructed to limit the range of values ​​of the operating parameters of the power plant simulation model. The set of target constraints includes at least power balance constraints, CHP unit output constraints, WPP unit output constraints, PV unit output constraints, CHP unit power constraints, and reserve capacity constraints. Finally, under the constraints of the set of target constraints, the operating parameters of the power plant simulation model are solved to obtain the power plant control parameters, with the maximum net profit of the virtual power plant as the objective function. The operation of the virtual power plant is controlled according to the power plant control parameters. This application performs physical simulation modeling on WPP units, PV units, CHP units, gas-fired boilers, thermal storage tanks, gas storage tanks, electric energy storage devices, and electrical conversion devices, constructing corresponding models and establishing energy flow relationships between each model to obtain the aforementioned power plant simulation models. Based on the operating parameters of the power plant simulation models, a correlation between operating parameters and costs is constructed to obtain a power plant cost model. Then, under constraints, a solution is performed with net profit maximization as the objective function to obtain a control strategy, and the virtual power plant is scheduled based on the control strategy. This method solves the problem in existing technologies where planning virtual power plants based on electricity as a link does not meet the actual operating conditions of current multi-energy coupling, leading to deviations in the benefits of scheduling strategies.

[0044] To construct the aforementioned power plant simulation model, in one optional implementation, step S202 includes:

[0045] Step S2021: Determine the first input power, the first power generation, and the first heat production power based on the above power plant operating parameters; construct a first target formula based on the first input power and the first power generation; construct a second target formula based on the first input power and the first heat production power; the first input power is the gas input power of the CHP unit; the first power generation is the power generation of the CHP unit; the first heat production power is the heat production power of the CHP unit; the first target formula is used to simulate the changing trend of the first power generation with the first input power; the second target formula is used to simulate the changing trend of the first heat production power with the first input power.

[0046] Specifically, the first input power is determined based on the aforementioned power plant operating parameters. First power generation and first heat production power A first target formula is constructed based on the first input power and the first power generation, and a second target formula is constructed based on the first input power and the first heat generation:

[0047]

[0048] Where, η e,CHP and η h,CHP These are the power conversion efficiency and thermal conversion efficiency of the CHP unit, respectively, determined based on historical operating parameters.

[0049] Step S2022: Determine the first wind speed and the second power generation based on the above power plant operating parameters, and construct a third target formula based on the first wind speed and the second power generation. The first wind speed is the input wind speed of the WPP unit, the second power generation is the power generation of the WPP unit, and the third target formula is used to simulate the change trend of the second power generation with the first wind speed.

[0050] Specifically, the first wind speed v(t) and the second power generation Q are determined based on the aforementioned power plant operating parameters. j,w (t), based on the first wind speed and the second power generation mentioned above, a third objective formula is constructed:

[0051]

[0052] Among them, Q j,w (t) represents the available output of WPP unit j at time t, i.e., the second power generation capacity mentioned above, g r For rated output power, v in vout These are the inlet and outlet wind velocities of the WPP unit, respectively. r This is the rated wind speed.

[0053] It is understandable that when the wind speed is within the unit's tolerance range, the unit's power increases with the increase of wind speed. However, if it exceeds the tolerance range, that is, if the wind speed is too low or too high, the wind turbine will not be turned on in order to avoid damage to the machine.

[0054] Step S2023: Determine the second input power, target area, and third power generation based on the above power plant operating parameters. Construct a fourth target formula based on the second input power, target area, and third power generation. The second input power is the solar input power of the PV unit, the target area is the total area of ​​the photovoltaic modules of the PV unit, and the third power generation is the power generation of the PV unit. The third target formula is used to simulate the trend of the third power generation as the second input power changes.

[0055] Specifically, the second input power θ is determined based on the aforementioned power plant operating parameters. t Target area S pv and the third power generation g m,pv (t), based on the second input power, the target area, and the third power generation, a fourth target formula is constructed:

[0056] g m,pv (t)=η PV ×S PV ×θ t ;

[0057] Where, η PV The efficiency of photovoltaic power generation is determined by historical operating parameters.

[0058] Step S2024: Determine the first input and the first output based on the power plant operating parameters, and construct a fifth target formula based on the first input and the first output. The first input is the electrical energy input of the electrical conversion device, and the first output is the natural gas output of the electrical conversion device. The fifth target formula is used to simulate the changing trend of the first output with the first input.

[0059] Specifically, the first input quantity is determined based on the aforementioned power plant operating parameters. and the first output quantity P pg,gas Based on the first input and the first output mentioned above, the fifth objective formula is constructed as follows:

[0060]

[0061] Wherein, γ is the electrical conversion efficiency of the electrical conversion equipment, which is determined by historical operating parameters.

[0062] Understandably, the electro-gas technology achieves the transfer of energy from electricity to gas through water electrolysis and methanation processes. When combined with gas storage tanks, the gas storage capacity efficiency is improved.

[0063] Step S2025: Determine the second input and the second output based on the above power plant operating parameters, and construct a sixth target formula based on the second input and the second output. The second input is the natural gas input of the gas boiler, and the second output is the heat output of the gas boiler. The sixth target formula is used to simulate the changing trend of the second output with the second input.

[0064] Specifically, the second input quantity is determined based on the aforementioned power plant operating parameters. Second output Based on the second input and the second output mentioned above, construct the sixth objective formula:

[0065]

[0066] in, η represents the heat output of the gas-fired boiler at time t. h For the conversion efficiency of natural gas and heat, L gas This refers to the calorific value of natural gas.

[0067] Step S2026: Determine the third input power, the first output power, and the capacity based on the above power plant operating parameters. Construct a seventh target formula based on the third input power, the first output power, and the capacity. The third input power is the charging power of the energy storage device, the first output power is the discharging power of the energy storage device, and the capacity is the stored capacity of the energy storage device. The seventh target formula is used to simulate the changing trend of the capacity with the third input power and the first output power.

[0068] Specifically, the third input power P is determined based on the aforementioned power plant operating parameters. chr First output power P disc and capacitance ES t Based on the aforementioned third input power, first output power, and capacitance, a seventh objective formula is constructed:

[0069]

[0070] Among them, ES t+1 and ES t δ represents the capacitance at times t+1 and t, respectively. chr and δ discThese are the charging and discharging efficiencies of the energy storage device, determined by historical operating parameters, P. chr and P disc Δt represents the charging and discharging power of the energy storage device, respectively, and Δt is the time interval between t+1 and t.

[0071] Understandably, P chr *P disc =0, meaning that when one term is a non-zero positive number, the other term must be 0, in order to restrict the energy storage device from charging and discharging simultaneously.

[0072] Step S2027: Determine the fourth input power, the second output power, and the heat capacity based on the above power plant operating parameters. Construct an eighth target formula based on the above fourth input power, the above second output power, and the above heat capacity. The above fourth input power is the thermal energy input power of the above thermal storage tank, the above second output power is the thermal energy output power of the above thermal storage tank, and the above heat capacity is the stored thermal energy of the above thermal storage tank. The above eighth target formula is used to simulate the change trend of the above heat capacity with the above fourth input power and the above second output power.

[0073] Specifically, the fourth input power h is determined based on the aforementioned power plant operating parameters. hi Second output power h ho and heat capacity HS t Based on the aforementioned fourth input power, second output power, and heat capacity, the eighth objective formula is constructed as follows:

[0074]

[0075] Among them, HS t+1 and HS t δ represents the heat capacity of the thermal storage tank at times t+1 and t, respectively. hi and δ ho These are the filling and discharging efficiencies of the thermal storage tank, determined based on historical operating parameters.

[0076] Step S2028: Determine the third input, third output, fourth output, and gas storage capacity based on the above power plant operating parameters. Construct a ninth target formula based on the above third input, third output, fourth output, and gas storage capacity. The third input is the natural gas input to the gas storage tank. The third output is the natural gas output from the gas storage tank to the gas boiler. The fourth output is the natural gas output from the gas storage tank to the CHP unit.

[0077] Specifically, the third input quantity is determined based on the aforementioned power plant operating parameters. Third output Fourth output Wagi reserves Q GST,tBased on the aforementioned third input, third output, fourth output, and gas storage, a ninth objective formula is constructed:

[0078]

[0079] Among them, Q GST,T0 This represents the initial gas storage capacity of the gas storage tank.

[0080] Understandable, That is, when one term is a non-zero positive number, the other term must be 0, which is used to restrict the gas storage tank from performing gas storage and gas release operations at the same time.

[0081] Step S2029: Combine the above-mentioned first objective formula, second objective formula, third objective formula, fourth objective formula, fifth objective formula, sixth objective formula, seventh objective formula, eighth objective formula and ninth objective formula to obtain the above-mentioned power plant simulation model.

[0082] Specifically, by combining the above-mentioned first objective formula, second objective formula, third objective formula, fourth objective formula, fifth objective formula, sixth objective formula, seventh objective formula, eighth objective formula, and ninth objective formula, the above-mentioned power plant simulation model is obtained by simulating the operation of the virtual power plant through a numerical model.

[0083] To construct the aforementioned power plant cost model, in one optional implementation, step S203 includes:

[0084] Step S2031: Determine the first coefficient, second coefficient, third coefficient, first variable, and first start-up cost based on the above power plant cost parameters; construct the tenth target formula based on the first coefficient, second coefficient, third coefficient, and first power generation; construct the eleventh target formula based on the first variable and first start-up cost; the first coefficient, second coefficient, and third coefficient are the energy consumption coefficients of the CHP unit; the tenth target formula is used to simulate the trend of the fuel cost of the CHP unit changing with the first power generation; the first variable is a binary variable indicating whether the CHP unit generates electricity; the first start-up cost is the start-up cost of the CHP unit; and the eleventh target formula is used to simulate the trend of the start-up and shutdown costs of the CHP unit changing with the first variable.

[0085] Specifically, the first coefficient a is determined based on the aforementioned power plant cost parameters. CHP Second coefficient b CHP The third coefficient c CHP The first variable u CHP,t and the first startup cost D CHP,tBased on the aforementioned first coefficient, second coefficient, third coefficient, and first power generation, a tenth target formula is constructed; based on the aforementioned first variable and first start-up cost, an eleventh target formula is constructed.

[0086]

[0087] in, For fuel costs, For start-stop costs, u CHP,t It is a 0 / 1 variable, where 1 indicates that the CHP unit is in operation and 0 indicates that the CHP unit is in shutdown.

[0088] Step S2032: Determine the first operating cost and the first depreciation cost based on the above power plant cost parameters. Construct a twelfth target formula based on the first operating cost, the first depreciation cost, and the second power generation. The first operating cost is the unit power generation cost of the WPP unit, the first depreciation cost is the loss cost of the WPP unit, and the twelfth target formula is used to simulate the trend of the total cost of the WPP unit changing with the second power generation.

[0089] Specifically, the first operating cost is determined based on the aforementioned power plant cost parameters. and first depreciation cost Based on the aforementioned first operating cost, first depreciation cost, and second power generation capacity, the twelfth target formula is constructed as follows:

[0090]

[0091] in, p wpp This represents the unit cost of power generation for WPP units.

[0092] Step S2033: Determine the second operating cost and the second depreciation cost based on the above power plant cost parameters. Construct a thirteenth target formula based on the above second operating cost, the above second depreciation cost and the above third power generation. The above second operating cost is the unit power generation cost of the above PV unit, the above second depreciation cost is the loss cost of the above PV unit, and the above thirteenth target formula is used to simulate the trend of the total cost of the above PV unit changing with the above third power generation.

[0093] Specifically, the second operating cost is determined based on the aforementioned power plant cost parameters. Second depreciation cost Based on the aforementioned second operating cost, second depreciation cost, and third power generation capacity, the thirteenth target formula is constructed as follows:

[0094]

[0095] in, p pv This represents the unit cost of electricity generation for PV units.

[0096] Step S2034: Determine the third depreciation cost based on the above power plant cost parameters, and construct the fourteenth target formula based on the above second operating cost, the above first input quantity and the above third depreciation cost. The above third depreciation cost is the loss cost of the above electrical conversion device. The above fourteenth target formula is used to simulate the trend of the total cost of the above electrical conversion device changing with the above first input quantity.

[0097] Specifically, the third depreciation cost is determined based on the aforementioned power plant cost parameters. Based on the aforementioned second operating cost, the aforementioned first input quantity, and the aforementioned third depreciation cost, construct the fourteenth objective formula:

[0098]

[0099] Understandably, the operating cost of power-to-gas (P2G) equipment mainly considers the electricity cost and the operating cost of raw material conversion, taking into account the electricity consumption. The main source is curtailed wind power, the cost of which is included in the cost of wind power.

[0100] Step S2035: Determine the third operating cost based on the power plant cost parameters mentioned above, and construct the fifteenth target formula based on the third operating cost and the second input quantity mentioned above. The third operating cost is the real-time electricity price of natural gas, and the fifteenth target formula is used to simulate the trend of the total cost of the gas boiler changing with the second input quantity mentioned above.

[0101] Specifically, the third operating cost is determined based on the aforementioned power plant cost parameters. Based on the third operating cost and the second input mentioned above, construct the fifteenth objective formula:

[0102]

[0103] Among them, C GB This represents the total cost of the gas-fired boiler.

[0104] Step S2036: Combine the above tenth objective formula, the above eleventh objective formula, the above twelfth objective formula, the above thirteenth objective formula, the above fourteenth objective formula, and the above fifteenth objective formula to obtain the above power plant cost model.

[0105] Specifically, by combining the above tenth objective formula, the above eleventh objective formula, the above twelfth objective formula, the above thirteenth objective formula, the above fourteenth objective formula, and the above fifteenth objective formula, and using the output parameters of each component of the above power plant simulation model as the input parameters of each component in the power plant cost model, the relationship between the two models is constructed, and the above power plant cost model is obtained.

[0106] To establish the correlation between the aforementioned power plant cost model and the aforementioned power plant simulation model, in an optional implementation, step S2036 includes:

[0107] Step S20361: Determine the fourth depreciation cost based on the above power plant cost parameters. The fourth depreciation cost includes the fifth depreciation cost, the sixth depreciation cost, and the seventh depreciation cost. The fifth depreciation cost is the loss cost of the above-mentioned energy storage device, the sixth depreciation cost is the loss cost of the above-mentioned gas storage tank, and the seventh depreciation cost is the loss cost of the above-mentioned thermal storage tank.

[0108] Specifically, the fourth depreciation cost C is determined based on the aforementioned power plant cost parameters. sv The aforementioned fourth depreciation cost includes the fifth depreciation cost C. ES Sixth, depreciation cost C GST And the seventh depreciation cost C HT .

[0109] Step S20362: The first power generation, the first variable, the second power generation, the third power generation, the first input quantity, and the second input quantity are determined as the input parameters of the power plant cost model.

[0110] Step S20363: The sum of the calculation results of the tenth objective formula, the eleventh objective formula, the twelfth objective formula, the thirteenth objective formula, the fourteenth objective formula, and the fifteenth objective formula, and the sum of the fourth depreciation cost are determined as the output parameters of the power plant cost model, thus obtaining the power plant cost model.

[0111] Specifically, if we set the output parameter of the above power plant cost model as K, then based on the above derivation process, we have:

[0112] To determine the net profit of the aforementioned virtual power plant, in one optional implementation, before solving for the operating parameters of the power plant simulation model to obtain the power plant control parameters using the maximum net profit of the aforementioned power plant cost model as the objective function, the method further includes:

[0113] Step S301: Construct a power plant revenue model based on the above power plant simulation model. The power plant revenue model is used to simulate the trend of the revenue of the virtual power plant changing with the operating parameters of the above power plant simulation model.

[0114] Specifically, let the revenue of the aforementioned virtual power plant be B, then the revenue model for the power plant is B = r CHP +r wpv +r GB .

[0115] To construct the aforementioned power plant revenue model, in one optional implementation, step S301 includes:

[0116] Step S3011: Obtain the first unit price and the second unit price, wherein the first unit price is the electricity sales unit price of the virtual power plant and the second unit price is the heat sales unit price of the virtual power plant.

[0117] Specifically, obtain the first unit price Second unit price

[0118] Step S3012: Construct a sixteenth target formula based on the first unit price, the second unit price, the first power generation, and the first heat generation. The sixteenth target formula is used to simulate the revenue trend of the CHP unit as a function of the first power generation and the first heat generation.

[0119] Specifically, based on the aforementioned first unit price, second unit price, first power generation capacity, and first heat generation capacity, the sixteenth target formula is constructed as follows:

[0120]

[0121] Where t represents the t-th time period of a day.

[0122] Step S3013: Construct a seventeenth target formula based on the first unit price, the second power generation and the third power generation. The seventeenth target formula is used to simulate the total revenue of the WPP unit and the PV unit as the second power generation and the third power generation change.

[0123] Specifically, the seventeenth target formula is constructed based on the aforementioned first unit price, the aforementioned second power generation capacity, and the aforementioned third power generation capacity:

[0124]

[0125] Step S3014: Construct an eighteenth target formula based on the second unit price and the second output quantity. The eighteenth target formula is used to simulate the change trend of the revenue of the gas boiler with the second output quantity.

[0126] Specifically, the eighteenth objective formula is constructed based on the second unit price and the second output quantity mentioned above:

[0127]

[0128] Step S3015: Combine the above sixteenth objective formula, seventeenth objective formula and eighteenth objective formula to obtain the above power plant revenue model.

[0129] Specifically, by combining the sixteenth, seventeenth, and eighteenth objective formulas mentioned above, the relationship between the power plant simulation model and the power plant revenue model is established, thus obtaining the power plant revenue model.

[0130] To construct the aforementioned target constraint set, in one optional implementation, step S204 includes:

[0131] Step S2041: Construct the power balance constraints of the virtual power plant corresponding to the above power plant simulation model to obtain the first objective constraint;

[0132] Specifically, the power balance constraints of the virtual power plant corresponding to the above power plant simulation model are constructed as follows:

[0133]

[0134] Among them, Q i,Th Q represents the active power output of CHP unit i. j,WPP Q represents the active power processing of WPP unit j. m,pv This represents the active power output of PV unit m, and D represents the load demand of the power system.

[0135] Step S2042: Construct the output constraints of the CHP units of the virtual power plant corresponding to the above power plant simulation model to obtain the second objective constraint;

[0136] Specifically, the output constraints of the CHP units in the virtual power plant corresponding to the above power plant simulation model are constructed as follows:

[0137]

[0138] in, This indicates the maximum dispatchable output of the CHP unit; This indicates the minimum dispatchable output of the CHP unit.

[0139] Step S2043: Construct the output constraints of the WPP units of the virtual power plant corresponding to the above power plant simulation model to obtain the third objective constraint;

[0140] Specifically, the output constraints of the WPP units in the virtual power plant corresponding to the above power plant simulation model are constructed as follows:

[0141]

[0142] in, This represents the maximum dispatchable output of WPP unit j. This represents the minimum dispatchable output of WPP unit j.

[0143] Step S2044: Construct the PV unit output constraints of the virtual power plant corresponding to the above power plant simulation model to obtain the fourth objective constraint;

[0144] Specifically, the output constraints of the PV units in the virtual power plant corresponding to the above power plant simulation model are constructed as follows:

[0145]

[0146] in, This represents the maximum dispatchable output of PV unit m; This represents the minimum dispatchable output of PV unit m.

[0147] Step S2045: Construct the power constraints of the CHP units of the virtual power plant corresponding to the above power plant simulation model to obtain the fifth objective constraint;

[0148] Specifically, the power constraints of the CHP units in the virtual power plant corresponding to the above power plant simulation model are constructed as follows:

[0149]

[0150] in, and P represents the lower and upper limits of the natural gas input power for the CHP unit. CHP,down and P CHP,up These are the lower and upper limits of the ramp-up power for the CHP unit. and These are the lower and upper limits of the electrical-to-heat ratio for CHP units.

[0151] Step S2046: Construct the above-mentioned reserve capacity constraints of the above-mentioned virtual power plant corresponding to the above-mentioned power plant simulation model to obtain the sixth objective constraint;

[0152] Specifically, the aforementioned reserve capacity constraints of the virtual power plant corresponding to the aforementioned power plant simulation model are constructed as follows:

[0153]

[0154] Where D(t) is the system load demand at time t, R(t) is the system reserve demand at time t, l is the system line loss rate, θ is the unit self-consumption rate, and Q... max (t) represents the sum of the maximum unit output at time t.

[0155] Step S2047: Combine the above-mentioned first objective constraint, second objective constraint, third objective constraint, fourth objective constraint, fifth objective constraint and sixth objective constraint to obtain the above-mentioned objective constraint group.

[0156] Specifically, the above-mentioned first objective constraint, second objective constraint, third objective constraint, fourth objective constraint, fifth objective constraint and sixth objective constraint are combined to obtain the above-mentioned objective constraint group.

[0157] In addition, this application also sets constraints on the operation of the energy storage device:

[0158]

[0159] in, and These are the minimum and maximum charging power values ​​for the energy storage device, respectively. and These represent the minimum and maximum discharge power of the energy storage device; ES min and ES max These represent the lower and upper limits of the capacity of electric energy storage devices, respectively.

[0160] Constraints are imposed on the operation of thermal storage tanks:

[0161]

[0162] in, and These are the minimum and maximum values ​​of the thermal storage tank's storage power, respectively. and For the minimum and maximum heat dissipation power of the thermal storage tank; HS min and HS max These are the lower and upper limits of the thermal storage tank capacity, respectively.

[0163] Constraints are imposed on the operation of the gas storage tank:

[0164]

[0165] in,

[0166] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0167] This application also provides a scheduling device for an energy-coupled virtual power plant based on multiple energy storage devices. It should be noted that this scheduling device can be used to execute the scheduling method for an energy-coupled virtual power plant based on multiple energy storage devices provided in this application. This device is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0168] The following describes the scheduling device for an energy-coupled virtual power plant based on multiple energy storage devices provided in the embodiments of this application.

[0169] Figure 3 This is a structural block diagram of a dispatching device for an energy-coupled virtual power plant based on multiple energy storage devices, according to an embodiment of this application. Figure 3 As shown, the device includes:

[0170] Acquisition unit 10 is used to acquire historical operating parameters, including power plant operating parameters and power plant cost parameters. The power plant operating parameters include the operating parameters of each component of the virtual power plant, and the power plant cost parameters include the operating costs of each component of the virtual power plant. The components include at least WPP units, PV units, CHP units, gas boilers, thermal storage tanks, gas storage tanks, energy storage devices, and electrical conversion devices. The PV units convert solar energy into electrical energy to supply the electrical load, and the WPP units convert wind energy into electrical energy to supply the electrical load. The aforementioned electrical conversion device and energy storage device, the aforementioned CHP unit converts natural gas into electrical energy to supply the aforementioned energy storage device and the aforementioned electrical load, and the generated heat supplies the heat load, the aforementioned gas boiler converts natural gas into heat energy to supply the aforementioned heat load and the heat storage tank, the aforementioned heat storage tank is used to store heat energy and supply the aforementioned heat load, the aforementioned electrical conversion device is used to receive electrical energy, perform electrical conversion to generate natural gas and supply the aforementioned gas storage tank, the aforementioned gas storage tank is used to store natural gas and supply the aforementioned CHP unit and the aforementioned gas boiler, the aforementioned energy storage device is used to store electrical energy and supply the aforementioned electrical conversion device;

[0171] Specifically, in actual production, virtual power plants introduce carbon capture devices in addition to power operation, consider the flow of two types of energy, and utilize by-products to improve overall economic benefits. Therefore, in order to solve the problem that the revenue growth of the planning and dispatching strategy is lower than expected due to the fact that the existing virtual power plant dispatching method does not consider the equipment required for multi-energy integration and the related impact of carbon capture devices, this application proposes to first determine the structure of the virtual power plant, including generating units, energy storage devices, and flexible components.

[0172] In one embodiment, the aforementioned units include WPP units (wind turbines), PV units (photovoltaic turbines), and CHP units (cogeneration units). The aforementioned energy storage devices include thermal storage tanks, gas storage tanks, and electrical energy storage devices. The aforementioned flexibility components include power conversion devices and gas-fired boilers. Wind power, photovoltaic, and cogeneration units generate electricity as power sources. The electrical energy storage devices can store excess electricity and release it during peak load periods. Waste heat from the cogeneration units and heat generated by the gas-fired boilers can supply the heat load or be stored in thermal storage tanks. Furthermore, the cogeneration units and gas-fired boilers are driven by natural gas. Power-to-gas (P2G) equipment can catalytically produce methane from carbon dioxide. The generated methane can be supplied to the cogeneration units and gas turbines or stored in gas storage tanks, with its flow determined by the operating power of the cogeneration units and gas-fired boilers.

[0173] In addition, based on the operating characteristics of each of the above components, their costs are determined, including the operating costs of power sources and heat sources, the operating conditions of various energy storage devices, and the operating costs of electric-to-gas generator units.

[0174] The first building unit 20 is used to build a power plant simulation model based on the above power plant operating parameters. The power plant simulation model is used to simulate the energy flow between the above-mentioned components.

[0175] Specifically, based on the operating parameters of each component in the above historical operating parameters, the operating status of each component is simulated to obtain the above power plant simulation model.

[0176] The second building unit 30 is used to build a power plant cost model based on the power plant simulation model and the power plant cost parameters. The power plant cost model is used to simulate the cost trend of the virtual power plant as the operating parameters of the power plant simulation model change.

[0177] Specifically, based on the relationship between the operating characteristics and operating costs of each of the above-mentioned components, a power plant cost model is constructed on the basis of the power plant simulation model, and the power plant simulation model and the power plant cost model are interconnected.

[0178] The third building unit 40 is used to build a target constraint group. The target constraint group is used to limit the range of values ​​of the operating parameters of the power plant simulation model. The target constraint group includes at least power balance constraints, CHP unit output constraints, WPP unit output constraints, PV unit output constraints, CHP unit power constraints, and reserve capacity constraints.

[0179] Specifically, to prevent the control results from not conforming to actual operation or damaging the components of the virtual power plant, this application sets the aforementioned target constraint group to limit the range of values ​​of the operating parameters of the power plant simulation model during the solution process, thereby ensuring the feasibility of the obtained scheduling strategy.

[0180] The calculation unit 50 is used to solve the operating parameters of the power plant simulation model under the constraints of the above-mentioned target constraint group, with the objective function of maximizing the net profit of the above-mentioned virtual power plant, to obtain the power plant control parameters, and to control the operation of the above-mentioned virtual power plant according to the above-mentioned power plant control parameters.

[0181] Specifically, under constraints, the operating parameters of the above-mentioned power plant simulation model are solved to obtain the power plant control parameters, with the objective function being to maximize the net profit of the virtual power plant. The operation of the virtual power plant is then controlled according to the above-mentioned power plant control parameters so that the virtual power plant can obtain the maximum profit.

[0182] In this embodiment, the acquisition unit acquires historical operating parameters, including power plant operating parameters and power plant cost parameters. The power plant operating parameters include the operating parameters of each component of the virtual power plant, and the power plant cost parameters include the operating costs of each component of the virtual power plant. The components include at least a WPP unit, a PV unit, a CHP unit, a gas boiler, a thermal storage tank, a gas storage tank, an electric energy storage device, and an electrical conversion device. The PV unit converts solar energy into electrical energy to supply the electrical load. The WPP unit converts wind energy into electrical energy to supply the electrical load, the electrical conversion device, and the electric energy storage device. The CHP unit converts natural gas into electrical energy to supply the electric energy storage device and the electrical load, and the generated heat supplies the heat load. The gas boiler converts natural gas into heat energy to supply the heat load and the thermal storage tank. The thermal storage tank stores heat energy and supplies the heat load. The electrical conversion device receives electrical energy, performs electrical conversion to generate natural gas, and supplies it to the gas storage tank. The gas storage tank stores natural gas and supplies it to the CHP unit. The generating unit and the aforementioned gas-fired boiler, along with the aforementioned electric energy storage device, are used to store electrical energy and supply it to the aforementioned electrical conversion device. A first construction unit constructs a power plant simulation model based on the aforementioned power plant operating parameters. This simulation model is used to simulate the energy flow between the aforementioned components. A second construction unit constructs a power plant cost model based on the aforementioned power plant simulation model and the aforementioned power plant cost parameters. This cost model is used to simulate the cost trend of the virtual power plant as a function of the operating parameters of the aforementioned power plant simulation model. A third construction unit constructs a set of target constraints. This set of target constraints is used to limit the range of values ​​for the operating parameters of the aforementioned power plant simulation model. The set of target constraints includes at least power balance constraints, CHP unit output constraints, WPP unit output constraints, PV unit output constraints, CHP unit power constraints, and reserve capacity constraints. Under the constraints of the aforementioned target constraint set, the calculation unit uses the maximum net profit of the aforementioned virtual power plant as the objective function to solve for the operating parameters of the aforementioned power plant simulation model to obtain the power plant control parameters. The virtual power plant is then controlled according to these power plant control parameters. This application performs physical simulation modeling on WPP units, PV units, CHP units, gas-fired boilers, thermal storage tanks, gas storage tanks, electric energy storage devices, and electrical conversion devices, constructing corresponding models and establishing energy flow relationships between each model to obtain the aforementioned power plant simulation models. Based on the operating parameters of the power plant simulation models, a correlation between operating parameters and costs is constructed to obtain a power plant cost model. Then, under constraints, a solution is performed with net profit maximization as the objective function to obtain a control strategy, and the virtual power plant is scheduled based on the control strategy. This method solves the problem in existing technologies where planning virtual power plants based on electricity as a link does not meet the actual operating conditions of current multi-energy coupling, leading to deviations in the benefits of scheduling strategies.

[0183] The aforementioned scheduling device for an energy-coupled virtual power plant based on multiple energy storage devices includes a processor and a memory. The acquisition unit, first construction unit, second construction unit, third construction unit, and calculation unit are all stored as program units in the memory. The processor executes these program units stored in the memory to achieve the corresponding functions. All of the above modules reside in the same processor; alternatively, the modules may be located in different processors in any combination.

[0184] The processor contains a kernel, which retrieves the corresponding program units from memory. One or more kernels can be configured, and adjusting kernel parameters can improve the net profitability of the virtual power plant.

[0185] The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0186] This invention provides a computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device containing the computer-readable storage medium to perform the scheduling method of the energy coupling virtual power plant based on multiple energy storage devices.

[0187] This invention provides a processor for running a program, wherein the program executes the scheduling method for an energy-coupled virtual power plant based on multiple energy storage devices.

[0188] This invention provides a virtual power plant scheduling system, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements at least the steps of a scheduling method for an energy-coupled virtual power plant based on multiple energy storage devices.

[0189] This application also provides a computer program product that, when executed on a data processing device, is adapted to perform the steps of initializing a scheduling method for an energy-coupled virtual power plant based on at least multiple energy storage devices.

[0190] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those described herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0191] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied 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.

[0192] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0193] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0194] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0195] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0196] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0197] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0198] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0199] As can be seen from the above description, the embodiments of this application achieve the following technical effects:

[0200] 1) The scheduling method of the energy-coupled virtual power plant based on multiple energy storage devices in this application firstly acquires historical operating parameters, including power plant operating parameters and power plant cost parameters. The power plant operating parameters include the operating parameters of each component of the virtual power plant, and the power plant cost parameters include the operating costs of each component of the virtual power plant. The components include at least a WPP unit, a PV unit, a CHP unit, a gas boiler, a thermal storage tank, a gas storage tank, an electric energy storage device, and an electrical conversion device. The PV unit converts solar energy into electrical energy to supply the electrical load. The WPP unit converts wind energy into electrical energy to supply the electrical load, the electrical conversion device, and the electric energy storage device. The CHP unit converts natural gas into electrical energy to supply the electric energy storage device and the electrical load, and the generated heat supplies the heat load. The gas boiler converts natural gas into heat energy to supply the heat load and the thermal storage tank. The thermal storage tank is used to store heat energy and supply the heat load. The electrical conversion device is used to receive electrical energy, perform electrical conversion to generate natural gas, and supply the gas storage tank. The above-mentioned energy storage device is used to store natural gas and supply it to the aforementioned CHP unit and gas-fired boiler. The above-mentioned energy storage device is used to store electrical energy and supply it to the aforementioned electrical conversion device. Then, a power plant simulation model is constructed based on the aforementioned power plant operating parameters. This simulation model is used to simulate the energy flow between the aforementioned components. Next, a power plant cost model is constructed based on the aforementioned power plant simulation model and the aforementioned power plant cost parameters. This cost model is used to simulate the cost trend of the virtual power plant as a function of the operating parameters of the aforementioned power plant simulation model. Then, a set of target constraints is constructed to limit the range of values ​​for the operating parameters of the aforementioned power plant simulation model. This set of target constraints includes at least power balance constraints, CHP unit output constraints, WPP unit output constraints, PV unit output constraints, CHP unit power constraints, and reserve capacity constraints. Finally, under the constraints of the aforementioned target constraint set, the operating parameters of the aforementioned power plant simulation model are solved to obtain the power plant control parameters, with the objective function being the maximum net profit of the aforementioned virtual power plant. The operation of the virtual power plant is then controlled according to these power plant control parameters. This application performs physical simulation modeling on WPP units, PV units, CHP units, gas-fired boilers, thermal storage tanks, gas storage tanks, electric energy storage devices, and electrical conversion devices, constructing corresponding models and establishing energy flow relationships between each model to obtain the aforementioned power plant simulation models. Based on the operating parameters of the power plant simulation models, a correlation between operating parameters and costs is constructed to obtain a power plant cost model. Then, under constraints, a solution is performed with net profit maximization as the objective function to obtain a control strategy, and the virtual power plant is scheduled based on the control strategy. This method solves the problem in existing technologies where planning virtual power plants based on electricity as a link does not meet the actual operating conditions of current multi-energy coupling, leading to deviations in the benefits of scheduling strategies.

[0201] 2) The dispatching device for an energy-coupled virtual power plant based on multiple energy storage devices in this application acquires historical operating parameters, including power plant operating parameters and power plant cost parameters. The power plant operating parameters include the operating parameters of each component of the virtual power plant, and the power plant cost parameters include the operating costs of each component of the virtual power plant. The components include at least a WPP unit, a PV unit, a CHP unit, a gas boiler, a thermal storage tank, a gas storage tank, an electric energy storage device, and an electrical conversion device. The PV unit converts solar energy into electrical energy to supply the electrical load. The WPP unit converts wind energy into electrical energy to supply the electrical load, the electrical conversion device, and the electric energy storage device. The CHP unit converts natural gas into electrical energy to supply the electric energy storage device and the electrical load, and the generated heat supplies the heat load. The gas boiler converts natural gas into heat energy to supply the heat load and the thermal storage tank. The thermal storage tank stores heat energy and supplies the heat load. The electrical conversion device receives electrical energy, performs electrical conversion to generate natural gas, and supplies it to the gas storage tank. The gas storage tank stores natural gas. Natural gas is supplied to the aforementioned CHP generating units and gas-fired boilers. The aforementioned electric energy storage device is used to store electrical energy and supply it to the aforementioned electrical conversion device. The first construction unit constructs a power plant simulation model based on the aforementioned power plant operating parameters. The power plant simulation model is used to simulate the energy flow between the aforementioned components. The second construction unit constructs a power plant cost model based on the aforementioned power plant simulation model and the aforementioned power plant cost parameters. The power plant cost model is used to simulate the cost trend of the aforementioned virtual power plant as a function of the operating parameters of the aforementioned power plant simulation model. The third construction unit constructs a target constraint group. The target constraint group is used to limit the range of values ​​of the operating parameters of the aforementioned power plant simulation model. The target constraint group includes at least power balance constraints, CHP generating unit output constraints, WPP generating unit output constraints, PV generating unit output constraints, CHP generating unit power constraints, and reserve capacity constraints. Under the constraints of the aforementioned target constraint group, the calculation unit uses the maximum net profit of the aforementioned virtual power plant as the objective function to solve the operating parameters of the aforementioned power plant simulation model to obtain the power plant control parameters. The virtual power plant is then controlled to operate based on the aforementioned power plant control parameters. This application performs physical simulation modeling on WPP units, PV units, CHP units, gas-fired boilers, thermal storage tanks, gas storage tanks, electric energy storage devices, and electrical conversion devices, constructing corresponding models and establishing energy flow relationships between each model to obtain the aforementioned power plant simulation models. Based on the operating parameters of the power plant simulation models, a correlation between operating parameters and costs is constructed to obtain a power plant cost model. Then, under constraints, a solution is performed with net profit maximization as the objective function to obtain a control strategy, and the virtual power plant is scheduled based on the control strategy. This method solves the problem in existing technologies where planning virtual power plants based on electricity as a link does not meet the actual operating conditions of current multi-energy coupling, leading to deviations in the benefits of scheduling strategies.

[0202] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A scheduling method for an energy-coupled virtual power plant based on multiple energy storage devices, characterized in that, include: Historical operating parameters are obtained, including power plant operating parameters and power plant cost parameters. The power plant operating parameters include the operating parameters of each component of the virtual power plant, and the power plant cost parameters include the operating costs of each component of the virtual power plant. Each component includes at least a WPP unit, a PV unit, a CHP unit, a gas-fired boiler, a thermal storage tank, a gas storage tank, an electric energy storage device, and an electrical conversion device. The PV unit converts solar energy into electrical energy to supply the electrical load, the WPP unit converts wind energy into electrical energy to supply the electrical load, and the electrical conversion device... The system includes a power conversion device and an electric energy storage device. The CHP unit converts natural gas into electrical energy to supply the electric energy storage device and the electrical load, and the generated heat supplies the thermal load. The gas boiler converts natural gas into thermal energy to supply the thermal load and the thermal storage tank. The thermal storage tank is used to store thermal energy and supply the thermal load. The power conversion device receives electrical energy, performs electrical conversion to generate natural gas, and supplies it to the gas storage tank. The gas storage tank is used to store natural gas and supply it to the CHP unit and the gas boiler. The electric energy storage device is used to store electrical energy and supply it to the power conversion device. A power plant simulation model is constructed based on the power plant operating parameters, and the power plant simulation model is used to simulate the energy flow between the various component elements. A power plant cost model is constructed based on the power plant simulation model and the power plant cost parameters. The power plant cost model is used to simulate the cost trend of the virtual power plant as the operating parameters of the power plant simulation model change. Construct a target constraint group, which is used to limit the range of values ​​of the operating parameters of the power plant simulation model. The target constraint group includes at least power balance constraints, CHP unit output constraints, WPP unit output constraints, PV unit output constraints, CHP unit power constraints, and reserve capacity constraints. Under the constraints of the target set, with the maximum net profit of the virtual power plant as the objective function, the operating parameters of the power plant simulation model are solved to obtain the power plant control parameters, and the operation of the virtual power plant is controlled according to the power plant control parameters.

2. The method according to claim 1, characterized in that, A power plant simulation model is constructed based on the power plant's operating parameters, including: The first input power, the first power generation, and the first heat production power are determined based on the power plant operating parameters. A first target formula is constructed based on the first input power and the first power generation, and a second target formula is constructed based on the first input power and the first heat production power. The first input power is the gas input power of the CHP unit, the first power generation is the power generation of the CHP unit, and the first heat production power is the heat production power of the CHP unit. The first target formula is used to simulate the changing trend of the first power generation with the first input power, and the second target formula is used to simulate the changing trend of the first heat production power with the first input power. The first wind speed and the second power generation are determined based on the power plant operating parameters. A third target formula is constructed based on the first wind speed and the second power generation. The first wind speed is the input wind speed of the WPP unit, and the second power generation is the power generation of the WPP unit. The third target formula is used to simulate the changing trend of the second power generation with the first wind speed. The second input power, target area, and third power generation are determined based on the power plant operating parameters. A fourth target formula is constructed based on the second input power, the target area, and the third power generation. The second input power is the solar input power of the PV unit, the target area is the total area of ​​the photovoltaic modules of the PV unit, and the third power generation is the power generation of the PV unit. The third target formula is used to simulate the trend of the third power generation as the second input power changes. The first input and the first output are determined based on the power plant operating parameters. A fifth target formula is constructed based on the first input and the first output. The first input is the electrical energy input of the electrical conversion device, and the first output is the natural gas output of the electrical conversion device. The fifth target formula is used to simulate the changing trend of the first output with the first input. The second input and the second output are determined based on the power plant operating parameters. A sixth target formula is constructed based on the second input and the second output. The second input is the natural gas input of the gas boiler, and the second output is the heat output of the gas boiler. The sixth target formula is used to simulate the changing trend of the second output with the second input. The third input power, the first output power, and the capacity are determined based on the power plant operating parameters. A seventh target formula is constructed based on the third input power, the first output power, and the capacity. The third input power is the charging power of the energy storage device, the first output power is the discharging power of the energy storage device, and the capacity is the stored capacity of the energy storage device. The seventh target formula is used to simulate the changing trend of the capacity with the third input power and the first output power. The fourth input power, the second output power, and the heat capacity are determined based on the power plant operating parameters. An eighth target formula is constructed based on the fourth input power, the second output power, and the heat capacity. The fourth input power is the thermal energy input power of the thermal storage tank, the second output power is the thermal energy output power of the thermal storage tank, and the heat capacity is the stored thermal energy of the thermal storage tank. The eighth target formula is used to simulate the changing trend of the heat capacity with the fourth input power and the second output power. The third input, third output, fourth output, and gas storage are determined based on the power plant operating parameters. A ninth target formula is constructed based on the third input, third output, fourth output, and gas storage. The third input is the natural gas input to the gas storage tank, the third output is the natural gas output from the gas storage tank to the gas boiler, and the fourth output is the natural gas output from the gas storage tank to the CHP unit. The power plant simulation model is obtained by combining the first objective formula, the second objective formula, the third objective formula, the fourth objective formula, the fifth objective formula, the sixth objective formula, the seventh objective formula, the eighth objective formula, and the ninth objective formula.

3. The method according to claim 2, characterized in that, A power plant cost model is constructed based on the power plant simulation model and the power plant cost parameters, including: Based on the power plant cost parameters, a first coefficient, a second coefficient, a third coefficient, a first variable, and a first start-up cost are determined. A tenth target formula is constructed based on the first coefficient, the second coefficient, the third coefficient, and the first power generation. An eleventh target formula is constructed based on the first variable and the first start-up cost. The first coefficient, the second coefficient, and the third coefficient are the energy consumption coefficients of the CHP unit. The tenth target formula is used to simulate the trend of the fuel cost of the CHP unit changing with the first power generation. The first variable is a binary variable indicating whether the CHP unit generates electricity. The first start-up cost is the start-up cost of the CHP unit. The eleventh target formula is used to simulate the trend of the start-up and shutdown costs of the CHP unit changing with the first variable. The first operating cost and the first depreciation cost are determined based on the power plant cost parameters. A twelfth target formula is constructed based on the first operating cost, the first depreciation cost, and the second power generation. The first operating cost is the unit power generation cost of the WPP unit, and the first depreciation cost is the loss cost of the WPP unit. The twelfth target formula is used to simulate the trend of the total cost of the WPP unit changing with the second power generation. The second operating cost and the second depreciation cost are determined based on the power plant cost parameters. A thirteenth target formula is constructed based on the second operating cost, the second depreciation cost, and the third power generation. The second operating cost is the unit power generation cost of the PV unit, and the second depreciation cost is the loss cost of the PV unit. The thirteenth target formula is used to simulate the trend of the total cost of the PV unit changing with the third power generation. The third depreciation cost is determined based on the power plant cost parameters. A fourteenth target formula is constructed based on the second operating cost, the first input quantity, and the third depreciation cost. The third depreciation cost is the loss cost of the electrical conversion device. The fourteenth target formula is used to simulate the trend of the total cost of the electrical conversion device changing with the first input quantity. The third operating cost is determined based on the power plant cost parameters. The fifteenth target formula is constructed based on the third operating cost and the second input. The third operating cost is the real-time electricity price of natural gas. The fifteenth target formula is used to simulate the trend of the total cost of the gas boiler changing with the second input. The power plant cost model is obtained by combining the tenth, eleventh, twelfth, thirteenth, fourteenth, and fifteenth objective formulas.

4. The method according to claim 3, characterized in that, The power plant cost model is obtained by simultaneously applying the tenth, eleventh, twelfth, thirteenth, fourteenth, and fifteenth objective formulas, including: The fourth depreciation cost is determined based on the power plant cost parameters. The fourth depreciation cost includes the fifth depreciation cost, the sixth depreciation cost, and the seventh depreciation cost. The fifth depreciation cost is the loss cost of the energy storage device, the sixth depreciation cost is the loss cost of the gas storage tank, and the seventh depreciation cost is the loss cost of the thermal storage tank. The first power generation, the first variable, the second power generation, the third power generation, the first input quantity, and the second input quantity are determined as the input parameters of the power plant cost model; The sum of the calculation results of the tenth, eleventh, twelfth, thirteenth, fourteenth, and fifteenth objective formulas, and the sum of the fourth depreciation cost, are determined as the output parameters of the power plant cost model, thus obtaining the power plant cost model.

5. The method according to claim 2, characterized in that, Before obtaining the power plant control parameters by solving the operating parameters of the power plant simulation model with the objective function of maximizing the net profit of the power plant cost model, the method further includes: A power plant revenue model is constructed based on the power plant simulation model. The power plant revenue model is used to simulate the trend of the revenue of the virtual power plant as the operating parameters of the power plant simulation model change.

6. The method according to claim 5, characterized in that, Based on the power plant simulation model, a power plant revenue model is constructed, including: Obtain a first unit price and a second unit price, wherein the first unit price is the electricity sales unit price of the virtual power plant, and the second unit price is the heat sales unit price of the virtual power plant; A sixteenth target formula is constructed based on the first unit price, the second unit price, the first power generation, and the first heat production. The sixteenth target formula is used to simulate the revenue trend of the CHP unit as the first power generation and the first heat production change. A seventeenth target formula is constructed based on the first unit price, the second power generation, and the third power generation. The seventeenth target formula is used to simulate the trend of the total revenue of the WPP unit and the PV unit as the second power generation and the third power generation change. An eighteenth target formula is constructed based on the second unit price and the second output quantity. The eighteenth target formula is used to simulate the trend of the revenue of the gas boiler changing with the second output quantity. The power plant revenue model is obtained by combining the sixteenth objective formula, the seventeenth objective formula, and the eighteenth objective formula.

7. The method according to claim 1, characterized in that, Construct a set of target constraints, including: Construct the power balance constraints of the virtual power plant corresponding to the power plant simulation model to obtain the first objective constraint; The output constraints of the CHP units of the virtual power plant corresponding to the power plant simulation model are constructed to obtain the second objective constraint; Construct the WPP unit output constraints of the virtual power plant corresponding to the power plant simulation model to obtain the third objective constraint; The output constraints of the PV units of the virtual power plant corresponding to the power plant simulation model are constructed to obtain the fourth objective constraint; Construct the power constraints of the CHP units of the virtual power plant corresponding to the power plant simulation model to obtain the fifth objective constraint; Construct the reserve capacity constraint of the virtual power plant corresponding to the power plant simulation model to obtain the sixth objective constraint; The first objective constraint, the second objective constraint, the third objective constraint, the fourth objective constraint, the fifth objective constraint, and the sixth objective constraint are combined to obtain the objective constraint group.

8. A dispatching device for an energy-coupled virtual power plant based on multiple energy storage devices, characterized in that, The device includes: The acquisition unit is used to acquire historical operating parameters, including power plant operating parameters and power plant cost parameters. The power plant operating parameters include the operating parameters of each component of the virtual power plant, and the power plant cost parameters include the operating costs of each component. The components include at least WPP units, PV units, CHP units, gas-fired boilers, thermal storage tanks, gas storage tanks, energy storage devices, and electrical conversion devices. The PV units convert solar energy into electrical energy to supply the electrical load, and the WPP units convert wind energy into electrical energy to supply the electrical load. The CHP unit converts natural gas into electrical energy to supply the electrical energy storage device and the electrical load, and the generated heat supplies the thermal load. The gas boiler converts natural gas into thermal energy to supply the thermal load and the thermal storage tank. The thermal storage tank is used to store thermal energy and supply the thermal load. The electrical conversion device is used to receive electrical energy, convert it into natural gas, and supply it to the gas storage tank. The gas storage tank is used to store natural gas and supply it to the CHP unit and the gas boiler. The electrical energy storage device is used to store electrical energy and supply it to the electrical conversion device. The first construction unit is used to construct a power plant simulation model based on the power plant operating parameters. The power plant simulation model is used to simulate the energy flow between the various component elements. The second construction unit is used to construct a power plant cost model based on the power plant simulation model and the power plant cost parameters. The power plant cost model is used to simulate the cost trend of the virtual power plant as the operating parameters of the power plant simulation model change. The third construction unit is used to construct a target constraint group, which is used to limit the range of values ​​of the operating parameters of the power plant simulation model. The target constraint group includes at least power balance constraints, CHP unit output constraints, WPP unit output constraints, PV unit output constraints, CHP unit power constraints, and reserve capacity constraints. The calculation unit is used to solve the operating parameters of the power plant simulation model under the constraints of the target constraint group, with the objective function of maximizing the net profit of the virtual power plant, to obtain the power plant control parameters, and to control the operation of the virtual power plant according to the power plant control parameters.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the method according to any one of claims 1 to 7.

10. A virtual power plant dispatching system, characterized in that, include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs comprising methods for performing any one of claims 1 to 7.

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