Resource allocation method and device for virtual power plant to participate in multiple markets and electronic equipment

Abstract

The invention relates to the technical field of electric power, in particular to a resource allocation method and device for a virtual power plant to participate in multiple markets and electronic equipment, and the method comprises the steps: constructing a resource allocation income model for the virtual power plant to participate in multiple markets; and constructing a market clearing model of the virtual power plant participating in the multiple markets, wherein the market clearing model comprises a second target function and a plurality of second constraint conditions, wherein the target of the second target function is to minimize the clearing cost of the multiple markets. And deciding and configuring the resources of the virtual power plant participating in the multiple markets based on the resource configuration income model and the market clearing model. Therefore, the resource allocation efficiency of the virtual power plant participating in the multiple markets is improved, and the reliability of achieving the revenue maximization target is high.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to a resource allocation method, device and electronic equipment for a virtual power plant to participate in multiple markets. Background Art

[0002] In recent years, the world has actively promoted energy transformation, and the proportion of renewable energy, represented by wind and solar power, in the power system has continued to rise. Although this trend has strongly promoted the development of a green and low-carbon energy structure, the inherent characteristics of renewable energy, such as randomness, intermittency, and volatility, make it difficult to accurately predict power supply. Faced with the complex changes brought about by the integration of renewable energy, the stability of the power grid is seriously threatened, and more flexible resources are needed to ensure the safe and reliable operation of the power grid. In this context, virtual power plants (VPPs) integrate distributed energy resources and flexibly and accurately allocate resources according to the real-time needs of the power grid, greatly improving the regulation capacity of the power system.

[0003] In a multi-market environment, the strategy for virtual power plants to participate in the market lacks systematic planning. They often consider each market participation method in isolation, without fully considering the close coupling relationship between the markets. For example, when a virtual power plant participates in the allocation of resources in the energy market and the frequency regulation market, it only considers its participation in the energy market or the frequency regulation market in isolation, without considering the close coupling relationship between the energy market and the frequency regulation market. The coordinated optimization of multiple markets is seriously insufficient, and it is impossible to achieve the optimal allocation of resources between different markets, and thus it is difficult to achieve the goal of maximizing profits. In this way, when the above method is used to allocate resources for virtual power plants to participate in multiple markets, the coordinated optimization of multiple markets is seriously insufficient, resulting in low efficiency in resource allocation for virtual power plants to participate in multiple markets and low reliability in achieving the goal of maximizing profits. Summary of the Invention

[0004] In order to solve the technical problem of low evaluation accuracy of the dynamic response capability of temperature control loads, the present invention aims to provide a resource allocation method, device, and electronic equipment for a virtual power plant to participate in multiple markets. The technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present invention provides a resource allocation method for a virtual power plant participating in multiple markets, comprising: constructing a resource allocation benefit model for the virtual power plant participating in multiple markets, the resource allocation benefit model including a first objective function and a plurality of first constraints whose objective is to maximize the benefit of the virtual power plant, the first objective function being determined based on key parameters of electricity market transactions in the electric energy market in which the virtual power plant participates, key parameters of the frequency regulation market in which the frequency regulation market participates, compensation costs of load equipment, and operating cost parameters of distributed resources; constructing a market clearing model for the virtual power plant participating in multiple markets, the market clearing model including a second objective function and a plurality of second constraints whose objective is to minimize clearing costs of the multiple markets, the second objective function being determined based on first electricity market declaration data of load equipment in the electric energy market, first frequency regulation declaration data of load equipment in the frequency regulation market, key parameters of electricity market transactions, key parameters of the frequency regulation market, second electricity market declaration data of the virtual power plant in the electric energy market, and second frequency regulation declaration data of the virtual power plant in the frequency regulation market. Based on the resource allocation benefit model and the market clearing model, decisions are made and allocated on the resources for the virtual power plant to participate in multiple markets.

[0006] Optionally, constructing a resource allocation benefit model for a virtual power plant to participate in multiple markets includes: obtaining the amount of electricity sold and purchased that the virtual power plant won in the electric energy market in each time period, the clearing price of the virtual power plant in the electric energy market and the frequency regulation market in each time period, and the frequency regulation capacity and frequency regulation mileage that the virtual power plant won in the frequency regulation market in each time period; determining the total clearing cost of the virtual power plant for clearing distributed resources based on the amount of electricity sold and purchased, the clearing price, the frequency regulation capacity and the frequency regulation mileage in each time period; determining the difference between the total clearing cost and the compensation cost and operating cost parameters in each time period, and superimposing the differences in each time period to obtain a first objective function; determining the first constraint condition based on the operating constraint rules of each distributed resource, the operating constraint rules of the load equipment, the power balance constraint rules of the distributed resources of the virtual power plant participating in multiple markets, the capacity declaration constraint rules of the virtual power plant participating in multiple markets, and the price declaration constraint rules of the virtual power plant participating in multiple markets.

[0007] Optionally, determining the total clearing cost of the virtual power plant for clearing distributed resources based on the electricity sales and purchases, clearing price, frequency regulation capacity and frequency regulation mileage in each time period includes: calculating a first difference between the electricity sales and purchases, and calculating a first product of the first difference and the clearing price time of the virtual power plant in the electricity market in each time period; calculating a second product between the clearing price of the frequency regulation capacity of the virtual power plant in the frequency regulation market in each time period and the frequency regulation capacity, and a third product between the clearing price of the frequency regulation mileage of the virtual power plant in the frequency regulation market in each time period and the frequency regulation mileage; superimposing the first product, the second product and the third product to obtain a first sum; and superimposing the first sum of each time period to obtain the total clearing cost.

[0008] Optionally, constructing a market clearing model for virtual power plants to participate in multiple markets includes:

[0009] The total declared cost of the load equipment is determined based on the first electricity market declaration data and electricity market winning data of each load equipment in the electric energy market in each time period, and the first frequency regulation declaration data and frequency regulation winning data of each load equipment in the frequency regulation market; the total declared cost of the virtual power plant is determined based on the key electricity market transaction parameters and frequency regulation market key parameters of the virtual power plant in each time period, the second electricity market declaration data of the virtual power plant in the electric energy market, and the second frequency regulation declaration data of the virtual power plant in the frequency regulation market; the total declared cost of the load equipment and the total declared cost of the virtual power plant are superimposed to obtain the second objective function; the second constraint conditions are determined based on the node power balance rules in the virtual power plant, the connection line safety rules between the nodes, the capacity and mileage balance rules of the frequency regulation market, and the market clearing rules of the electric energy market and the frequency regulation market.

[0010] Optionally, based on the first electricity market declaration data and electricity market winning bid data of each load device in the electric energy market in each time period, and the first frequency modulation declaration data and frequency modulation winning bid data of each load device in the frequency modulation market, determining the total declared cost of the load device includes: calculating the fourth product between the first electricity market declaration data and the electricity market winning bid data of each load device in the electric energy market in each time period, the fifth product between the frequency modulation capacity declaration data and the frequency modulation capacity winning bid data in the first frequency modulation declaration data of each load device in the frequency modulation market, and the sixth product between the frequency modulation mileage declaration data and the frequency modulation mileage winning bid data in the first frequency modulation declaration data of each load device in the frequency modulation market; superimposing the fourth product, the fifth product and the sixth product to obtain a second sum; superimposing the second sum of each time period to obtain the total declared cost of the load device.

[0011] Optionally, based on the key parameters of electricity market transactions of the virtual power plant in each time period, the key parameters of the frequency regulation market, the second electricity market declaration data of the virtual power plant in the electric energy market, and the second frequency regulation declaration data of the virtual power plant in the frequency regulation market, determining the total declared cost of the virtual power plant includes: calculating the seventh product between the electricity sales price in the second electricity market declaration data of the virtual power plant in each time period and the electricity sales amount in the key parameters of electricity market transactions, the eighth product between the electricity purchase price in the second electricity market declaration data of the virtual power plant in each time period and the electricity purchase amount in the key parameters of electricity market transactions, the ninth product between the frequency regulation capacity declaration price in the second frequency regulation declaration data and the frequency regulation capacity in the key parameters of frequency regulation market, and the tenth product between the frequency regulation mileage declaration price in the second frequency regulation declaration data and the frequency regulation mileage in the key parameters of frequency regulation market; calculating the second difference between the seventh product and the eighth product, and calculating the third sum between the second difference, the ninth product and the tenth product; and superimposing the third sums of each time period to obtain the total declared cost of the virtual power plant.

[0012] Optionally, making decisions and allocating resources for the virtual power plant to participate in multiple markets based on the resource allocation benefit model and the market clearing model includes: introducing Lagrange multipliers to convert the second constraint of the market clearing model into a Lagrangian function; deriving the Lagrangian function to obtain the marginal cost and market supply and demand balance conditions of the market clearing model; through the principle of strong duality, converting the second objective function of the market clearing model into a dual problem; using the optimal solution of the dual problem as the third constraint of the resource allocation benefit model, the third constraint includes marginal cost and market supply and demand balance conditions; using a linearization method to convert the complementary constraints of the first objective function into a linear form, and converting the product of the dual variable and the decision variable in the first objective function into a linear form to obtain a mixed integer linear programming problem; solving the mixed integer linear programming problem through a target solver to obtain the amount of electricity sold and purchased, the purchase price and selling price of electricity in the electric energy market of the virtual power plant, as well as the frequency regulation capacity, frequency regulation mileage and frequency regulation price in each period of the frequency regulation market.

[0013] In a second aspect, an embodiment of the present invention provides a resource allocation device for a virtual power plant to participate in multiple markets, including: a construction module for constructing a resource allocation benefit model for a virtual power plant to participate in multiple markets, the resource allocation benefit model including a first objective function and multiple first constraints whose goal is to maximize the benefit of the virtual power plant, the first objective function is determined based on the key parameters of electricity market transactions in the electric energy market in which the virtual power plant participates, the key parameters of the frequency regulation market, the compensation cost of the load equipment, and the operating cost parameters of distributed resources; the construction module is also used to construct a market clearing model for the virtual power plant to participate in multiple markets, the market clearing model including a second objective function and multiple second constraints whose goal is to minimize the clearing costs of multiple markets, the second objective function is determined based on the first electricity market declaration data of the load equipment in the electric energy market, the first frequency regulation declaration data of the load equipment in the frequency regulation market, key parameters of electricity market transactions, key parameters of the frequency regulation market, the second electricity market declaration data of the virtual power plant in the electric energy market, and the second frequency regulation declaration data of the virtual power plant in the frequency regulation market; a configuration module for making decisions and configuring resources for the virtual power plant to participate in multiple markets based on the resource allocation benefit model and the market clearing model.

[0014] Optionally, the construction module is also used to obtain the electricity sales and purchase amounts won by the virtual power plant in the electric energy market in each time period, the clearing prices of the virtual power plant in the electric energy market and the frequency regulation market in each time period, and the frequency regulation capacity and frequency regulation mileage won by the virtual power plant in the frequency regulation market in each time period; determine the total clearing cost of the virtual power plant for clearing distributed resources based on the electricity sales and purchase amounts, clearing prices, frequency regulation capacity and frequency regulation mileage in each time period; determine the difference between the total clearing cost and the compensation cost and operating cost parameters in each time period, and superimpose the differences in each time period to obtain the first objective function; determine the first constraint condition based on the operating constraint rules of each distributed resource, the operating constraint rules of the load equipment, the power balance constraint rules of the distributed resources of the virtual power plant participating in multiple markets, the capacity declaration constraint rules of the virtual power plant participating in multiple markets, and the price declaration constraint rules of the virtual power plant participating in multiple markets.

[0015] In a third aspect, an embodiment of the present invention provides an electronic device comprising: a processor and a memory; wherein the memory is used to store computer programs that can be run on the processor; and the processor is used to execute the programs stored in the memory to implement the steps of the resource allocation method for virtual power plants participating in multiple markets as mentioned in the first aspect.

[0016] The present invention has the following beneficial effects: first, a resource allocation benefit model for a virtual power plant participating in multiple markets is constructed, the resource allocation benefit model includes a first objective function and multiple first constraints for maximizing the benefit of the virtual power plant, the first objective function is determined based on the key parameters of the power market transactions in the electric energy market, the key parameters of the frequency regulation market, the compensation cost of the load equipment, and the operating cost parameters of the distributed resources; second, a market clearing model for the virtual power plant participating in multiple markets is constructed, the market clearing model includes a second objective function and multiple second constraints for minimizing the clearing cost of the multiple markets, the second objective function is determined based on the first power market declaration data of the load equipment in the electric energy market, the first frequency regulation declaration data of the load equipment in the frequency regulation market, the key parameters of the power market transactions, the key parameters of the frequency regulation market, the second power market declaration data of the virtual power plant in the electric energy market, and the second frequency regulation declaration data of the virtual power plant in the frequency regulation market. Finally, based on the resource allocation benefit model and the market clearing model, decisions are made and allocations are made on the resources for the virtual power plant to participate in multiple markets.

[0017] In this way, the embodiment of the present invention can collaboratively optimize the maximization of the benefits of the virtual power plant's participation in the energy market and frequency regulation market and the minimization of the market clearing costs through the resource allocation model and the market clearing model, fully consider the close coupling relationship between the energy market and the frequency regulation market, and collaboratively consider its resource allocation for participating in the energy market or the frequency regulation market, thereby optimizing the collaborative optimization performance of multiple markets, achieving the optimal allocation of resources among different markets, and thus promoting the goal of maximizing benefits. In this way, when the above-mentioned method is used to configure the resources of the virtual power plant participating in multiple markets, the collaborative optimization of multiple markets is guaranteed, the resource allocation efficiency of the virtual power plant participating in multiple markets is improved, and the reliability of achieving the goal of maximizing benefits is high. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 A flowchart of a resource allocation method for a virtual power plant participating in multiple markets provided in an embodiment of the present invention.

[0020] Figure 2 This is a resource allocation result of a virtual power plant in the electric energy market provided by an embodiment of the present invention.

[0021] Figure 3 This embodiment of the present invention provides a resource allocation result of the frequency regulation capacity of a virtual power plant in the frequency regulation market.

[0022] Figure 4 This embodiment of the present invention provides a resource allocation result of frequency regulation mileage of a virtual power plant in the frequency regulation market.

[0023] Figure 5 A structural diagram of a resource allocation device for a virtual power plant participating in multiple markets provided by an embodiment of the present invention.

[0024] Figure 6 The present invention provides a schematic structural diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] To further illustrate the technical means and effectiveness of the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of a method, device, and electronic device for allocating resources for a virtual power plant participating in multiple markets proposed by the present invention. In the following description, different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0026] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0027] The following describes in detail a method, device and electronic equipment for allocating resources for a virtual power plant to participate in multiple markets provided by the present invention in conjunction with the accompanying drawings.

[0028] like Figure 1 As shown, the resource allocation method for a virtual power plant participating in multiple markets disclosed in an embodiment of the present invention includes:

[0029] Step S101, construct a resource allocation benefit model for the virtual power plant to participate in multiple markets. The resource allocation benefit model includes a first objective function whose goal is to maximize the benefit of the virtual power plant and multiple first constraints. The first objective function is determined based on the key parameters of the electricity market transactions in the electric energy market in which the virtual power plant participates, the key parameters of the frequency regulation market, the compensation cost of the load equipment, and the operating cost parameters of the distributed resources.

[0030] Specifically, the embodiment of the present invention constructs a two-tier decision-making model, in which the upper-tier model is a resource allocation benefit model, and the lower-tier model is a market clearing model. The two-tier decision-making model simultaneously considers the resource allocation when the virtual power plant participates in the electric energy market and the frequency regulation market at the same time. The goal of the upper-tier model in the embodiment of the present invention is to maximize the benefits of the virtual power plant, and the goal of the lower-tier model is to minimize the market clearing costs and complete the joint clearing of the market. Among them, the two-tier decision-making model in the embodiment of the present invention is established based on the Stackelberg game principle.

[0031] Furthermore, in the embodiment of the present invention, the key parameters of the electricity market transaction in the electric energy market include but are not limited to the amount of electricity sold and purchased by the virtual power plant in the electric energy market during each period, the clearing price of the virtual power plant in the electric energy market during each period, etc. The key parameters of the frequency regulation market in the frequency regulation market include but are not limited to the clearing price of the frequency regulation capacity of the virtual power plant in the frequency regulation market during each period, the clearing price of the frequency regulation mileage, the winning frequency regulation capacity and frequency regulation mileage, etc. The compensation cost of the load equipment includes but is not limited to the compensation cost of the virtual power plant to compensate the load equipment (such as air conditioners) for the electricity price during each period. The operating cost parameters of distributed resources include but are not limited to the operating cost of the gas turbine in the virtual power plant, the operating cost of the energy storage equipment, and the operating cost of the wind power equipment.

[0032] Furthermore, the first constraints include, but are not limited to, distributed resource constraints corresponding to the operating constraint rules for each distributed resource, load device constraints corresponding to the operating constraint rules for load devices, constraints corresponding to the power balance constraint rules for distributed resources in virtual power plants participating in multiple markets, and constraints corresponding to the price declaration constraint rules for virtual power plants participating in multiple markets. Distributed resource constraints include, but are not limited to, gas turbine constraints, wind power equipment constraints, and energy storage equipment operating constraints. Load device constraints include, but are not limited to, air conditioning load operating constraints.

[0033] Furthermore, as an optional embodiment of the present invention, constructing a resource allocation benefit model for a virtual power plant to participate in multiple markets includes: obtaining the amount of electricity sold and purchased that the virtual power plant won in the electric energy market in each time period, the clearing price of the virtual power plant in the electric energy market and the frequency regulation market in each time period, and the frequency regulation capacity and frequency regulation mileage that the virtual power plant won in the frequency regulation market in each time period; determining the total clearing cost of the virtual power plant for clearing distributed resources based on the amount of electricity sold and purchased, the clearing price, the frequency regulation capacity and the frequency regulation mileage in each time period; determining the difference between the total clearing cost and the compensation cost and operating cost parameters in each time period, and superimposing the difference in each time period to obtain a first objective function; determining the first constraint condition based on the operating constraint rules of each distributed resource, the operating constraint rules of the load equipment, the power balance constraint rules of the distributed resources of the virtual power plant participating in multiple markets, the capacity declaration constraint rules of the virtual power plant participating in multiple markets, and the price declaration constraint rules of the virtual power plant participating in multiple markets.

[0034] Specifically, in an embodiment of the present invention, when determining the total clearing cost, the first difference between the amount of electricity sold and the amount of electricity purchased is first calculated, and the first product of the first difference and the clearing price time of the virtual power plant in the electric energy market in each time period is calculated; then the second product between the clearing price of the frequency regulation capacity of the virtual power plant in the frequency regulation market in each time period and the frequency regulation capacity, and the third product between the clearing price of the frequency regulation mileage of the virtual power plant in the frequency regulation market in each time period and the frequency regulation mileage are calculated; finally, the first product, the second product and the third product are superimposed to obtain a first sum; the first sum of each time period is superimposed to obtain the total clearing cost.

[0035] Furthermore, taking the distributed resources as gas turbines, energy storage equipment, and wind power equipment, and the load equipment as air conditioning users as an example, the embodiment of the present invention uses the following formula to express the first objective function:

[0036]

[0037] In the above formula, It is the profit of virtual power plant after participating in bidding in electricity energy market and frequency regulation market. represents the first objective function of maximizing the benefits of the virtual power plant. It represents the amount of electricity sold by the virtual power plant in the electricity market during period t. Represents the amount of electricity purchased by the virtual power plant in the electricity market during period t. It represents the clearing price of the virtual power plant in the electricity market during period t. It represents the clearing price of the frequency regulation capacity of the virtual power plant in the frequency regulation market during period t. It represents the clearing price of the frequency regulation mileage of the virtual power plant in the frequency regulation market in period t. It represents the frequency regulation capacity won by the virtual power plant in the frequency regulation market during period t. It represents the frequency regulation mileage won by the virtual power plant in the frequency regulation market during period t. It represents the compensation cost of the virtual power plant to compensate the air-conditioning users (load equipment) for the electricity price during period t. Represents the operating cost parameters of the gas turbine in the virtual power plant. represents the operating cost parameters of the energy storage equipment in the virtual power plant, represents the operating cost parameter of wind power equipment in the virtual power plant. T represents the number of time periods in which the virtual power plant participates.

[0038] Among them, in the above formula, Indicates the total clearing cost.

[0039] Furthermore, the embodiments of the present invention take the distributed resources as gas turbines, energy storage equipment and wind power equipment, and the load equipment as air-conditioning users as examples, and use the following formulas to represent the first constraints, wherein the first constraints include the constraints of the gas turbine, the operating constraints of the wind power equipment, the operating constraints of the energy storage equipment and the operating constraints of the air-conditioning load, the power balance constraints of the virtual power plant, the declared capacity constraints of the virtual power plant and the declared price constraints of the virtual power plant.

[0040] Constraints of gas turbines:

[0041]

[0042] In the above formula, represents the operating cost parameter of the gas turbine in the virtual power plant. c,v represents the fuel cost coefficient of the gas turbine. c c,sd Represents the start-up and shutdown cost coefficient of the gas turbine. It represents the active power output of the gas turbine in time period t. A Boolean variable indicating the enabled state of the gas turbine during period t. A Boolean variable representing the stop state of the gas turbine during period t, where the gas turbine is started 1. 0, when stopped 1. is 0. Indicates the maximum active power output of the gas turbine. Indicates the minimum active power output of the gas turbine.

[0043] Operating constraints of wind power equipment:

[0044]

[0045] In the above formula, Represents the operating cost parameters of wind power equipment in the virtual power plant. Indicates the active power output of wind power equipment in period t. w Represents the unit output cost of wind power equipment in period t. Indicates the minimum active output of wind power equipment. Indicates the maximum active output of the wind turbine.

[0046] Operating constraints of energy storage equipment:

[0047]

[0048] In the above formula, Represents the operating cost parameter of the energy storage equipment in the virtual power plant. sis the unit active power operating cost of the energy storage equipment. Represents the charging power of the energy storage device in time period t. Represents the discharge power of the energy storage device in time period t. and It is a Boolean variable used to ensure that the charging and discharging states of the energy storage device are mutually exclusive. 1. 0, in discharge state 1. is 0. Indicates the maximum charging power of the energy storage device. Indicates the maximum discharge power of the energy storage device. Indicates the maximum capacity of the energy storage device. Indicates the minimum capacity of the energy storage device. Represents the remaining capacity of the energy storage device in time period t. Represents the remaining capacity of the energy storage device in time period t-1. s is the charge and discharge efficiency of the energy storage device.

[0049] Air conditioning load operating constraints: This embodiment of the present invention assumes that the virtual power plant first signs a compensation agreement with some air conditioning users in the region. That is, the virtual power plant requires these users to participate in the unified scheduling of the virtual power plant at a certain compensation price. Considering that it is summer and the air conditioner is in cooling mode, the operating constraints of the air conditioning load are as follows:

[0050]

[0051] In the above formula, λ represents the compensation cost of the virtual power plant to compensate the air conditioning load equipment for the electricity price during period t. fl,t It represents the compensation electricity price for time period t agreed upon by the virtual power plant and the air-conditioning user. is the dispatchable power of air conditioning load in period t. It represents the maximum dispatchable power of air conditioning load in time period t. Indicates the minimum dispatchable power of air conditioning load in time period t. N AC is the number of users who signed the air-conditioning contract. t out is the outdoor temperature at time t of the next day. t down Indicates the lower limit of the user's comfort temperature range. t upRepresents the upper limit of the user comfort temperature range. k1, k2, l1, l2, and R are all critical parameters of the air conditioning load model, where R represents the equivalent thermal resistance of the room. k1, k2, l1, and l2 are all constant coefficients of the inverter AC system, which can be determined based on the application scenario of the inverter AC system and are not limited in this embodiment of the present invention.

[0052] The power balance constraints for distributed resources participating in multiple markets for virtual power plants are as follows:

[0053]

[0054] In the above formula, It represents the amount of electricity sold by the virtual power plant in the electricity market during period t. Represents the amount of electricity purchased by the virtual power plant in the electricity market during period t. It represents the active power output of the gas turbine in time period t. It represents the active power output of wind power equipment in period t. Represents the charging power of the energy storage device in time period t. Represents the discharge power of the energy storage device in time period t. is the dispatchable power of air conditioning load in period t.

[0055] The capacity declaration constraints for virtual power plants participating in multiple markets are as follows:

[0056]

[0057] In the above formula, It represents the electricity sales amount reported by the virtual power plant in the electricity market during period t. Represents the amount of electricity purchased by the virtual power plant in the electricity market during period t. It represents the frequency regulation capacity declared by the virtual power plant in period t. It represents the frequency regulation mileage declared by the virtual power plant in period t. It represents the maximum value of the frequency regulation capacity declared by the virtual power plant in period t. It represents the maximum value of frequency regulation mileage declared by the virtual power plant in period t. and Both are Boolean variables, indicating that the virtual power plant cannot be in the state of purchasing and selling electricity at the same time. When in the state of selling electricity, 1. 0; in the electricity purchasing state 1. is 0. It represents the maximum amount of electricity sales that the virtual power plant can declare during period t. It represents the maximum amount of electricity that the virtual power plant can declare to purchase during period t. It represents the maximum output of the gas turbine during period t. Indicates the maximum output of the wind turbine during period t. It represents the maximum capacity of the adjustable air-conditioning load during period t. It is the frequency regulation mileage multiplier of the virtual power plant. The specific value can be determined according to the actual scenario and is not limited in this embodiment of the present invention. Represents the discharge power of the energy storage device in time period t.

[0058] The price constraints for virtual power plants are as follows:

[0059]

[0060] In the above formula, It represents the electricity purchase price declared by the virtual power plant in period t. It represents the electricity selling price declared by the virtual power plant in period t. Indicates the frequency regulation capacity price declared by the virtual power plant. Indicates the frequency regulation mileage price declared by the virtual power plant. It represents the maximum electricity selling price that the virtual power plant is allowed to declare in the electricity market during period t. It represents the maximum electricity purchase price that the virtual power plant is allowed to declare in the electricity market during period t. It represents the maximum frequency regulation capacity that a virtual power plant is allowed to declare in the frequency regulation market during period t. It represents the maximum frequency regulation mileage that a virtual power plant is allowed to declare in the frequency regulation market during period t.

[0061] Step S102, construct a market clearing model for virtual power plants to participate in multiple markets. The market clearing model includes a second objective function whose goal is to minimize the clearing costs of multiple markets and multiple second constraints. The second objective function is determined based on the first electricity market declaration data of the load equipment in the electric energy market, the first frequency regulation declaration data of the load equipment in the frequency regulation market, key parameters of electricity market transactions, key parameters of the frequency regulation market, the second electricity market declaration data of the virtual power plant in the electric energy market, and the second frequency regulation declaration data of the virtual power plant in the frequency regulation market.

[0062] Specifically, in embodiments of the present invention, the first power market declaration data includes, but is not limited to, the declared price of load equipment in the electric energy market, the amount of electricity bid successfully completed, and the like. The first frequency regulation declaration data in the frequency regulation market includes, but is not limited to, the declared price of frequency regulation capacity of load equipment in the frequency regulation market, the declared price of frequency regulation mileage, the frequency regulation capacity bid successfully completed, and the frequency regulation mileage bid successfully completed in the frequency regulation market. Key power market transaction parameters include, but are not limited to, the amount of electricity sold and purchased by virtual power plants in the electric energy market during each time period, and the clearing price of virtual power plants in the electric energy market during each time period. Key frequency regulation market parameters in the frequency regulation market include, but are not limited to, the clearing price of frequency regulation capacity, the clearing price of frequency regulation mileage, the frequency regulation capacity bid successfully completed, and the frequency regulation mileage bid successfully completed in the frequency regulation market during each time period. The second power market declaration data includes, but is not limited to, the purchase price and sales price of electricity declared by virtual power plants during each time period. The second frequency regulation declaration data includes, but is not limited to, the frequency regulation capacity price and frequency regulation mileage price declared by virtual power plants during each time period.

[0063] Furthermore, the second constraints include but are not limited to node power balance constraints corresponding to node power balance rules in virtual power plants, connection line safety constraints corresponding to connection line safety rules between nodes, capacity and mileage balance constraints of the frequency regulation market corresponding to capacity and mileage balance rules of the frequency regulation market, and market clearing constraints corresponding to market clearing rules of the electric energy market and the frequency regulation market.

[0064] Furthermore, as an optional embodiment of the present invention, constructing a market clearing model for virtual power plants to participate in multiple markets includes: determining the total declared cost of the load equipment based on the first electricity market declaration data and electricity market winning data of each load equipment in the electric energy market in each time period, and the first frequency regulation declaration data and frequency regulation winning data of each load equipment in the frequency regulation market; determining the total declared cost of the virtual power plant based on the key electricity market transaction parameters of the virtual power plant in each time period, the key parameters of the frequency regulation market, the second electricity market declaration data of the virtual power plant in the electric energy market, and the second frequency regulation declaration data of the virtual power plant in the frequency regulation market; superimposing the total declared cost of the load equipment and the total declared cost of the virtual power plant to obtain a second objective function; determining each second constraint condition based on the node power balance rule in the virtual power plant, the connection line safety rule between each node, the capacity and mileage balance rule of the frequency regulation market, and the market clearing rules of the electric energy market and the frequency regulation market.

[0065] Specifically, as an optional embodiment of the present invention, based on the first electricity market declaration data and electricity market winning bid data of each load device in the electric energy market in each time period, and the first frequency modulation declaration data and frequency modulation winning bid data of each load device in the frequency modulation market, determining the total declared cost of the load device includes: calculating the fourth product between the first electricity market declaration data and the electricity market winning bid data of each load device in the electric energy market in each time period, the fifth product between the frequency modulation capacity declaration data and the frequency modulation capacity winning bid data in the first frequency modulation declaration data of each load device in the frequency modulation market, and the sixth product between the frequency modulation mileage declaration data and the frequency modulation mileage winning bid data in the first frequency modulation declaration data of each load device in the frequency modulation market; superimposing the fourth product, the fifth product and the sixth product to obtain a second sum; superimposing the second sum of each time period to obtain the total declared cost of the load device.

[0066] Furthermore, as an optional embodiment of the present invention, according to the key parameters of electricity market transactions, frequency regulation market key parameters, the second electricity market declaration data of the virtual power plant in the electric energy market and the second frequency regulation declaration data of the virtual power plant in the frequency regulation market in each time period, determining the total declared cost of the virtual power plant includes: calculating the seventh product between the electricity sales price in the second electricity market declaration data of the virtual power plant in each time period and the electricity sales amount in the key parameters of electricity market transactions, the eighth product between the electricity purchase price in the second electricity market declaration data of the virtual power plant in each time period and the electricity purchase amount in the key parameters of electricity market transactions, the ninth product between the frequency regulation capacity declaration price in the second frequency regulation declaration data and the frequency regulation capacity in the key parameters of frequency regulation market, and the tenth product between the frequency regulation mileage declaration price in the second frequency regulation declaration data and the frequency regulation mileage in the key parameters of frequency regulation market; calculating the second difference between the seventh product and the eighth product, and calculating the third sum between the second difference, the ninth product and the tenth product; superimposing the third sum of each time period to obtain the total declared cost of the virtual power plant.

[0067] Specifically, the embodiment of the present invention specifically uses the following formula to express the second objective function:

[0068]

[0069] In the above formula, Represents the sum of clearing costs. represents minimizing the sum of clearing costs. It represents the declared price of the load equipment (unit) in the electric energy market during the period t. It represents the declared price of the frequency regulation capacity of the load equipment (unit) within the time period t. It represents the declared price of the frequency regulation mileage of the load equipment (unit) within the time period t. It represents the amount of electricity that the load equipment (unit) bids for in the electricity market during time period t. It represents the frequency regulation capacity of the load equipment (unit) that won the bid in the frequency regulation market within the time period t. It represents the frequency regulation mileage of the load equipment (unit) in the frequency regulation market during period t. G is the total number of units participating in multiple markets. It represents the amount of electricity sold by the virtual power plant in the electricity market during period t. Represents the amount of electricity purchased by the virtual power plant in the electricity market during period t. It represents the frequency regulation capacity won by the virtual power plant in the frequency regulation market during period t. It represents the frequency regulation mileage won by the virtual power plant in the frequency regulation market during period t. Indicates the frequency regulation capacity price declared by the virtual power plant. Indicates the frequency regulation mileage price declared by the virtual power plant. It represents the electricity purchase price declared by the virtual power plant in period t. It represents the electricity selling price declared by the virtual power plant in period t.

[0070] In the above formula, the first half represents the total declared cost of the load equipment, and the second half represents the total declared cost of the virtual power plant.

[0071] Furthermore, the second constraint condition is as follows:

[0072] First, the node power balance constraints:

[0073]

[0074] In the above formula, It represents the amount of electricity sold by the virtual power plant in the electricity market during period t. Represents the amount of electricity purchased by the virtual power plant in the electricity market during period t. It represents the amount of electricity that the load equipment (unit) bids for in the electricity market during time period t. P represents the declared price of the load equipment (unit) in the electric energy market during period t. w,t L is the winning bid amount of wind power equipment w in period t. d,t Represents the load forecast value in period t. nm is the line admittance between nodes n and m. n,t The phase of node n at time t. θ m,t are the phases of node m at time t. n,t is the dual variable corresponding to the power balance constraint. Ω n They correspond to the wind power equipment, load equipment and node set connected to node n. Gis the total number of units participating in multiple markets.

[0075] Secondly, line safety constraints:

[0076]

[0077] In the above formula, L l Indicates the maximum transmission capacity of line l. nm is the line admittance between nodes n and m. n,t The phase of node n at time t. θ m,t are the phases of node m at time t. n Represents the set of links connected to node n. Dual variable representing the upper limit of line power flow. The dual variable representing the lower limit of the line power flow. ε1 represents the voltage phase angle θ at node n=1 n =1 dual variable.

[0078] Then, the frequency regulation capacity and frequency regulation mileage balance constraints are as follows:

[0079]

[0080] In the above formula, Indicates the set system frequency regulation capacity requirement. Indicates the set system frequency regulation mileage requirement. Represents the dual variable corresponding to the frequency regulation capacity. Represents the dual variable corresponding to the frequency modulation mileage. It represents the frequency regulation capacity won by the virtual power plant in the frequency regulation market during period t. It represents the frequency regulation mileage won by the virtual power plant in the frequency regulation market during period t. It represents the frequency regulation capacity of the load equipment (unit) that won the bid in the frequency regulation market within the time period t. It represents the frequency regulation mileage of the load equipment (unit) in the frequency regulation market during period t. G is the total number of units participating in multiple markets.

[0081] Finally, the market clearing constraint is as follows:

[0082]

[0083] In the above formula, It represents the amount of electricity sold by the virtual power plant in the electricity market during period t. Represents the amount of electricity purchased by the virtual power plant in the electricity market during period t. It represents the electricity sales amount reported by the virtual power plant in the electricity market during period t. Represents the amount of electricity purchased by the virtual power plant in the electricity market during period t. It represents the frequency regulation capacity won by the virtual power plant in the frequency regulation market during period t. It represents the frequency regulation mileage won by the virtual power plant in the frequency regulation market during period t. It represents the frequency regulation capacity declared by the virtual power plant in period t. It represents the frequency regulation mileage declared by the virtual power plant in period t. It represents the frequency regulation capacity of the load equipment (unit) that won the bid in the frequency regulation market within the time period t. It represents the frequency regulation mileage of the load equipment (unit) that won the bid in the frequency regulation market during period t. They are the declared frequency regulation capacity, declared frequency regulation mileage, maximum active output, minimum active output and frequency regulation mileage multiplier of conventional units. It is the frequency regulation mileage multiplier of the virtual power plant. The specific value can be determined according to the actual scenario and is not limited in this embodiment of the present invention. and They represent the dual variables of the lower limit and upper limit of the electricity sales of the virtual power plant in the electricity market during period t. and are the dual variables that represent the lower and upper limits of the amount of electricity a virtual power plant can purchase in the electricity market during period t. and are the dual variables representing the lower limit and upper limit of the frequency regulation capacity reported by the virtual power plant in period t. and They represent the dual variables of the lower limit and upper limit of the frequency regulation mileage reported by the virtual power plant in period t. and are the dual variables of the lower and upper limits of the frequency regulation capacity declared by unit k in period t. and are the dual variables of the lower and upper limits of the frequency regulation mileage declared by unit k in period t. and are the dual variables representing the lower and upper limits of VPP frequency regulation mileage; and are the dual variables representing the lower and upper limits of the frequency regulation mileage of unit k. and are the complementary slack dual variables of the power caps sold and purchased by the virtual power plant in period t. and are the dual variables representing the upper and lower limits of the output of unit k in period t. It represents the amount of electricity that the load equipment (unit) bids for in the electricity market during time period t. It represents the maximum amount of electricity sales that the virtual power plant can declare during period t. It represents the maximum amount of electricity that the virtual power plant can declare to purchase during period t.

[0084] Step S103: making decisions and allocating resources for the virtual power plant to participate in multiple markets based on the resource allocation benefit model and the market clearing model.

[0085] Specifically, this embodiment of the present invention solves a resource allocation benefit model and a market clearing model to derive the optimal bidding strategy for virtual power plants participating in the energy and frequency regulation markets, namely, a resource allocation solution. This embodiment of the present invention inputs the virtual power plant's operating parameters, system load, frequency regulation requirements, and application information into the resource allocation benefit model and the market clearing model, introducing the KKT condition and strong duality theory to solve the aforementioned two-layer model. Among them, as an optional embodiment of the present invention, making decisions and configuring resources for virtual power plants to participate in multiple markets based on the resource allocation benefit model and the market clearing model includes: introducing Lagrange multipliers to convert the second constraint of the market clearing model into a Lagrangian function; deriving the Lagrangian function to obtain the marginal cost and market supply and demand balance condition of the market clearing model; through the strong duality principle, converting the second objective function of the market clearing model into a dual problem; using the optimal solution of the dual problem as the third constraint of the resource allocation benefit model, the third constraint includes marginal cost and market supply and demand balance condition; using a linearization method to convert the complementary constraints of the first objective function into a linear form, and converting the product of the dual variable and the decision variable in the first objective function into a linear form to obtain a mixed integer linear programming problem; solving the mixed integer linear programming problem through a target solver to obtain the amount of electricity sold and purchased, the purchase price and selling price of electricity in the electric energy market of the virtual power plant, as well as the frequency regulation capacity, frequency regulation mileage and frequency regulation price in each period of the frequency regulation market.

[0086] Specifically, the embodiment of the present invention introduces Lagrange multipliers, converts the second constraint of the lower model (market clearing model) into a Lagrange function, and derives the function to obtain the necessary conditions of the lower problem, including marginal cost and market supply and demand balance conditions. Secondly, through the principle of strong duality, the lower problem is converted into a dual problem, and its optimal solution is used as the constraint of the upper model (resource allocation benefit model) and introduced into the upper model, thereby converting the original two-layer problem into a single-layer optimization problem. In this process, the first objective function is still to maximize the revenue of the virtual power plant, but the constraints of the upper model add the market supply and demand balance and the marginal cost conditions of the producer. After the conversion to a single-layer model, there are still some nonlinear terms, such as the product of the dual variable and the decision variable in the first objective function, or the complementary slack conditions in the constraints. To linearize the nonlinear terms, a linearization method, such as the Big M method, can be used to convert the complementary constraints into linear form. The product of the dual variable and the decision variable in the first objective function is also converted into linear form. This results in a mixed integer linear programming (MILP) problem, which can be solved using a target solver. The target solver can be Gurobi. In this embodiment of the present invention, the Gurobi solver is used in Matlab software to solve the mixed integer linear programming problem, obtaining the final resource allocation result, i.e., the bidding result. The bidding result includes the amount of electricity sold and purchased by the virtual power plant in the energy market, the purchase and sale prices, as well as the frequency regulation capacity, frequency regulation mileage, and frequency regulation price for each time period in the frequency regulation market. It is worth noting that the principles of the KKT condition and strong duality theory are known in the art and will not be further elaborated herein in this embodiment of the present invention.

[0087] The embodiment of the present invention can collaboratively optimize the maximization of the benefits of virtual power plants participating in the energy market and frequency regulation market and the minimization of market clearing costs through a resource allocation model and a market clearing model, fully consider the close coupling relationship between the energy market and the frequency regulation market, and collaboratively consider the resource allocation of its participation in the energy market or the frequency regulation market, thereby optimizing the collaborative optimization performance of multiple markets, achieving the optimal allocation of resources among different markets, and thus promoting the goal of maximizing benefits. In this way, when the above-mentioned method is used to configure the resources of virtual power plants participating in multiple markets, the collaborative optimization of multiple markets is guaranteed, the resource allocation efficiency of virtual power plants participating in multiple markets is improved, and the reliability of achieving the goal of maximizing benefits is high.

[0088] To demonstrate the effectiveness of the technical solutions provided by the embodiments of the present invention, this paper conducted tests based on an IEEE 14-node system. The virtual power plant consists of a gas turbine, a wind turbine with a rated power of 30 MW, an energy storage system, and a temperature-controlled load cluster. The temperature-controlled load consists of 2,000 air conditioners. The energy storage system in the virtual power plant uses a 30 MW / 150 MWh capacity configuration with a charge-discharge efficiency of 0.95. The initial state of charge (SOC) is set to 0.2, and the SOC is controlled within a range of 20%-80% during operation. The 14-node system has a 24-hour scheduling cycle, with a scheduling time unit of 1 hour. In this embodiment, the user temperature comfort zone is set to [24, 28]°C, and the system's total frequency regulation demand is set to 5% of the load. For ease of analysis, all distributed resources in the virtual power plant are connected to the same node. This embodiment of the present invention assumes the following two different operating scenarios: Scenario 1: The virtual power plant and traditional units participate in multiple markets, while the virtual power plant participates in market bidding only as a generator. Scenario 2: Virtual power plants and traditional units participate in multiple markets, and virtual power plants participate in market bidding as both electricity buyers and generators.

[0089] After setting the above scenarios, a two-layer model is established and solved using the method of the embodiment of the present invention. The optimal bidding strategy for the electric energy market and frequency regulation market of the virtual power plant in each scenario is as follows: Figure 2-4 shown. Figure 2 The resource allocation result of a virtual power plant in the electric energy market provided by an embodiment of the present invention is: Figure 3 The embodiment of the present invention provides a resource allocation result of the frequency regulation capacity of a virtual power plant in the frequency regulation market. Figure 4 This example shows the resource allocation results of a virtual power plant in the frequency regulation market, provided by an embodiment of the present invention. Through the above simulation analysis, a virtual power plant can dynamically adjust its bidding strategy based on multi-market demands in different scenarios. During periods of low electricity prices, the virtual power plant may choose not to sell electricity, while during periods of high prices, it may choose to sell large quantities of electricity. Furthermore, the virtual power plant can increase revenue by providing frequency regulation capacity in the frequency regulation market, thereby improving overall profitability.

[0090] Therefore, through the above-described embodiments of the present invention, a two-tier model is employed to achieve the dual goals of maximizing virtual power plant revenue and minimizing market clearing costs. Virtual power plants can function as both electricity buyers and sellers, flexibly leveraging price differences and fluctuating frequency regulation requirements to dynamically adjust bidding strategies. Compatibility with a variety of distributed resources, such as gas turbines, energy storage systems, wind power, and temperature-controlled loads, optimizes resource allocation for virtual power plants and enhances their market competitiveness.

[0091] Corresponding to the resource allocation method for a virtual power plant participating in multiple markets provided in the above embodiment, based on the same technical concept, an embodiment of the present invention further provides a resource allocation device for a virtual power plant participating in multiple markets, which is used to execute the resource allocation method for a virtual power plant participating in multiple markets. Figure 5 A schematic diagram of a resource allocation device for a virtual power plant participating in multiple markets according to an embodiment of the present invention is provided. Figure 5 As shown, the resource allocation device 500 for a virtual power plant participating in multiple markets includes: a construction module 501 for constructing a resource allocation benefit model for the virtual power plant participating in multiple markets, the resource allocation benefit model including a first objective function and a plurality of first constraints for maximizing the benefit of the virtual power plant, the first objective function being determined based on key parameters of power market transactions in the electric energy market in which the virtual power plant participates, key parameters of the frequency regulation market, compensation costs of load devices, and operating cost parameters of distributed resources; a construction module 501 for constructing a market clearing model for the virtual power plant participating in multiple markets, the market clearing model including a second objective function and a plurality of second constraints for minimizing the clearing costs of multiple markets, the second objective function being determined based on first power market declaration data of load devices in the electric energy market, first frequency regulation declaration data of load devices in the frequency regulation market, key parameters of power market transactions, key parameters of the frequency regulation market, second power market declaration data of the virtual power plant in the electric energy market, and second frequency regulation declaration data of the virtual power plant in the frequency regulation market; and a configuration module 502 for making decisions and configuring resources for the virtual power plant participating in multiple markets based on the resource allocation benefit model and the market clearing model.

[0092] The embodiment of the present invention can collaboratively optimize the maximization of the benefits of virtual power plants participating in the energy market and frequency regulation market and the minimization of market clearing costs through a resource allocation model and a market clearing model, fully consider the close coupling relationship between the energy market and the frequency regulation market, and collaboratively consider the resource allocation of its participation in the energy market or the frequency regulation market, thereby optimizing the collaborative optimization performance of multiple markets, achieving the optimal allocation of resources among different markets, and thus promoting the goal of maximizing benefits. In this way, when the above-mentioned method is used to configure the resources of virtual power plants participating in multiple markets, the collaborative optimization of multiple markets is guaranteed, the resource allocation efficiency of virtual power plants participating in multiple markets is improved, and the reliability of achieving the goal of maximizing benefits is high.

[0093] Optionally, construction module 501 is also used to obtain the electricity sales and purchase amounts won by the virtual power plant in the electric energy market in each time period, the clearing prices of the virtual power plant in the electric energy market and the frequency regulation market in each time period, and the frequency regulation capacity and frequency regulation mileage won by the virtual power plant in the frequency regulation market in each time period; determine the total clearing cost of the virtual power plant for clearing distributed resources based on the electricity sales and purchase amounts, clearing prices, frequency regulation capacity and frequency regulation mileage in each time period; determine the difference between the total clearing cost and the compensation cost and operating cost parameters in each time period, and superimpose the differences in each time period to obtain the first objective function; determine the first constraint condition based on the operating constraint rules of each distributed resource, the operating constraint rules of the load equipment, the power balance constraint rules of the distributed resources of the virtual power plant participating in multiple markets, the capacity declaration constraint rules of the virtual power plant participating in multiple markets, and the price declaration constraint rules of the virtual power plant participating in multiple markets.

[0094] Corresponding to the resource allocation method for a virtual power plant participating in multiple markets provided in the above embodiment, based on the same technical concept, an embodiment of the present invention further provides an electronic device for executing the resource allocation method for a virtual power plant participating in multiple markets. Figure 6 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention is shown in FIG. Figure 6 As shown. Electronic devices may have relatively large differences due to different configurations or performances, and may include one or more processors 601 and memory 602, the memory 602 is used to store computer programs that can be run on the processor 601, and the processor 601 is used to execute the programs stored in the memory 602 to achieve the above Figure 1 The memory 602 may be a temporary storage or a persistent storage. The application stored in the memory 602 may include one or more modules (not shown), each of which may include a series of computer-executable instructions for the electronic device.

[0095] Furthermore, the processor 601 can be configured to communicate with the memory 602 to execute a series of computer-executable instructions in the memory 602 on the electronic device. The electronic device may also include one or more power supplies 603, one or more wired or wireless network interfaces 604, one or more input / output interfaces 605, and one or more keyboards 606.

[0096] Specifically in this embodiment, the electronic device includes a processor, a communication interface, a memory and a communication bus; wherein the processor, the communication interface and the memory communicate with each other through the bus; the memory is used to store computer programs; the processor is used to execute the programs stored in the memory to achieve the above Figure 1The various steps in the method embodiment have the beneficial effects of the above method embodiments. To avoid repetition, the embodiments of the present invention will not be described again here.

[0097] It should be noted that the electronic device provided by the embodiment of the present invention and the resource allocation method for the virtual power plant to participate in multiple markets provided by the embodiment of the present invention are based on the same application concept. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned resource allocation method for the virtual power plant to participate in multiple markets, and has the same or similar beneficial effects, and the repetitions will not be repeated.

[0098] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0099] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A resource allocation method for a virtual power plant to participate in multiple markets, characterized in that: include: Constructing a resource allocation benefit model for a virtual power plant participating in multiple markets, the resource allocation benefit model including a first objective function for maximizing the benefit of the virtual power plant and a plurality of first constraints, wherein the first objective function is determined based on key parameters of power market transactions in the electric energy market in which the virtual power plant participates, key parameters of the frequency regulation market in which the frequency regulation market participates, compensation costs of load equipment, and operating cost parameters of distributed resources; Constructing a market clearing model for the virtual power plant to participate in multiple markets, the market clearing model including a second objective function whose goal is to minimize the clearing costs of the multiple markets and a plurality of second constraints, wherein the second objective function is determined based on first electricity market declaration data of the load device in the electric energy market, first frequency regulation declaration data of the load device in the frequency regulation market, the key electricity market transaction parameters, the key frequency regulation market parameters, second electricity market declaration data of the virtual power plant in the electric energy market, and second frequency regulation declaration data of the virtual power plant in the frequency regulation market; Based on the resource allocation benefit model and the market clearing model, decisions are made and allocations are made on the resources of the virtual power plant participating in multiple markets.

2. The resource allocation method for a virtual power plant to participate in multiple markets according to claim 1, characterized in that: The resource allocation benefit model for building a virtual power plant to participate in multiple markets includes: Obtaining the amount of electricity sold and purchased by the virtual power plant in the electric energy market during each time period, the clearing price of the virtual power plant in the electric energy market and the frequency regulation market during each time period, and the frequency regulation capacity and frequency regulation mileage of the virtual power plant in the frequency regulation market during each time period; Determine the total clearing cost of the virtual power plant for clearing distributed resources based on the electricity sales and electricity purchases in each time period, the clearing price, the frequency regulation capacity, and the frequency regulation mileage; Determining the difference between the total clearing cost and the compensation cost and the operating cost parameter for each time period, and superimposing the differences for each time period to obtain the first objective function; The first constraint condition is determined based on the operating constraint rules of each distributed resource, the operating constraint rules of the load equipment, the power balance constraint rules of the distributed resources of the virtual power plant participating in multiple markets, the capacity declaration constraint rules of the virtual power plant participating in multiple markets, and the price declaration constraint rules of the virtual power plant participating in multiple markets.

3. The resource allocation method for a virtual power plant to participate in multiple markets according to claim 2, characterized in that: The total clearing cost of the virtual power plant for clearing distributed resources based on the electricity sales and electricity purchases in each time period, the clearing price, the frequency regulation capacity, and the frequency regulation mileage includes: Calculating a first difference between the amount of electricity sold and the amount of electricity purchased, and calculating a first product of the first difference and a clearing price time of the virtual power plant in the electric energy market in each time period; Calculating a second product between the clearing price of the frequency regulation capacity of the virtual power plant in the frequency regulation market in each time period and the frequency regulation capacity, and a third product between the clearing price of the frequency regulation mileage of the virtual power plant in the frequency regulation market in each time period and the frequency regulation mileage; Superimposing the first product, the second product, and the third product to obtain a first sum; The first sum values of each time period are added together to obtain the total clearing fee.

4. The resource allocation method for a virtual power plant participating in multiple markets according to claim 1, characterized in that: The construction of the market clearing model for the virtual power plant to participate in multiple markets includes: Determine the total declared cost of the load equipment according to the first power market declaration data and power market winning bid data of each load equipment in the electric energy market in each time period, and the first frequency regulation declaration data and frequency regulation winning bid data of each load equipment in the frequency regulation market; Determine the total declared cost of the virtual power plant according to the key parameters of the power market transactions of the virtual power plant in each time period, the key parameters of the frequency regulation market, the second power market declaration data of the virtual power plant in the electric energy market, and the second frequency regulation declaration data of the virtual power plant in the frequency regulation market; Adding the total declared cost of the load equipment and the total declared cost of the virtual power plant to obtain the second objective function; Each of the second constraints is determined based on the node power balance rules in the virtual power plant, the connection line safety rules between the nodes, the capacity and mileage balance rules of the frequency regulation market, and the market clearing rules of the electric energy market and the frequency regulation market.

5. The resource allocation method for a virtual power plant participating in multiple markets according to claim 4, characterized in that: Determining the total declared cost of the load equipment according to the first power market declaration data and power market winning bid data of each load equipment in the electric energy market in each time period, and the first frequency regulation declaration data and frequency regulation winning bid data of each load equipment in the frequency regulation market includes: Calculate the fourth product between the first power market declaration data of each load device in the electric energy market and the power market winning bid data in each time period, the fifth product between the frequency regulation capacity declaration data of each load device in the first frequency regulation declaration data of the frequency regulation market and the frequency regulation capacity winning bid data, and the sixth product between the frequency regulation mileage declaration data of each load device in the first frequency regulation declaration data of the frequency regulation market and the frequency regulation mileage winning bid data; superimposing the fourth product, the fifth product, and the sixth product to obtain a second sum; The second sum values of each time period are added together to obtain the total declared cost of the load equipment.

6. The resource allocation method for a virtual power plant participating in multiple markets according to claim 4, characterized in that: The determining of the total declared fee of the virtual power plant according to the key power market transaction parameters of the virtual power plant in each time period, the key frequency regulation market parameters, the second power market declaration data of the virtual power plant in the electric energy market, and the second frequency regulation declaration data of the virtual power plant in the frequency regulation market includes: Calculate the seventh product between the electricity sales price in the second electricity market declaration data of the virtual power plant in each time period and the electricity sales volume in the key parameters of the electricity market transaction, the eighth product between the electricity purchase price in the second electricity market declaration data of the virtual power plant in each time period and the electricity purchase volume in the key parameters of the electricity market transaction, the ninth product between the frequency regulation capacity declaration price in the second frequency regulation declaration data and the frequency regulation capacity in the key parameters of the frequency regulation market, and the tenth product between the frequency regulation mileage declaration price in the second frequency regulation declaration data and the frequency regulation mileage in the key parameters of the frequency regulation market; calculating a second difference between the seventh product and the eighth product, and calculating a third sum of the second difference, the ninth product, and the tenth product; The third sum values of each time period are added together to obtain the total declared cost of the virtual power plant.

7. The resource allocation method for a virtual power plant participating in multiple markets according to any one of claims 1 to 6, characterized in that: The making decisions and configuring resources for the virtual power plant to participate in multiple markets based on the resource allocation benefit model and the market clearing model includes: Introducing Lagrange multipliers to transform the second constraint of the market clearing model into a Lagrange function; Derivative the Lagrangian function to obtain the marginal cost and market supply and demand equilibrium conditions of the market clearing model; By using the strong duality principle, the second objective function of the market clearing model is transformed into a dual problem; The optimal solution of the dual problem is used as the third constraint of the resource allocation benefit model, wherein the third constraint includes marginal cost and market supply and demand balance conditions; Using a linearization method to transform the complementary constraint of the first objective function into a linear form, and transforming the product of the dual variable and the decision variable in the first objective function into a linear form, thereby obtaining a mixed integer linear programming problem; The mixed integer linear programming problem is solved by the target solver to obtain the amount of electricity sold and purchased, the electricity purchase price and the electricity selling price of the virtual power plant in the electric energy market, as well as the frequency regulation capacity, frequency regulation mileage and frequency regulation price in each period of the frequency regulation market.

8. A resource allocation device for a virtual power plant to participate in multiple markets, characterized in that: include: A construction module is used to construct a resource allocation benefit model for a virtual power plant participating in multiple markets, wherein the resource allocation benefit model includes a first objective function for maximizing the benefit of the virtual power plant and a plurality of first constraints, wherein the first objective function is determined based on key parameters of power market transactions in the electric energy market in which the virtual power plant participates, key parameters of the frequency regulation market in the frequency regulation market, compensation costs of load equipment, and operating cost parameters of distributed resources; The construction module is further used to construct a market clearing model for the virtual power plant to participate in multiple markets, the market clearing model including a second objective function whose goal is to minimize the clearing costs of the multiple markets and a plurality of second constraints, the second objective function being determined based on the first electricity market declaration data of the load device in the electric energy market, the first frequency regulation declaration data of the load device in the frequency regulation market, the key parameters of the electricity market transactions, the key parameters of the frequency regulation market, the second electricity market declaration data of the virtual power plant in the electric energy market, and the second frequency regulation declaration data of the virtual power plant in the frequency regulation market; A configuration module is used to make decisions and configure the resources of the virtual power plant participating in multiple markets based on the resource configuration benefit model and the market clearing model.

9. The resource allocation device for a virtual power plant participating in multiple markets according to claim 8, characterized in that: The construction module is further used to obtain the amount of electricity sold and purchased by the virtual power plant in the electric energy market during each time period, the clearing price of the virtual power plant in the electric energy market and the frequency regulation market during each time period, and the frequency regulation capacity and frequency regulation mileage of the virtual power plant in the frequency regulation market during each time period; Determine the total clearing cost of the virtual power plant for clearing distributed resources based on the electricity sales and electricity purchases in each time period, the clearing price, the frequency regulation capacity, and the frequency regulation mileage; Determining the difference between the total clearing cost and the compensation cost and the operating cost parameter for each time period, and superimposing the differences for each time period to obtain the first objective function; The first constraint condition is determined based on the operating constraint rules of each distributed resource, the operating constraint rules of the load equipment, the power balance constraint rules of the distributed resources of the virtual power plant participating in multiple markets, the capacity declaration constraint rules of the virtual power plant participating in multiple markets, and the price declaration constraint rules of the virtual power plant participating in multiple markets.

10. An electronic device, characterized in that: include: A processor and a memory; wherein the memory is used to store a computer program that can be run on the processor; A processor is used to execute the program stored in the memory to implement the steps of the resource allocation method for a virtual power plant participating in multiple markets as described in any one of claims 1 to 7.

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