Energy storage battery efficiency guarantee value optimization method and device based on master-slave game, equipment and storage medium

Abstract

The invention provides an energy storage battery efficiency guarantee value optimization method and device based on a master-slave game, equipment and a storage medium, and the method comprises the steps: S1, determining a leader and a follower according to a participant of an energy storage power station; s2, pre-allocating an efficiency guarantee value of each key device of each follower to the leader, and initially determining a required value of the efficiency guarantee of each follower within a boundary condition range of performance requirements of the leader; s3, determining the unit price of the follower efficiency value according to the key efficiency value given by the leader; s4, according to the optimal pricing scheme proposed by each follower in the current stage and the benefit function of the leader, determining the distribution scheme of the efficiency guarantee value of the leader in the next stage; and S5, iterating the steps S3 to S4 for multiple times until convergence is achieved, and obtaining an optimal efficiency guarantee value under a balance condition. According to the method, the negotiation process of the owner party and the supplier party is described by constructing the performance guarantee value optimization model based on the master-slave game, so that the win-win situation of the owner party and the supplier party is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of new energy, and particularly relates to an optimization method, device, equipment and storage medium for the efficiency guarantee value of energy storage batteries based on principal-agent game. Background Art

[0002] The efficiency assessment for overseas energy storage projects is becoming increasingly stringent. However, there is no clear definition for the efficiency allocation among manufacturers. In particular, the costs associated with improving the efficiency of different devices vary. Therefore, by allocating the efficiency of each device, the overall system efficiency can be enhanced and the cost can be optimized. Summary of the Invention

[0003] The first object of the present invention is to provide an optimization method for the efficiency guarantee value of energy storage batteries based on principal-agent game, aiming at the deficiencies in the prior art.

[0004] To achieve the above object, the following technical solutions are adopted in the present invention:

[0005] An optimization method for the efficiency guarantee value of energy storage batteries based on principal-agent game includes the following steps:

[0006] S1. Determine the leader and the followers according to the participants in the energy storage power station;

[0007] S2. For the efficiency guarantee values of each key device pre-allocated by the leader to each follower, initially determine the required values of the efficiency guarantee for each follower within the boundary conditions of the leader's performance requirements;

[0008] S3. Determine the unit price of the follower's efficiency value based on the key efficiency value given by the leader;

[0009] S4. Determine the allocation scheme of the leader's next-round efficiency guarantee value according to the optimal pricing scheme proposed by each follower in this round and the benefit function of the leader;

[0010] S5. Through multiple iterations of steps S3 to S4 until convergence, the optimal efficiency guarantee value under the equilibrium condition is obtained. The convergence condition is that the benefit function does not change between this round and the next round.

[0011] While adopting the above technical solutions, the present invention can also adopt or combine the following technical solutions:

[0012] As a preferred technical solution of the present invention: In step S1, the leader is determined as the owner, and the followers are determined as the suppliers of key devices in the energy storage system.

[0013] As a preferred technical solution of the present invention: In step S2, the followers are the suppliers of key devices in the energy storage system, and the required value of the pre-allocated key device efficiency is Among them: represents the efficiency value requirement of the battery under the j-th allocation, represents the efficiency value requirement of the inverter under the j-th allocation, represents the efficiency value requirement of the transformer under the j-th allocation;

[0014] Considering the overall efficiency requirement of the energy storage system required by the leader and the maximum efficiency value that the equipment can achieve, the following boundary conditions are obtained:

[0015]

[0016] In the above formula, represents the efficiency value requirement of the battery under the j-th allocation, represents the efficiency value requirement of the inverter under the j-th allocation, represents the efficiency value requirement of the transformer under the j-th allocation, p req is the actually required efficiency value, p imin and p imax are respectively the maximum and minimum efficiency values that the i-th type of equipment can achieve under actual conditions.

[0017] As a preferred technical solution of the present invention: in step S3, the unit price is:

[0018]

[0019] In the above formula, m1, m2, and m3 are respectively the competitiveness of the battery product, the competitiveness of the inverter product, and the competitiveness of the transformer product. If the market competition is more intense, the m i value is larger, and its sensitivity to price is higher. p1, p2, and p3 are respectively the efficiency value requirements of the battery product, the efficiency value requirements of the inverter product, and the efficiency value requirements of the transformer product. k1, k2, and k3 are respectively the battery product pricing, the inverter product pricing, and the transformer product pricing.

[0020] As a preferred technical solution of the present invention: in step S4, the benefit function is:

[0021]

[0022] In the above formula, p1, p2, and p3 are respectively the efficiency value requirements of the battery product, the efficiency value requirements of the inverter product, and the efficiency value requirements of the transformer product. k1, k2, and k3 are respectively the battery product pricing, the inverter product pricing, and the transformer product pricing. A is the average price in the market for different efficiency requirements.

[0023] The second object of the present invention is to provide an optimization device for the efficiency guarantee value of an energy storage battery based on master-slave game in view of the deficiencies existing in the prior art.

[0024] To achieve the above object, the present invention adopts the following technical solutions:

[0025] An optimization device for the efficiency guarantee value of energy storage batteries based on master-slave game, comprising the following units:

[0026] A participant determination unit, which is used to determine the leader and the follower according to the participants in the energy storage power station;

[0027] An iterative initialization unit, which is used to pre-allocate the efficiency guarantee values of each key device of the leader to each follower;

[0028] A follower unit pricing determination unit, which is used to determine the unit pricing of the follower efficiency value according to the key efficiency value given by the leader;

[0029] A distribution unit for the efficiency guarantee value of the next round, which is used to determine the distribution plan of the efficiency guarantee value of the leader in the next round according to the optimal pricing plan proposed by each follower in this stage and the benefit function of the leader

[0030] An iterative solution unit, which is used to iteratively solve according to the information of the follower unit pricing determination unit and the distribution unit for the efficiency guarantee value of the next round until convergence to obtain the optimal efficiency guarantee value under the equilibrium condition.

[0031] The third object of the present invention is to provide an electronic device in view of the deficiencies in the prior art.

[0032] To achieve the above object, the present invention adopts the following technical solutions:

[0033] An electronic device, comprising a processor, a communication interface, a memory and a communication bus, and the processor, the communication interface and the memory complete the communication with each other through the communication bus. The characteristics are as follows:

[0034] A memory, which is used to store computer programs,

[0035] A processor, which is used to execute the computer programs stored on the memory to implement the steps of the optimization method for the efficiency guarantee value of the energy storage battery based on master-slave game as described above.

[0036] Another object of the present invention is to provide a computer-readable storage medium in view of the deficiencies in the prior art.

[0037] To achieve the above object, the present invention adopts the following technical solutions:

[0038] A computer-readable storage medium, characterized in that: a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the optimization method for the efficiency guarantee value of the energy storage battery based on the master-slave game as described above are realized.

[0039] The present invention provides an optimization method, device, equipment and storage medium for the efficiency guarantee value of an energy storage battery based on a master-slave game, which associates the efficiency guarantee value of the energy storage system with benefits, and describes the negotiation process between the owner (leader) and the supplier (follower) by constructing an optimization model for the performance guarantee value based on the master-slave game, so as to obtain the optimal value-taking strategies of both parties for the performance guarantee value and achieve a win-win situation for both parties. Description of the Drawings

[0040] Figure 1 It is a flowchart of the optimization method for the efficiency guarantee value of the energy storage battery based on the master-slave game provided by the present invention. Detailed Embodiments

[0041] The present invention will be further described in detail with reference to the accompanying drawings and specific embodiments.

[0042] An optimization method for the efficiency guarantee value of an energy storage battery based on a master-slave game includes the following steps:

[0043] S1. Determine the leader and the follower according to the participants in the energy storage power station, where the leader is the owner and the follower is the supplier of key equipment in the energy storage system, mainly including batteries, PCS, transformers, etc. The owner meets the efficiency requirements of the entire energy storage system by assigning different efficiency requirements to the follower. The equipment industrial party will determine the benefit function based on the cost of the product and the risk of replaceability according to the efficiency requirements assigned by the owner, so as to adjust the cost adjustment strategy and feedback it to the leader to correct the leader's efficiency allocation requirements, so as to achieve a balance between the leader and the follower.

[0044] S2. The owner, as the leader, pre-assigns the efficiency value requirements of each key equipment to each key equipment manufacturer. In general energy storage projects, the key equipment manufacturers mainly include three companies: batteries, inverters and transformers. Therefore, the pre-assigned efficiency value requirements of key equipment are where represents the efficiency value requirement of the battery under the jth allocation, represents the efficiency value requirement of the inverter under the jth allocation, represents the efficiency value requirement of the transformer under the jth allocation. Considering the overall efficiency requirement of the energy storage system required by the owner and the maximum efficiency value that the equipment can reach, the following boundary conditions are obtained.

[0045]

[0046] In the above formula, represents the efficiency value requirement of the battery under the j-th allocation, represents the efficiency value requirement of the inverter under the j-th allocation, represents the efficiency value requirement of the transformer under the j-th allocation, p req is the actually required efficiency value, p imin and p imax are respectively the maximum and minimum efficiency values that the i-th device can achieve under actual conditions.

[0047] S3. As a follower, the equipment manufacturer will determine the unit price of the efficiency value based on the key efficiency value given by the owner. Assume the unit price given by the manufacturer is where represents the unit price of the battery manufacturer under the j-th cycle, represents the unit price of the PCS manufacturer under the j-th cycle, represents the unit price of the transformer manufacturer under the j-th cycle. For the equipment manufacturer, the higher the unit price, the higher the profit, but the greater the probability of being replaced by similar products. Therefore, the benefit function of the equipment manufacturer can be expressed as:

[0048]

[0049] In the above formula, m i is the supply price elasticity of the i-th key equipment. For equipment with more intense competition in the same category, the supply price elasticity value is larger, and the probability of the product being replaced is more sensitive to price fluctuations. When its value is 1, it means that the equipment is a single-source equipment and has no substitutability. represents the efficiency value requirement of the battery under the j-th allocation, represents the efficiency value requirement of the inverter under the j-th allocation, represents the efficiency value requirement of the transformer under the j-th allocation. For the j-th cycle, the optimal pricing of the follower is

[0050]

[0051] In the above formula, m i is the supply price elasticity of the i-th key equipment. For equipment with more intense competition in the same category, the supply price elasticity value is larger, and the probability of the product being replaced is more sensitive to price fluctuations. When its value is 1, it means that the equipment is a single-source equipment and has no substitutability. represents the efficiency value requirement of the battery under the j-th allocation, represents the efficiency value requirement of the inverter under the j-th allocation, represents the efficiency value requirement of the transformer under the j-th allocation. Among them represents the unit price of the battery manufacturer under the j-th cycle, Denote the unit price of the PCS manufacturer under the j-th cycle, and denote the unit price of the transformer manufacturer under the j-th cycle. Denote it as

[0052] S4. At this time, the owner will determine the optimal efficiency value allocation plan for the next stage according to the optimal pricing plans proposed by each equipment manufacturer and the power generation revenue. For the owner, its revenue is mainly to improve the efficiency guarantee values of each part of the manufacturers, thereby reducing the charge and discharge losses of the energy storage power station, and then improving the overall revenue. However, it is also necessary to consider the different payment costs for each manufacturer due to different efficiency guarantee values. Therefore, the revenue function of the owner is:

[0053]

[0054] In the above formula, p1, p2, and p3 are the efficiency value requirements for battery products, inverter products, and transformer products respectively, and k1, k2, and k3 are the battery product pricing, inverter product pricing, and transformer product pricing respectively. A is the average price in the market for different efficiency requirements.

[0055] At this time, the optimal efficiency guarantee value problem of the owner can be described by the following model.

[0056]

[0057] In the above formula, denotes the efficiency value requirement of the battery under the (j + 1)-th allocation, denotes the efficiency value requirement of the inverter under the (j + 1)-th allocation, denotes the efficiency value requirement of the transformer under the (j + 1)-th allocation, p req is the actually required efficiency value, p imin and p imax are the maximum and minimum efficiency values that the i-th device can achieve under actual conditions respectively.

[0058] Substitute Equation (3) into Equation (5) to obtain the Hessian matrix of the function U owner (P, K) is strictly negative definite. Therefore, the optimization problem of the owner has a maximum value. To solve this problem, transform this model into:

[0059]

[0060] In the above formula, denotes the efficiency value requirement of the battery under the (j + 1)-th allocation, denotes the efficiency value requirement of the inverter under the (j + 1)-th allocation, denotes the efficiency value requirement of the transformer under the (j + 1)-th allocation, p reqis the actual required efficiency value, p imin and p imax are respectively the maximum and minimum efficiency values that the i-th device can achieve under actual conditions.

[0061] It can be considered that both the objective function and the constraint function of the optimization problem are convex functions. At this time, the problem of the owner solving the optimal efficiency guarantee value is transformed into a convex optimization problem. Since this problem satisfies the Slater condition, the original problem and its dual problem have strong duality, that is, the optimal solution of the dual problem is the optimal solution of the original problem. For equation (6), its dual problem is where:

[0062]

[0063] In the above formula, represents the efficiency value requirement of the battery under the (j + 1)-th allocation, represents the efficiency value requirement of the inverter under the (j + 1)-th allocation, represents the efficiency value requirement of the transformer under the (j + 1)-th allocation, p req is the actual required efficiency value, p imin and p imax are respectively the maximum and minimum efficiency values that the i-th device can achieve under actual conditions.

[0064] The optimal solution of the dual problem can be obtained by the gradient descent method.

[0065] S5. Through multiple iterative steps from S3 to S4 until convergence, the optimal efficiency guarantee value under the balanced condition is obtained, and the convergence condition is that the benefit function no longer changes between this round and the next round.

[0066] The present invention also provides an optimization device for the efficiency guarantee value of an energy storage battery based on a leader-follower game, including the following units:

[0067] A participant determination unit, which is used to determine the leader and the follower according to the participants of the energy storage power station;

[0068] An iterative initialization unit, which is used to pre-allocate the efficiency guarantee values of each key device of the leader to each follower;

[0069] A follower unit pricing determination unit, which is used to determine the unit pricing of the follower efficiency value according to the key efficiency value given by the leader;

[0070] A next-round efficiency guarantee value allocation unit, which is used to determine the allocation scheme of the leader's next-round efficiency guarantee value according to the optimal pricing scheme proposed by each follower in this stage and the benefit function of the leader

[0071] An iterative solution unit, which is configured to determine information of a follower unit pricing determination unit and an allocation unit of the next-round efficiency guarantee value, and perform iterative solution until convergence to obtain an optimal efficiency guarantee value under equilibrium conditions.

[0072] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications to these embodiments once they learn the basic creative concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments and all changes and modifications falling within the scope of the present invention.

[0073] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. An optimization method for the guaranteed efficiency value of energy storage batteries based on master-slave game, characterized in that: The method for optimizing the efficiency guarantee value of an energy storage battery based on a master-slave game includes the following steps: S1. Determine the leader and the followers according to the participants in the energy storage power station; S2. For the efficiency guarantee values of each key device pre-allocated by the leader to each follower, initially determine the required values of the efficiency guarantee for each follower within the boundary conditions of the leader's performance requirements; S3. Determine the unit price of the follower's efficiency value based on the key efficiency value given by the leader; S4. Determine the allocation scheme of the leader's next-round efficiency guarantee value according to the optimal pricing scheme proposed by each follower in this round and the leader's benefit function; S5. Through multiple iterations of steps S3 to S4 until convergence, so as to obtain the optimal efficiency guarantee value under the equilibrium condition, and the convergence condition is that the benefit function does not change between this round and the next round.

2. The optimization method for the guaranteed efficiency value of an energy storage battery based on master-slave game according to claim 1, characterized in that: In step S1, the leader is determined as the owner, and the followers are determined as the suppliers of key devices in the energy storage system.

3. The optimization method for the guaranteed efficiency value of energy storage batteries based on master-slave game according to claim 1, characterized in that: In step S2, the follower is the supplier of key equipment in the energy storage system, and the required efficiency value of the pre-allocated key equipment is Wherein: represents the required efficiency value of the battery under the j-th allocation, represents the required efficiency value of the inverter under the j-th allocation, represents the required efficiency value of the transformer under the j-th allocation; Considering the overall efficiency requirement of the energy storage system required by the leader and the maximum efficiency value that the device can achieve, the following boundary conditions are obtained: where i = 1, 2, 3 In the above formula, represents the efficiency value requirement of the battery under the j-th allocation, represents the efficiency value requirement of the inverter under the j-th allocation, represents the efficiency value requirement of the transformer under the j-th allocation, p req is the actually required efficiency value, p imin and p imax are respectively the maximum and minimum efficiency values that the i-th device can achieve under actual conditions.

4. The optimization method for the guaranteed efficiency value of an energy storage battery based on master-slave game according to claim 1, wherein: In step S3, the unit price is: In the above formula, m1, m2, and m3 are the competitiveness of battery products, the competitiveness of inverter products, and the competitiveness of transformer products respectively. If the market competition is more intense, the i larger the value of m, the higher its sensitivity to price; p1, p2, and p3 are the efficiency value requirements for battery products, inverter products, and transformer products respectively, and k1, k2, and k3 are the pricing of battery products, inverter products, and transformer products respectively.

5. The optimization method for the guaranteed value of the energy storage battery efficiency based on the master-slave game according to claim 1, wherein: In step S4, the benefit function is: In the above formula, p1, p2, and p3 are respectively the requirements for the efficiency value of the battery product, the requirements for the efficiency value of the inverter product, and the requirements for the efficiency value of the transformer product, and k1, k2, and k3 are respectively the pricing of the battery product, the pricing of the inverter product, and the pricing of the transformer product; A is the average price in the market for different efficiency requirements.

6. An optimization device for the guaranteed efficiency value of energy storage batteries based on master-slave game, characterized in that: The device for optimizing the efficiency guarantee value of an energy storage battery based on a master-slave game includes the following units: A participant determination unit, which is used to determine the leader and the followers according to the participants in the energy storage power station; An iterative initialization unit, which is used to pre-allocate the efficiency guarantee values of each key device from the leader to each follower; A follower unit price determination unit, which is used to determine the unit price of the follower's efficiency value based on the key efficiency value given by the leader; A next-round efficiency guarantee value allocation unit, which is used to determine the allocation scheme of the leader's next-round efficiency guarantee value according to the optimal pricing scheme proposed by each follower in this stage and the leader's benefit function; An iterative solution unit, which is used to iteratively solve according to the information of the follower unit price determination unit and the next-round efficiency guarantee value allocation unit until convergence to obtain the optimal efficiency guarantee value under the equilibrium condition.

7. An electronic device, the electronic device includes a processor, a communication interface, a memory, and a communication bus, and the processor, the communication interface, and the memory complete mutual communication through the communication bus. Its characteristics are as follows: A memory, which is used to store a computer program; A processor, which is used to execute the computer program stored on the memory to implement the steps of the method for optimizing the efficiency guarantee value of an energy storage battery based on a master-slave game according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the steps of the method for optimizing the guaranteed value of the energy storage battery efficiency based on the master-slave game as described in any one of claims 1-5.

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