Energy cooperation method considering community shared energy storage and light charging station cluster

Abstract

The invention provides an energy cooperation method considering community shared energy storage and a light charging station cluster, and relates to the technical field of new energy power supply and consumption collaborative optimization. The method comprises the following steps: firstly, acquiring electric vehicle charging demand, photovoltaic output, electricity price and external power grid operation information, constructing a light charging station cost objective function, solving a peak regulation-charging collaborative optimization model, and obtaining electric vehicle charging and discharging power and light charging station electricity purchasing and selling power in each time period; based on the charge state and the charge and discharge cost of the community shared energy storage unit, establishing an optimized operation model of the community shared energy storage unit, and obtaining electric energy interaction power and electricity selling power between the light charging station and the community shared energy storage unit; and constructing a cooperative alliance income model by combining optimization results of both parties, introducing alliance total income, electric energy contribution degree and cost saving amount into an asymmetric Nash negotiation income distribution model, determining bargaining weight, and obtaining an income distribution share and an electric energy sharing price. According to the invention, the photovoltaic absorption capability and the safety of the power distribution network can be improved.

Description

Technical Field

[0001] This invention relates to the field of new energy power supply and consumption coordination optimization technology, and in particular to an energy cooperation method that considers community-shared energy storage and photovoltaic charging station clusters. Background Technology

[0002] With the increasing global adoption of electric vehicles (EVs), the impact of EV charging load on the power system is becoming more and more significant, especially during peak periods when grid load is high. Due to the randomness and concentration of EV charging load, it can easily lead to excessive localized grid loads, resulting in power supply imbalances and grid instability. Particularly during peak hours, the concentrated charging activity of EVs can exacerbate grid pressure and affect the overall reliability of the power system.

[0003] Currently, some charging strategies, such as time-based pricing-based optimized charging strategies, while reducing grid load pressure to some extent, still rely on users actively following charging schedules and do not fully consider user satisfaction and charging experience. Meanwhile, the intermittency and instability of photovoltaic power generation systems also pose challenges to the operation of photovoltaic electric vehicle charging stations.

[0004] Community-based shared energy storage, as a novel energy management approach, aims to balance supply and demand and improve energy efficiency by storing excess renewable energy through centralized energy storage facilities and distributing it when needed. However, existing shared energy storage systems are mainly limited to optimizing capacity allocation and energy trading, and have not yet addressed how to fairly distribute benefits based on the contributions of different photovoltaic charging stations and energy storage systems. Problems include: 1. The randomness and concentration of electric vehicle charging loads place excessive pressure on the power grid; 2. Existing charging strategies rely on active user participation and lack consideration for user satisfaction; 3. The synergistic optimization of photovoltaic power generation and electric vehicle charging stations has not been fully realized, and the fairness of power distribution cannot be addressed; 4. The unfair benefit distribution mechanism of shared energy storage systems fails to effectively incentivize participants. Summary of the Invention

[0005] To overcome the shortcomings of existing technologies, the purpose of this invention is to provide an energy cooperation method that considers community-shared energy storage and photovoltaic charging station clusters. This method not only significantly improves the photovoltaic absorption capacity and the safety of the distribution network operation, but also ensures the fairness and rationality of the distribution of benefits among the participating entities, thereby constructing a sustainable multi-entity energy cooperation system.

[0006] To achieve the above objectives, the present invention provides the following solution: An energy cooperation method considering community-shared energy storage and photovoltaic charging station clusters, applied to a system including multiple photovoltaic charging stations, community-shared energy storage units, and an external power grid, the method comprising: The system acquires information on electric vehicle charging demand, photovoltaic output, electricity price, and external power grid operation at each photovoltaic charging station. It constructs a cost objective function for photovoltaic charging stations that includes electricity purchase and sale costs, electricity sharing costs, and electric vehicle user satisfaction. Under the conditions of satisfying the constraints of photovoltaic output, electric vehicle power status, and power balance, it establishes and solves a peak-shaving-charging collaborative optimization model to obtain the electric vehicle charging and discharging power and the electricity purchase and sale power of photovoltaic charging stations at each time period. Based on the state of charge and charging / discharging cost of the community shared energy storage unit, and combined with the power interaction relationship with each photovoltaic charging station and the external power grid, an optimized operation model of the community shared energy storage unit is established and solved to obtain the power interaction power between the photovoltaic charging station and the community shared energy storage unit and the power sold by the community shared energy storage unit in each time period. Based on the solution results of the cost objective function of the photovoltaic charging station and the optimized operation model of the community shared energy storage unit, a cooperative alliance revenue model is constructed. The total alliance revenue, the energy contribution of each photovoltaic charging station and the cost savings are substituted into the asymmetric Nash negotiation revenue distribution model to determine the bargaining weight of each participating party. The revenue distribution share and corresponding energy sharing price between the photovoltaic charging station and the community shared energy storage unit are then obtained.

[0007] Preferably, the cost objective function of the photovoltaic charging station is composed of the cost of purchasing electricity from the external grid at each time period, the revenue from selling electricity to the external grid at each time period, the cost of sharing electricity between the photovoltaic charging station and the community-shared energy storage unit at each time period, and the user satisfaction of various types of electric vehicles at each time period. The cost objective function of the photovoltaic charging station is obtained by summing the cost of purchasing electricity from the external grid at each time period, the revenue from selling electricity to the external grid at each time period, the cost of sharing electricity between the photovoltaic charging station and the community-shared energy storage unit at each time period, and the user satisfaction of various types of electric vehicles at each time period over the entire scheduling cycle.

[0008] Preferably, the electric vehicle user satisfaction is divided according to electric vehicle category. The charging time, charging price and charging power of each type of electric vehicle in each time period are used as input variables to set a corresponding unit satisfaction value for each type of electric vehicle. The numerical value of electric vehicle user satisfaction is obtained by summing the charging and discharging satisfaction values ​​of each type of electric vehicle in each time period.

[0009] Preferably, in the peak shaving-charging collaborative optimization model, electric vehicle charging and discharging power constraints are set for each type of electric vehicle to ensure that the electric vehicle charging and discharging power of each type of electric vehicle in each time period does not exceed the corresponding maximum charging and discharging power. The parking status indicator variable is used to distinguish whether the electric vehicle is parked at the photovoltaic charging station. At the same time, upper and lower limits are set for the electric vehicle power status of each type of electric vehicle to make the electric vehicle power status change between a preset minimum power status and a preset maximum power status.

[0010] Preferably, in the peak shaving-charging collaborative optimization model, the time evolution of the electric vehicle's power state is jointly determined by the initial power state, the electric vehicle's charging and discharging power at each time period, and the charging and discharging efficiency factor. Furthermore, when the electric vehicle leaves the solar charging station, a constraint is set that the terminal power state is not lower than the preset departure power state to ensure the electric vehicle's usage needs when leaving the station.

[0011] Preferably, in the peak shaving-charging collaborative optimization model, upper and lower limits of photovoltaic power generation are set to ensure that the photovoltaic power generation of the photovoltaic charging station at each time does not exceed the corresponding upper limit of photovoltaic power generation and is not lower than the lower limit of photovoltaic power generation. The power balance constraint of the photovoltaic charging station ensures that the sum of photovoltaic power generation, electric vehicle charging and discharging power of various types of electric vehicles, power purchased and sold by the photovoltaic charging station to the external power grid, and power exchange between the photovoltaic charging station and the community shared energy storage unit meets the power balance of the photovoltaic charging station in each time period.

[0012] Preferably, the energy sharing cost between the photovoltaic charging station and the community shared energy storage unit is obtained by summing the product of the energy transaction volume of each photovoltaic charging station and the community shared energy storage unit in each time period and the corresponding unit energy price over the entire scheduling cycle. When the energy transaction volume is positive, it means that the photovoltaic charging station obtains energy from the community shared energy storage unit, and when the energy transaction volume is negative, it means that the photovoltaic charging station supplies energy to the community shared energy storage unit.

[0013] Preferably, the optimized operation model of the community shared energy storage unit is constructed with the community shared energy storage cost model as the objective function. The community shared energy storage cost model consists of the charging and discharging cost of the community shared energy storage unit, the transaction cost between the community shared energy storage unit and the external power grid, and the energy sharing cost between the community shared energy storage unit and the photovoltaic charging station. In the optimized operation model of the community shared energy storage unit, the initial state of charge, the change of state of charge in each time period, and the upper and lower limits of the state of charge are set for the state of charge of the community shared energy storage unit. At the same time, the terminal state of charge is limited to not be lower than the initial state of charge.

[0014] Preferably, in the optimized operation model of the community shared energy storage unit, the charging and discharging power of the community shared energy storage unit is limited by a preset maximum charging power and a preset maximum discharging power, and the transaction power between the community shared energy storage unit and the external power grid satisfies the non-negativity constraint, allowing the community shared energy storage unit to sell excess electricity to the external power grid without purchasing electricity from the external power grid. Through the power balance constraint of the community shared energy storage unit, the sum of the charging and discharging power of the community shared energy storage unit, the power sold to the external power grid, and the power exchange between the community shared energy storage unit and each photovoltaic charging station is kept in balance at each time period.

[0015] Preferably, the asymmetric Nash negotiation revenue distribution model uses the weighted product of the differences between the total revenue of the alliance obtained from the cooperative alliance revenue model and the benchmark revenue of each participating party as the optimization objective. The bargaining weight is determined by the amount of electricity contribution of each photovoltaic charging station in the cooperation process, the change in the electricity sharing cost between the photovoltaic charging station and the community shared energy storage unit, and the amount of savings in the cost objective function value of the photovoltaic charging station. The asymmetric Nash negotiation revenue distribution model satisfies the individual rationality constraint of each participating party and the collective rationality constraint of the total alliance revenue remaining unchanged. The revenue distribution share obtained by solving is used to back-calculate the electricity sharing price between the photovoltaic charging station and the community shared energy storage unit.

[0016] The present invention discloses the following technical effects: This invention overcomes the shortcomings of previous technologies that relied solely on time-of-use pricing and struggled to balance grid security and user experience by simultaneously incorporating the electricity purchase cost, electricity sales revenue, electricity sharing cost between the photovoltaic charging station and the community-shared energy storage unit, as well as electric vehicle user satisfaction, into the objective function of photovoltaic charging station costs. It also constructs a peak-shaving-charging collaborative optimization model.

[0017] This invention overcomes the shortcomings of previous technologies where photovoltaic electric vehicle charging stations were often optimized locally from the perspective of a single station or single load, and no collaborative operation mechanism was formed in the peak-shaving-charging collaborative optimization model. It achieves the beneficial effects of smoothing the load curve at the cluster level, improving the photovoltaic output following capability, and increasing the safety margin of the distribution network operation.

[0018] This invention constructs an optimized operation model for community-shared energy storage units with a community-shared energy storage cost model as the objective function. Within this model, the electrical energy interaction relationships between the community-shared energy storage units, each photovoltaic charging station, and the external power grid are explicitly modeled. Under state of charge and power constraints, the electrical energy interaction power between the photovoltaic charging station and the community-shared energy storage units, as well as the electricity sales power of the community-shared energy storage units, are solved. This overcomes the shortcomings of previous technologies that only considered the revenue of a single operating entity and ignored the energy synergy between community-shared energy storage and photovoltaic charging stations. It improves the local absorption capacity of photovoltaic power generation, reduces photovoltaic curtailment, and lowers the overall system electricity purchase cost.

[0019] This invention introduces an asymmetric Nash negotiation profit distribution model on the basis of the cooperative alliance profit model, and maps the total alliance profit, electricity contribution, and cost savings to the bargaining weight of each participant. This overcomes the shortcomings of the background technology, which uses fixed electricity prices or proportional allocation based on electricity consumption, and makes it difficult to reflect the differentiated contributions of different photovoltaic charging stations and community-shared energy storage units. It realizes an asymmetric profit distribution mechanism in which the greater the electricity contribution and cost savings of the photovoltaic charging station, the higher its bargaining weight and the larger its profit distribution share. This is conducive to maintaining a long-term stable cooperative relationship among multiple parties.

[0020] This invention overcomes the problem in the prior art that the operation decision and economic incentives are separated and difficult to implement in engineering by forming a clear integrated design framework of "operation optimization - energy coordination - revenue distribution" by combining the peak-shaving-charging collaborative optimization model, the community shared energy storage unit optimization operation model and the asymmetric Nash negotiation revenue distribution model. The resulting decision quantities, such as the electric vehicle charging and discharging power, the power purchased and sold by the photovoltaic charging station, the power of power interaction between the photovoltaic charging station and the community shared energy storage unit, and the power sharing price, can be directly used for dispatch execution and business settlement, thereby taking into account grid security, renewable energy utilization and the economic benefits of all parties. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 A flowchart of the method provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the overall system framework provided in an embodiment of the present invention. Detailed Implementation

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

[0024] The purpose of this invention is to provide an energy cooperation method that considers community-shared energy storage and photovoltaic charging station clusters. By constructing a three-in-one collaborative mechanism of peak shaving and charging synergy optimization of photovoltaic charging station clusters, optimized operation of community-shared energy storage, and asymmetric Nash revenue distribution, the overall coordination and benefit integration of photovoltaic power output, energy storage regulation, and electric vehicle charging behavior are achieved.

[0025] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0026] Figure 1 The method flowchart provided in the embodiments of the present invention is as follows: Figure 1 As shown, this invention provides an energy cooperation method considering community-shared energy storage and photovoltaic charging station clusters, applicable to systems including multiple photovoltaic charging stations, community-shared energy storage units, and an external power grid. The method includes: Step 100: Obtain information on electric vehicle charging demand, photovoltaic output, electricity price, and external power grid operation for each photovoltaic charging station. Construct a cost objective function for photovoltaic charging stations that includes electricity purchase and sale costs, electricity sharing costs, and electric vehicle user satisfaction. Under the conditions of satisfying the constraints of photovoltaic output, electric vehicle power status, and power balance, establish and solve a peak-shaving-charging collaborative optimization model to obtain the electric vehicle charging and discharging power and the electricity purchase and sale power of photovoltaic charging stations for each time period. Step 200: Based on the state of charge and charging / discharging cost of the community shared energy storage unit, and combined with the power interaction relationship with each photovoltaic charging station and the external power grid, establish and solve the optimized operation model of the community shared energy storage unit to obtain the power interaction power between the photovoltaic charging station and the community shared energy storage unit and the power sold by the community shared energy storage unit in each time period. Step 300: Based on the solution results of the cost objective function of the photovoltaic charging station and the optimized operation model of the community shared energy storage unit, construct the cooperative alliance revenue model. Substitute the total alliance revenue, the energy contribution of each photovoltaic charging station and the cost savings into the asymmetric Nash negotiation revenue distribution model to determine the bargaining weight of each participating party. Solve to obtain the revenue distribution share and corresponding energy sharing price between the photovoltaic charging station and the community shared energy storage unit.

[0027] This embodiment provides an energy cooperation framework based on community-shared energy storage and photovoltaic charging station clusters. It aims to improve electric vehicle charging efficiency, optimize the allocation of photovoltaic and energy storage resources, and ensure fair cooperation and profit distribution among multiple stakeholders through peak-shaving-charging collaborative optimization strategies and asymmetric Nash negotiation profit-sharing mechanisms. The specific steps include: 1. Optimized scheduling of electric vehicle charging load: By coordinating the charging load of multiple photovoltaic charging stations through an intelligent scheduling system, charging is ensured during off-peak hours, thereby reducing the load pressure on the power grid during peak hours.

[0028] 2. Coordinated energy scheduling between photovoltaic charging stations and community shared energy storage: Photovoltaic charging stations and shared energy storage systems achieve effective storage and release of photovoltaic power through intelligent scheduling, optimizing grid load.

[0029] 3. Profit-sharing mechanism based on asymmetric Nash negotiation: By considering the contributions of each participant, the benefits in the cooperation process are fairly distributed using an asymmetric bargaining method.

[0030] The overall system framework is as follows Figure 2 As shown in the figure, this embodiment proposes a cooperative game-theoretic optimization scheduling model comprising three photovoltaic charging stations (referred to as photovoltaic charging station 1, photovoltaic charging station 2, and photovoltaic charging station 3) and one community-shared energy storage unit. Each photovoltaic charging station can engage in bidirectional energy interaction with the shared energy storage system and can also unidirectionally output energy to the external power grid. Specifically, the photovoltaic charging stations centrally manage excess energy through the photovoltaic power generation system and achieve energy interaction with the shared energy storage and the external power grid through an effective cooperative game-theoretic scheduling strategy.

[0031] The photovoltaic charging station module is located at the front end of the system. Each charging station is directly connected to the shared energy storage unit, allowing excess photovoltaic energy to be stored in the shared energy storage unit through a bidirectional energy transmission channel. Simultaneously, the charging station also has the ability to connect to the external power grid, but only to sell energy to the grid, thereby generating revenue in the event of excess photovoltaic energy. The community shared energy storage unit, as the core component of the system, uses a flexible energy management mechanism to store and release energy with the charging stations, achieving energy balance and optimized management of the local system.

[0032] The external power grid is located at the edge of the system, serving only as an absorber of excess energy from the photovoltaic charging stations, accepting power output from each station. The power grid does not participate in the direct energy storage process, nor does it interact with the shared energy storage units. Through this design, the system can effectively achieve rational scheduling among photovoltaic power generation, energy storage, and the external power grid.

[0033] Furthermore, the technical approach of this embodiment includes: Step 1: Optimization and scheduling of electric vehicle charging load, executed by the intelligent scheduling system (computer equipment and control system).

[0034] The steps are described as follows: (1) Data collection: Through sensors and communication systems, the charging needs, charging duration, charging power of electric vehicle users, and load status of photovoltaic charging stations are collected. The scheduling system predicts future charging demand and formulates scheduling strategies based on real-time grid load and charging status of charging stations.

[0035] (2) Off-peak charging guidance: Based on the electricity price model and grid load, optimize the charging time period and guide electric vehicles to charge during off-peak hours.

[0036] (3) Dynamically adjust charging load: The dispatching system dynamically adjusts the charging power of each photovoltaic charging station based on the charging demand of electric vehicles and the real-time load of the power grid, thereby reducing the charging load during peak hours.

[0037] The key steps serve the following purposes: Reduce grid load pressure: By optimizing the charging time of electric vehicles, especially by guiding charging to take place during off-peak hours, the grid load during peak periods can be effectively reduced, alleviating the problem of grid load imbalance.

[0038] Enhance user experience: Through intelligent scheduling, optimize the electric vehicle charging process, reduce waiting time during peak hours, and improve user charging satisfaction.

[0039] Step 2: Coordinated energy scheduling between photovoltaic charging stations and community shared energy storage, with the intelligent scheduling system, photovoltaic charging stations, and community shared energy storage system as the main implementing entities.

[0040] The steps are described as follows: (1) Energy interaction mode: The excess electricity generated by the photovoltaic power generation system is stored in the shared energy storage system, and the charging and discharging characteristics of the energy storage system are used to balance the power demand.

[0041] (2) Scheduling and control: The intelligent scheduling system optimizes the energy flow between the photovoltaic charging station and the shared energy storage based on the grid demand, the power generation capacity of the photovoltaic charging station and the energy storage status, and releases the stored electrical energy during the peak period of grid load to avoid grid overload.

[0042] (3) Energy balance between photovoltaic charging station and energy storage system: Ensure that the energy interaction between photovoltaic charging station and shared energy storage is balanced, avoid overcharging or over-discharging of energy storage system, and take into account battery health management and charging and discharging efficiency.

[0043] The key steps serve the following purposes: Improving the utilization rate of photovoltaic power generation: By storing excess photovoltaic power in a shared energy storage system, the waste of photovoltaic power generation is effectively avoided.

[0044] Power grid load balancing: During peak power grid periods, releasing stored electrical energy effectively reduces power grid load pressure and improves the stability and reliability of the power system.

[0045] Step 3: Based on the asymmetric Nash negotiation, the distribution of benefits is carried out by the intelligent scheduling system, photovoltaic charging stations, and community shared energy storage.

[0046] The steps are described as follows: (1) Calculate energy contribution: Monitor the energy interaction between the photovoltaic charging station and the shared energy storage through the scheduling system, and calculate the amount of energy provided by each photovoltaic charging station during the cooperation process.

[0047] (2) Asymmetric Bargaining Model: Based on the contribution of the photovoltaic charging station to the system, an asymmetric Nash negotiation model is used for revenue distribution. The more electricity the photovoltaic charging station provides, the stronger its bargaining power in revenue distribution.

[0048] (3) Profit distribution: Based on the contribution and bargaining power of each optical charging station, the profits in the cooperation are distributed through an asymmetric bargaining model to ensure that the interests of each participant are maximized.

[0049] The key steps serve the following purposes: Fair revenue distribution: The asymmetric bargaining model distributes revenue based on the contributions of each party, ensuring that each optical charging station receives fair revenue according to its actual contribution.

[0050] Incentivize participants: Enhance cooperation between photovoltaic charging stations and shared energy storage systems through reasonable revenue distribution, thereby improving the overall efficiency of the system.

[0051] As an example, in the electric vehicle solar charging station model established in this embodiment, the objective function for the solar charging station cost is set as a trade-off between the electricity purchase cost, electricity sales revenue, and user satisfaction. The specific form is as follows: (1) in, To reduce the cost of the optical charging station, and Is The electricity purchase and sale price of the Shikeguang charging station from the grid and for The Shikeguang charging station purchases and sells electricity from the power grid. The cost of sharing electricity between photovoltaic charging stations and communities for energy storage. This represents the sum of the utility functions related to electric vehicle user satisfaction.

[0052] The specific formula for the energy sharing cost between photovoltaic charging stations and community-shared energy storage is as follows: (2) in, For optical charging station Shared energy storage with the community During the period The amount of electricity traded at that time. If optical charging station Sharing energy storage with the community If energy is obtained, then the stored energy is shared with the community; otherwise, it is not. Supplying electrical energy. Indicates optical charging station Requires interaction power The price paid per unit of electricity. (Optical charging station) Shared energy storage with the community This set of cooperative alliances is defined as That is, and .

[0053] The utility function for electric vehicle charging and discharging satisfaction in this embodiment is described below: In economics, the utility function describes consumer satisfaction across different combinations of goods or services. The calculation of electric vehicle charging and discharging satisfaction is also based on this concept, using the utility function to measure user preferences for charging time, cost, and charging power. The utility function can be defined as the sum of charging satisfaction values ​​for each type of electric vehicle at different time periods, calculated as follows: (3) (4) in, It is the first The unit utility value of electric vehicles represents the user's assessment of the value of each unit, in units of... .

[0054] Furthermore, the photovoltaic power generation model in this embodiment is constrained as follows: (5) In the formula, for Time Light Charging Station The photovoltaic power generation; , These are the upper and lower limits of photovoltaic power generation. Specifically, the charging and discharging power constraints in this implementation are as follows: The charging and discharging power of each type of electric vehicle should not exceed its rated power to protect the safety of the battery and charging equipment. The constraints are as follows: (6) (7) in, and They represent the first electric vehicles at all times The charging and discharging power, Indicates the first electric vehicles at all times Whether it stops at the optical charging station, and These represent the maximum charging and discharging power for each type of vehicle.

[0055] Furthermore, the electric vehicle battery capacity constraint in this embodiment is as follows: The state of charge of an electric vehicle battery should be maintained at to In order to extend battery life and ensure the vehicle can run normally, This represents the charge / discharge efficiency factor. Its specific form is: (8) in, For battery capacity, For the first electric vehicles at all times The state of the battery (SOC).

[0056] Optionally, the power state constraints in this embodiment are as follows: There is a continuous relationship between the initial state of charge of each type of electric vehicle and its state of charge during its stay at the charging station: (1) Initial power status: (9) (2) Changes in battery status during the period from leaving the photovoltaic charging station: (10) (3) Battery capacity constraints when leaving the solar charging station: (11) Specifically, the upper limit constraint on the purchase and sale of electricity for the optical charging station in this embodiment is as follows: The electricity purchased and sold by photovoltaic charging stations is subject to upper limits at any given time to ensure the stability of the power system. (12) (13) in, and These represent the electricity purchased and sold by the optical charging station, respectively. Let be a binary variable, representing the time interval [time]. The status of electricity purchase and sale on the power grid.

[0057] Optionally, the power balance constraint in this embodiment is as follows: At any given time, the power input and output of a charging station should remain balanced. This condition can be described as follows: (14) in, Indicates the first day of each day The number of electric vehicles served by each charging station. It is the first The proportion of electric vehicles indicates the percentage of users of this type of electric vehicle within the solar charging station. For optical charging station Shared energy storage with the community Total interactive power.

[0058] make For optical charging station Shared energy storage with the community The total price payable during the interaction.

[0059] When the entire system engages in cooperative game theory, the photovoltaic charging stations and community-shared energy storage participating in electricity trading must satisfy both energy sharing balance constraints and transaction payment balance constraints: (15) (16) Optionally, the community-shared energy storage model in this embodiment is described as follows: The expression for the community-shared energy storage cost model is as follows: (17) in, Represents the cost of community-shared energy storage charging and discharging. Represents the community's shared energy storage and external grid transaction costs. This represents the cost of sharing electricity between community-shared energy storage and photovoltaic charging stations.

[0060] The expression for the charging and discharging cost of community-shared energy storage is: (18) in, This is the cost factor per unit of charge / discharge power. This item represents the sum of the charge / discharge costs of the community-shared energy storage equipment over its entire operating cycle.

[0061] The expression for the transaction cost with the external power grid is: (19) This item represents the revenue generated from selling excess electricity to the external power grid by community-shared energy storage devices. It is a moment The price of electricity sold to external power grids.

[0062] The expression for the energy sharing cost of community-shared energy storage and photovoltaic charging stations is: (20) in Shared energy storage for the community With optical charging station During the period The amount of electricity traded at that time. If Community-shared energy storage Xiangguang charging station To gain energy, or conversely, to recharge the light station. Supplying electrical energy. Indicates community-shared energy storage Interactive power consumption The price paid per unit of electricity.

[0063] Specifically, the energy storage state of charge constraints are described as follows: The state of charge (SOC) of a community-shared energy storage system needs to be maintained within a reasonable range to ensure the safe operation of the system and the health of the energy storage batteries.

[0064] (1) Initial state of charge (twenty one) This is the initial state of charge (i.e., the amount of electricity at the initial moment) of the community-shared energy storage. This formula describes the state of charge after the initial moment. It increases or decreases the current charge / discharge power based on the initial state, taking into account charging efficiency. ) and discharge efficiency ( The impact of ) and For detailed values, please refer to the appendix. (2) Changes in state of charge at different time periods: (twenty two) in, This represents the state of charge for the next time period. This formula implies that the change in the energy storage state depends on the state of charge of the previous time period and the current charging and discharging behavior.

[0065] (3) Upper and lower limits of charge state constraints: (twenty three) The energy storage state of charge must always be maintained and This is to ensure the safe operation of the battery and avoid overcharging and over-discharging.

[0066] (twenty four) Among these requirements, the state of charge in the final period must not be lower than the initial state, which ensures that the energy storage device still has a certain amount of electricity reserve after long-term operation.

[0067] Furthermore, the expression for the charging and discharging power constraint of the community-shared energy storage device is as follows: The charging and discharging power of energy storage devices is limited by their physical components, specifically: (25) , (26) and These are the maximum charging and maximum discharging power, respectively. This constraint ensures that the charging and discharging behavior of the energy storage device is within its design capacity and will not cause overload or damage to the device.

[0068] Optionally, the electrical energy interaction constraints are described as follows: In this collaborative alliance between photovoltaic charging stations and community-shared energy storage, CES will prioritize consuming its own generated energy. When there is a surplus of electricity, CES will choose to sell the excess power to the external grid to generate revenue. However, to reduce the system's dependence on the external grid and the cost of electricity purchases, CES will only perform internal balancing when necessary and will not purchase electricity from external sources. Therefore, the non-negativity constraint of CES's transaction volume with the external grid is as follows: (27) in, The amount of electricity sold to the power grid.

[0069] Furthermore, the power balance constraints for community-shared energy storage are as follows: At any given time, the charging and discharging of the energy storage system, the sale of electricity to the external power grid, and the energy exchange with photovoltaic charging stations must meet the requirements of energy balance. (28) In the implementation of this invention, the intelligent scheduling system, as the core execution entity, is responsible for uniformly collecting information on electric vehicle charging demand, photovoltaic power generation output, electricity prices, and external power grid operation from photovoltaic charging stations. Based on this, it executes a peak-shaving-charging collaborative optimization model and a community-shared energy storage optimized operation model. Through solving the above models, the intelligent scheduling system generates the electric vehicle charging and discharging power, the photovoltaic charging station's power purchase and sale, and the power exchange between the photovoltaic charging station and the community-shared energy storage unit for each time period. The photovoltaic charging station and the community-shared energy storage unit execute specific operations according to the instructions issued by the intelligent scheduling system, including charging and discharging electric vehicles, purchasing and selling electricity from the external power grid, and performing bidirectional energy sharing. This ensures that electric vehicles smoothly handle charging loads while meeting their power demand, and fully utilizes photovoltaic output to alleviate peak power pressure.

[0070] The three core steps in this invention correspond to different functional objectives. The first step optimizes the charging and discharging behavior of electric vehicles at different times, guiding charging to avoid peak loads and fill valleys, thereby effectively reducing peak loads and improving the operational safety of the distribution network. The second step, through energy collaborative scheduling between photovoltaic charging stations and community-shared energy storage units, prioritizes the use of photovoltaic power generation for local energy storage, improving photovoltaic utilization and reducing curtailment. The third step, through an asymmetric Nash negotiation benefit distribution model, determines the bargaining weights of each party based on the amount of electricity contributed and the cost savings, ensuring a fair and reasonable distribution of benefits between photovoltaic charging stations and community-shared energy storage units, forming a sustainable multi-party cooperation mechanism. These steps together constitute the overall operational logic of this invention, achieving an integrated implementation effect of operational optimization, energy collaboration, and economic incentives.

[0071] This invention optimizes the coordinated energy scheduling of electric vehicle charging load, photovoltaic charging stations, and shared energy storage through an intelligent scheduling system, and utilizes asymmetric Nash negotiation for fair revenue distribution, thus solving several problems in existing technologies. This solution not only improves energy efficiency and reduces grid load pressure, but also enhances the willingness of system participants to cooperate through a reasonable revenue distribution mechanism, providing a new solution for the efficient operation of multi-entity energy systems.

[0072] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0073] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. An energy cooperation method considering community-shared energy storage and photovoltaic charging station clusters, characterized in that, The method, applicable to systems including multiple photovoltaic charging stations, community-shared energy storage units, and external power grids, includes: The system acquires information on electric vehicle charging demand, photovoltaic output, electricity price, and external power grid operation at each photovoltaic charging station. It constructs a cost objective function for photovoltaic charging stations that includes electricity purchase and sale costs, electricity sharing costs, and electric vehicle user satisfaction. Under the conditions of satisfying the constraints of photovoltaic output, electric vehicle power status, and power balance, it establishes and solves a peak-shaving-charging collaborative optimization model to obtain the electric vehicle charging and discharging power and the electricity purchase and sale power of photovoltaic charging stations at each time period. Based on the state of charge and charging / discharging cost of the community shared energy storage unit, and combined with the power interaction relationship with each photovoltaic charging station and the external power grid, an optimized operation model of the community shared energy storage unit is established and solved to obtain the power interaction power between the photovoltaic charging station and the community shared energy storage unit and the power sold by the community shared energy storage unit in each time period. Based on the solution results of the cost objective function of the photovoltaic charging station and the optimized operation model of the community shared energy storage unit, a cooperative alliance revenue model is constructed. The total alliance revenue, the energy contribution of each photovoltaic charging station and the cost savings are substituted into the asymmetric Nash negotiation revenue distribution model to determine the bargaining weight of each participating party. The revenue distribution share and corresponding energy sharing price between the photovoltaic charging station and the community shared energy storage unit are then obtained.

2. The energy cooperation method considering community-shared energy storage and photovoltaic charging station clusters according to claim 1, characterized in that, The target cost function for the photovoltaic charging station is composed of the cost of purchasing electricity from the external grid at each time period, the revenue from selling electricity to the external grid at each time period, the cost of sharing electricity between the photovoltaic charging station and the community-shared energy storage unit at each time period, and the user satisfaction of various types of electric vehicles at each time period. The target cost function is obtained by summing the cost of purchasing electricity from the external grid at each time period, the revenue from selling electricity to the external grid at each time period, the cost of sharing electricity between the photovoltaic charging station and the community-shared energy storage unit at each time period, and the user satisfaction of various types of electric vehicles at each time period over the entire scheduling cycle.

3. The energy cooperation method considering community-shared energy storage and photovoltaic charging station clusters according to claim 1, characterized in that, The electric vehicle user satisfaction is divided according to electric vehicle category. The charging time, charging price and charging power of each type of electric vehicle in each time period are used as input variables. A corresponding unit satisfaction value is set for each type of electric vehicle. The numerical value of electric vehicle user satisfaction is obtained by summing the charging and discharging satisfaction values ​​of each type of electric vehicle in each time period.

4. The energy cooperation method considering community-shared energy storage and photovoltaic charging station clusters according to claim 1, characterized in that, In the peak shaving-charging collaborative optimization model, electric vehicle charging and discharging power constraints are set for each type of electric vehicle to ensure that the charging and discharging power of each type of electric vehicle does not exceed the corresponding maximum charging and discharging power in each time period. The parking status indicator variable is used to distinguish whether the electric vehicle is parked at the photovoltaic charging station. At the same time, upper and lower limits are set for the electric vehicle power status of each type of electric vehicle to make the electric vehicle power status change between the preset minimum power status and the preset maximum power status.

5. The energy cooperation method considering community-shared energy storage and photovoltaic charging station clusters according to claim 1, characterized in that, In the peak shaving-charging collaborative optimization model, the temporal evolution of the electric vehicle's power state is jointly determined by the initial power state, the electric vehicle's charging and discharging power at each time period, and the charging and discharging efficiency factor. When the electric vehicle leaves the solar charging station, a constraint is set that the terminal power state is not lower than the preset departure power state to ensure the electric vehicle's usage needs when leaving the station.

6. The energy cooperation method considering community-shared energy storage and photovoltaic charging station clusters according to claim 1, characterized in that, In the peak-shaving-charging collaborative optimization model, upper and lower limits are set for photovoltaic power generation to ensure that the photovoltaic power generation of the photovoltaic charging station at each time does not exceed the corresponding upper limit and is not lower than the lower limit. The power balance constraint of the photovoltaic charging station ensures that the sum of photovoltaic power generation, electric vehicle charging and discharging power of various types of electric vehicles, power purchased and sold by the photovoltaic charging station to the external power grid, and power exchange between the photovoltaic charging station and the community shared energy storage unit meets the power balance of the photovoltaic charging station in each time period.

7. The energy cooperation method considering community-shared energy storage and photovoltaic charging station clusters according to claim 1, characterized in that, The cost of energy sharing between photovoltaic charging stations and community shared energy storage units is obtained by summing the product of the energy transaction volume of each photovoltaic charging station and the community shared energy storage unit in each time period and the corresponding unit price of energy over the entire scheduling cycle. When the energy transaction volume is positive, it means that the photovoltaic charging station obtains energy from the community shared energy storage unit, and when the energy transaction volume is negative, it means that the photovoltaic charging station supplies energy to the community shared energy storage unit.

8. The energy cooperation method considering community-shared energy storage and photovoltaic charging station clusters according to claim 1, characterized in that, The optimized operation model of the community shared energy storage unit is constructed with the community shared energy storage cost model as the objective function. The community shared energy storage cost model consists of the charging and discharging cost of the community shared energy storage unit, the transaction cost between the community shared energy storage unit and the external power grid, and the energy sharing cost between the community shared energy storage unit and the photovoltaic charging station. In the optimized operation model of the community shared energy storage unit, the initial state of charge, the change of state of charge in each time period, and the upper and lower limits of the state of charge are set for the state of charge of the community shared energy storage unit. At the same time, it is limited that the terminal state of charge is not lower than the initial state of charge.

9. The energy cooperation method considering community-shared energy storage and photovoltaic charging station clusters according to claim 8, characterized in that, In the optimized operation model of the community shared energy storage unit, the charging and discharging power of the community shared energy storage unit is limited by the preset maximum charging power and the preset maximum discharging power. The transaction power between the community shared energy storage unit and the external power grid satisfies the non-negativity constraint, allowing the community shared energy storage unit to sell excess electricity to the external power grid without purchasing electricity from the external power grid. Through the power balance constraint of the community shared energy storage unit, the sum of the charging and discharging power of the community shared energy storage unit, the power sold to the external power grid, and the power exchange with each photovoltaic charging station is kept in balance at each time period.

10. The energy cooperation method considering community-shared energy storage and photovoltaic charging station clusters according to claim 8, characterized in that, The asymmetric Nash negotiation revenue distribution model uses the weighted product of the difference between the total revenue of the alliance obtained from the cooperative alliance revenue model and the benchmark revenue of each participating party as the optimization objective. The bargaining weight is determined by the amount of electricity contribution of each photovoltaic charging station in the cooperation process, the change in the electricity sharing cost between the photovoltaic charging station and the community shared energy storage unit, and the amount of savings in the cost objective function value of the photovoltaic charging station. The asymmetric Nash negotiation revenue distribution model satisfies the individual rationality constraint of each participating party and the collective rationality constraint of the total alliance revenue remaining unchanged. The revenue distribution share obtained by solving is used to back-calculate the electricity sharing price between the photovoltaic charging station and the community shared energy storage unit.

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