Cooperative scheduling and income distribution method for energy storage power stations in alliance chain

Abstract

The invention provides a collaborative scheduling and income distribution method for energy storage power stations in an alliance chain, and belongs to the technical field of energy storage power stations. The method comprises the steps of constructing an energy storage capacity sharing alliance block chain taking the energy storage power stations as nodes; an intelligent contract is constructed, the intelligent contract comprises a mathematical model for solving the shared scheduling plan, and the benefit of the shared capacity of each energy storage power station under the optimal shared scheduling plan is obtained based on the intelligent contract; each energy storage power station solves the shared scheduling plan through real-time information, the smart contract compares the earnings under the shared scheduling plans to obtain the shared scheduling plan with the maximum total earnings as the optimal shared scheduling plan, and each energy storage power station executes the optimal shared scheduling plan. And the maximization of the total capacity is realized.

Description

Technical Field

[0001] This invention belongs to the field of energy storage power station technology, and in particular relates to a method for collaborative scheduling and revenue distribution of energy storage power stations within a consortium blockchain. Background Technology

[0002] As the global energy structure transitions towards low-carbon and clean energy, the proportion of renewable energy sources such as wind and solar power continues to rise. However, renewable energy generation is characterized by significant randomness and volatility. Deviations in power forecasting can lead to problems such as grid frequency fluctuations and power imbalances, affecting the safe and stable operation of the power system. Energy storage stations, with their flexible charging and discharging characteristics, have become a key means to stabilize renewable energy fluctuations and enhance grid regulation capabilities.

[0003] When independently addressing renewable energy power deviations, individual energy storage power stations face challenges such as frequent charge-discharge switching, high energy losses, limited regulation capabilities, and poor economic performance. Currently, the coordinated operation of multiple energy storage stations is considered an effective way to improve regulatory capabilities and reduce operating costs.

[0004] Traditional methods for coordinating the operation of energy storage stations primarily employ a centralized scheduling model with a master-slave control strategy. In this approach, the dispatch center collects operational data from each energy storage station and stores it in a central database. Profit sharing typically uses a fixed-ratio split model, requiring operational verification by a third-party organization. However, traditional methods for coordinating the operation of energy storage stations face challenges such as information barriers and a lack of trust, making it difficult for energy storage power stations to maximize their profits.

[0005] Therefore, this invention provides a method for collaborative scheduling and revenue distribution of energy storage power stations within a consortium blockchain. Summary of the Invention

[0006] This invention provides a method for the coordinated scheduling and revenue distribution of energy storage power stations within a consortium blockchain, which at least solves the problem that energy storage power stations are difficult to maximize their revenue in the prior art.

[0007] In a first aspect, embodiments of this application provide a method for the coordinated scheduling of energy storage power stations within a consortium blockchain, the method comprising: The method includes: Construct a blockchain alliance for sharing energy storage capacity with energy storage power stations as nodes; Construct a smart contract containing a mathematical model for solving the shared scheduling plan, and obtain the revenue of the shared capacity of each energy storage power station under the optimal shared scheduling plan based on the smart contract; Each energy storage power station solves the shared scheduling plan through real-time information. The smart contract compares the benefits under each shared scheduling plan and obtains the shared scheduling plan with the highest total benefit as the optimal shared scheduling plan. Each energy storage power station executes the optimal shared scheduling plan.

[0008] Furthermore, based on smart contracts, the benefits of shared capacity among various energy storage power stations under the optimal shared scheduling plan are obtained, including: Establish an energy storage power station model to describe the relationship between the installed capacity, charge / discharge rate, charge / discharge efficiency, state of charge, and charge / discharge power of the energy storage power station. Establish power output models for wind turbines and photovoltaic modules to obtain the deviation between predicted and actual power generation values; Based on the deviation between the predicted and actual power generation values, the opportunity cost of each energy storage power station is calculated. Based on the deviation between the predicted and actual power generation and the opportunity cost of each energy storage power station, the total revenue of the shared capacity of energy storage power stations in the consortium blockchain is calculated.

[0009] Furthermore, each energy storage power station solves the shared scheduling plan using real-time information. The smart contract compares the revenue under each shared scheduling plan, and the shared scheduling plan with the highest total revenue is the optimal shared scheduling plan. The maximum total revenue expression for each energy storage power station executing the optimal shared scheduling plan is: (twenty one) in, This represents the optimization objective of maximizing the shared profits of total capacity. This represents the total revenue generated from the shared capacity of several energy storage power stations. Indicates the first The charging and discharging power of an energy storage power station , This represents the power loss of the power grid. Indicates the first The power deviation between the actual power generation and the predicted power generation of a wind turbine , Indicates the first The power deviation between the actual power generation and the predicted power generation of each photovoltaic module , This indicates the total number of energy storage power stations. This indicates the total number of wind power stations. This indicates the total number of photovoltaic power plants. Indicates the running time The service relationship of wind power stations Indicates the running time The service relationship of photovoltaic module power plants. Indicates the time of execution No. The state of charge of an energy storage power station This indicates the charging and discharging efficiency of the energy storage power station. Indicates the first The installed capacity of an energy storage power station Indicates the first The charge / discharge rate of an energy storage power station.

[0010] Furthermore, the relationship between the installed capacity, charge / discharge rate, charge / discharge efficiency, state of charge, and charge / discharge power of an energy storage power station is expressed as follows: (1) in, This indicates the installed capacity of the energy storage power station. This indicates the charge / discharge rate of the energy storage power station. This indicates the charging and discharging efficiency of the energy storage power station. Indicates the state of charge of the energy storage power station. This indicates the charging and discharging power of the energy storage power station; Indicates discharge. Indicates charging; The relationship between charge / discharge efficiency and charge / discharge power is expressed as follows: (2) in, This indicates the real-time charge and discharge rate of the energy storage power station. The formula for energy loss during charging and discharging in the operation of an energy storage power station is: (3) in, This indicates the energy loss during charging and discharging of the energy storage power station; The state of charge formula for an energy storage power station is: (4) in, It is the interval between execution times. This indicates the current state of charge of the energy storage power station. This indicates the state of charge of the energy storage power station at the previous moment.

[0011] Furthermore, power output models for wind turbines and photovoltaic modules are established to obtain the deviation between the predicted and actual power generation values, specifically including: For wind turbines, the power output formula is: (5) in, This indicates the actual power generation capacity of the wind turbine. Indicates wind speed; For photovoltaic modules, the power output formula is: (6) in, This indicates the actual power generation of the photovoltaic module. Indicates solar radiation intensity; The power deviations between the actual and predicted power generation of wind turbines and photovoltaic modules are as follows: , (7) in, This indicates the power deviation between the actual power output and the predicted power output of a wind turbine. This indicates the power deviation between the actual power generation of a photovoltaic module and its predicted power generation. This indicates the predicted power generation capacity of the wind turbine. This indicates the predicted power generation of the photovoltaic module.

[0012] Furthermore, based on the deviation between the predicted and actual power generation values, the opportunity cost of each energy storage power station is calculated, specifically including: The formula for calculating the operating revenue of an energy storage power station is as follows: (8) in, This indicates the operating revenue of the energy storage power station. express The charging and discharging power of the energy storage power station at all times. express The purchase and sale price of electricity at any given time; Assuming the predicted power output of wind power plants and photovoltaic modules matches the actual power output, then the entire installed capacity of energy storage power stations is used for peak shaving, and the expression for peak shaving revenue is: (9) in, This represents revenue within a peak-shaving cycle. Indicates peak electricity price, This indicates the off-peak electricity price; Due to the discrepancy between the predicted and actual power generation, the power discharged during peak electricity price periods is shifted to other periods, reducing discharge revenue. The expression for this revenue reduction is: (10) The discrepancy between the predicted and actual power generation results in charging power shifting from off-peak electricity price periods to other periods, increasing charging costs. The expression for this cost increase is: (11) in, express Income that is constantly decreasing express The cost increases constantly; Before joining a capacity-sharing consortium blockchain, the opportunity cost of operating an energy storage power station is expressed as: (12).

[0013] Furthermore, based on the deviation between the predicted and actual power generation values ​​and the opportunity cost of each energy storage power station, the total revenue from the shared capacity of energy storage power stations in the consortium blockchain is calculated, specifically including: The expression for the total revenue from capacity sharing of energy storage power stations in a consortium blockchain is: (13) in, This represents the total benefits of capacity sharing. This represents the opportunity cost of sharing the capacity of several energy storage power stations. This indicates the energy loss in the power grid caused by the shared operation mode; Under the capacity-sharing model, the power balance equation for renewable energy power plants and energy storage power plants that include wind power and photovoltaic power generation is expressed as: (14) in, This indicates the power loss of the power grid; The cost of energy loss on the power grid can be expressed as: (15).

[0014] Secondly, a method for distributing benefits applied to the collaborative scheduling method described above, the method comprising: A revenue distribution model for each energy storage power station is constructed based on its installed capacity, opportunity cost, and actual cost. The total revenue of the alliance is then distributed to each energy storage power station based on this revenue distribution model.

[0015] Furthermore, the revenue distribution model for energy storage power stations is expressed as follows: (16) (17) (18) (19) (20) in, This represents the percentage of revenue used to reward the optimal shared scheduling plan. This indicates the weight of factors contributing to installed capacity. This indicates the weight of the opportunity cost contribution factor before sharing. This indicates the weight of the opportunity cost contribution factor after sharing. This indicates the profit sharing based on the capacity of the energy storage power station. Indicates the factors contributing to installed capacity. This indicates the opportunity cost contribution factor before sharing. Indicates the contribution factor of opportunity cost after sharing.

[0016] Furthermore, the method also includes optimizing the revenue distribution weights using a revenue distribution weight optimization model when changing the consensus nodes in the consortium blockchain. The expression for the revenue distribution weight optimization model is: (twenty two) in, This represents the optimization objective that minimizes the variance of the cost reduction rate of the energy storage power station itself. Calculate the capacity share profit of energy storage power stations under the revenue distribution weights before the change of the consortium blockchain; Calculate the capacity share profit of energy storage power stations under the revenue distribution weight after the change of the consortium blockchain; Compare the capacity sharing profits of the energy storage power stations before and after the change to the consortium blockchain. If the capacity sharing profits of the energy storage power stations after the change to the consortium blockchain are higher than those before the change, then each energy storage power station accepts the change; otherwise, each energy storage power station rejects the change.

[0017] As can be seen from the above technical solutions, the present invention has the following advantages: The collaborative scheduling method for energy storage power stations within a consortium blockchain provided in this application constructs an energy storage capacity sharing consortium blockchain with energy storage power stations as nodes; and constructs a mathematical model that includes solving the shared scheduling plan, realizing revenue calculation based on smart contracts. Each energy storage power station first solves the plan, and the smart contract compares the revenue under each shared scheduling plan. The shared scheduling plan with the largest total revenue is the optimal shared scheduling plan. Each energy storage power station executes the optimal shared scheduling plan, thereby ensuring that the total revenue of the entire system is maximized under the shared capacity mode, and improving the economic efficiency of the energy storage power station.

[0018] By constructing a revenue distribution model for energy storage power stations and allocating the total revenue of shared capacity based on factors such as the installed capacity, opportunity cost, and actual cost of each energy storage power station, a fairer distribution of the total capacity sharing profit is achieved.

[0019] Based on consortium blockchain, energy storage power stations can share data and operate collaboratively in a decentralized environment, breaking down information barriers in the traditional centralized scheduling model, enhancing trust and cooperation among energy storage power stations, promoting efficient collaborative operation of the entire energy storage power station network, and improving the overall performance and stability of the system. Attached Figure Description

[0020] To more clearly illustrate the technical solution of this application, the accompanying drawings used in the description will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a diagram of a blockchain architecture for a shared alliance of energy storage power stations, as shown in one embodiment of the present invention.

[0022] Figure 2 This is a node diagram of a power station in an IEEE 33-node power system according to an embodiment of the present invention.

[0023] Figure 3 This is a schematic diagram illustrating typical daily wind and solar power generation and their prediction deviations in one embodiment of the present invention.

[0024] Figure 4 This is a schematic diagram of the peak-shaving charging and discharging scheme and the state of charge of the energy storage element in an embodiment of the present invention.

[0025] Figure 5 This is a schematic diagram illustrating the annual costs and profits of a consortium blockchain in one embodiment of the present invention.

[0026] Figure 6 This is a schematic diagram illustrating the annual cost and profit of an energy storage power station in one embodiment of the present invention. Detailed Implementation

[0027] To make the purpose, features, and advantages of this application more apparent and understandable, specific embodiments and accompanying drawings will be used to clearly and completely describe the technical solution protected by this application. Obviously, the embodiments described below are only some embodiments of this application, and not all embodiments. Based on the embodiments in this patent, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this patent.

[0028] This application provides a method for collaborative scheduling and revenue distribution of energy storage power stations within a consortium blockchain. It addresses the current urgent need for a method to handle frequent charge-discharge switching, significant energy loss, and poor economic efficiency when individual energy storage power stations independently address prediction deviations in renewable energy power generation. A power output model for wind turbines and photovoltaic modules is established to obtain the deviation between the predicted and actual power generation values. Based on this deviation, the opportunity cost of each energy storage power station is calculated, enabling a more accurate calculation of the station's operating costs. To achieve a fairer distribution of total capacity-sharing profits, the reduction in peak-shaving revenue caused by renewable energy power station power deviations is considered the opportunity cost of capacity sharing. The difference between the opportunity cost of the capacity-sharing mode and the opportunity cost of the independent operation mode is used as the total capacity-sharing profit. Furthermore, by assigning different weights to the installed capacity cost, energy loss cost, and opportunity cost of the energy storage power station, the total capacity-sharing profit is distributed to each energy storage station.

[0029] The technical solutions proposed in the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0030] Figure 1 This application provides a collaborative scheduling method for energy storage power stations within a consortium blockchain, illustrating a shared consortium blockchain architecture for energy storage power stations. The method includes: constructing a shared energy storage capacity consortium blockchain with energy storage power stations as nodes; Construct a smart contract containing a mathematical model for solving the shared scheduling plan, and obtain the revenue of the shared capacity of each energy storage power station under the optimal shared scheduling plan based on the smart contract; Each energy storage power station solves the shared scheduling plan through real-time information. The smart contract compares the benefits under each shared scheduling plan and obtains the shared scheduling plan with the highest total benefit as the optimal shared scheduling plan. Each energy storage power station executes the optimal shared scheduling plan.

[0031] By setting energy storage power stations as consensus nodes of the consortium blockchain and constructing smart contracts containing shared scheduling plans, revenue calculation based on smart contracts is realized. After each energy storage power station executes the shared scheduling plan, the smart contract can automatically compare and select the scheduling plan with the largest total revenue and apply it to each energy storage power station, thereby ensuring that the total revenue of the entire system is maximized under the shared capacity mode and improving the economic efficiency of energy storage power stations.

[0032] The architecture of the consortium blockchain enables energy storage power stations to share data and operate collaboratively in a decentralized environment, breaking down information barriers in the traditional centralized scheduling model, enhancing trust and cooperation among energy storage power stations, promoting efficient collaborative operation of the entire energy storage power station network, and improving the overall performance and stability of the system.

[0033] Based on smart contracts, the benefits of shared capacity among energy storage power stations under the optimal shared scheduling plan are obtained, including: Establish an energy storage power station model to describe the relationship between the installed capacity, charge / discharge rate, charge / discharge efficiency, state of charge, and charge / discharge power of the energy storage power station. Establish power output models for wind turbines and photovoltaic modules to obtain the deviation between predicted and actual power generation values; Based on the deviation between the predicted and actual power generation values, the opportunity cost of each energy storage power station is calculated. Based on the deviation between the predicted and actual power generation and the opportunity cost of each energy storage power station, the total revenue of the shared capacity of energy storage power stations in the consortium blockchain is calculated.

[0034] By establishing models of energy storage power stations and the power output of wind turbines and photovoltaic modules, the operating characteristics of energy storage power stations and the power deviation of renewable energy generation can be accurately described. Based on this, the opportunity cost of an energy storage power station can be calculated, thus providing a basis for accurately assessing the operating costs and benefits of energy storage power stations under a shared capacity model, making the distribution of benefits more reasonable and fair.

[0035] Constructing an energy storage power station model: The installed capacity, charge-discharge rate (C-Rate), charge-discharge efficiency (C-Efficiency), and state of charge (SOC) of an energy storage power station are the main factors determining its charge-discharge power (C-power). Among these, the installed capacity and charge-discharge rate (C-Rate) are constant values, while the charge-discharge efficiency (C-Efficiency), state of charge (SOC), and charge-discharge power (C-power) are variables that vary depending on different operating times and operating conditions.

[0036] The relationship between the installed capacity, charge / discharge rate, charge / discharge efficiency, state of charge, and charge / discharge power of an energy storage power station is expressed as follows: (1) in, This indicates the installed capacity of the energy storage power station. This indicates the charge / discharge rate of the energy storage power station. This indicates the charging and discharging efficiency of the energy storage power station. Indicates the state of charge of the energy storage power station. This indicates the charging and discharging power of the energy storage power station; Indicates discharge. Indicates charging; Considering the variation of charge / discharge rate over time during full-operational-condition operation, the charge / discharge efficiency varies with the charge / discharge power. The relationship between charge / discharge efficiency and charge / discharge power is expressed as: (2) in, This indicates the real-time charge and discharge rate of the energy storage power station. The formula for the charge and discharge energy loss (C-loss) during the operation of an energy storage power station is: (3) in, This indicates the energy loss during charging and discharging of the energy storage power station; The state of charge formula for an energy storage power station is: (4) in, It is the interval between execution times. This indicates the current state of charge of the energy storage power station. This indicates the state of charge of the energy storage power station at the previous moment.

[0037] Establish power output models for wind turbines and photovoltaic modules to obtain the deviation between predicted and actual power generation values, specifically including: The power generation of a renewable energy power plant is related to its installed capacity, the renewable energy source, and the power curve of the power generation components. For wind turbines, the power output formula is: (5) in, This indicates the actual power generation capacity of the wind turbine. Wind speed and power curve function It is an exponential function, and the values ​​of its coefficients are related to the manufacturing process of the wind turbine. For photovoltaic modules, the power output formula is: (6) in, This indicates the actual power generation of the photovoltaic module. The power curve function represents the intensity of solar radiation. It is an exponential function, and the values ​​of its coefficients are related to the manufacturing process of photovoltaic modules; Due to the fluctuations and randomness of wind speed and solar radiation, there is a discrepancy between the predicted and actual power generation. The power deviations between the actual and predicted power generation of wind turbines and photovoltaic modules are as follows: , (7) in, This indicates the power deviation between the actual power output and the predicted power output of a wind turbine. This indicates the power deviation between the actual power generation of a photovoltaic module and its predicted power generation. This indicates the predicted power generation capacity of the wind turbine. This indicates the predicted power generation of the photovoltaic module.

[0038] Based on the deviation between the predicted and actual power generation values, the opportunity cost of each energy storage power station is calculated, specifically including: The formula for calculating the operating revenue of an energy storage power station is as follows: (8) in, This indicates the operating revenue of the energy storage power station. express The charging and discharging power of the energy storage power station at all times. express The purchase and sale price of electricity at any given time; Assuming the predicted power output of wind power plants and photovoltaic modules matches the actual power output, then the entire installed capacity of energy storage power stations is used for peak shaving, and the expression for peak shaving revenue is: (9) in, This represents revenue within a peak-shaving cycle. Indicates peak electricity price, This indicates the off-peak electricity price; Due to the discrepancy between the predicted and actual power generation, the power discharged during peak electricity price periods is shifted to other periods, reducing discharge revenue. The expression for this revenue reduction is: (10) The discrepancy between the predicted and actual power generation results in charging power shifting from off-peak electricity price periods to other periods, increasing charging costs. The expression for this cost increase is: (11) in, express Income that is constantly decreasing express The cost increases constantly; Before joining a capacity-sharing consortium blockchain, the opportunity cost of operating an energy storage power station is expressed as: (12).

[0039] Based on the discrepancy between the predicted and actual power generation values ​​and the opportunity cost of each energy storage power station, the total revenue from the shared capacity of energy storage power stations in the consortium blockchain is calculated, specifically including: When multiple energy storage power stations share capacity to jointly address power deviations from multiple renewable energy power stations, the energy loss cost on the grid cannot be ignored. The expression for the total revenue from energy storage power station capacity sharing in a consortium blockchain is: (13) in, This represents the total benefits of capacity sharing. This represents the opportunity cost of sharing the capacity of several energy storage power stations. This indicates the energy loss in the power grid caused by the shared operation mode; Under the capacity-sharing model, the power balance equation for renewable energy power plants and energy storage power plants that include wind power and photovoltaic power generation is expressed as: (14) in, This indicates the power loss of the power grid; The cost of energy loss on the power grid can be expressed as: (15).

[0040] Each energy storage power station solves the shared scheduling plan using real-time information. The smart contract compares the revenue under each shared scheduling plan, and the shared scheduling plan with the highest total revenue is the optimal shared scheduling plan. The maximum total revenue expression for each energy storage power station executing the optimal shared scheduling plan is: (twenty one) in, This represents the optimization objective of maximizing the shared profits of total capacity. This represents the total revenue generated from the shared capacity of several energy storage power stations. Indicates the first The charging and discharging power of an energy storage power station , This represents the power loss of the power grid. Indicates the first The power deviation between the actual power generation and the predicted power generation of a wind turbine , Indicates the first The power deviation between the actual power generation and the predicted power generation of each photovoltaic module , This indicates the total number of energy storage power stations. This indicates the total number of wind power stations. This indicates the total number of photovoltaic power plants. Indicates the running time The service relationship of wind power stations Indicates the running time The service relationship of photovoltaic module power plants. Indicates the time of execution No. The state of charge of an energy storage power station This indicates the charging and discharging efficiency of the energy storage power station. Indicates the first The installed capacity of an energy storage power station Indicates the first The charge / discharge rate of an energy storage power station.

[0041] The present invention also provides a method for distributing benefits in the collaborative scheduling method described in the above embodiments, the method comprising: A revenue distribution model for each energy storage power station is constructed based on its installed capacity, opportunity cost, and actual cost. The total revenue of the alliance is then distributed to each energy storage power station based on this revenue distribution model.

[0042] The revenue distribution model for energy storage power stations is expressed as follows: (16) (17) (18) (19) (20) in, This represents the percentage of revenue used to reward the optimal shared scheduling plan. This indicates the weight of factors contributing to installed capacity. This indicates the weight of the opportunity cost contribution factor before sharing. This indicates the weight of the opportunity cost contribution factor after sharing. This indicates the profit sharing based on the capacity of the energy storage power station. Indicates the factors contributing to installed capacity. This indicates the opportunity cost contribution factor before sharing. This indicates the contribution factor of opportunity cost after sharing.

[0043] The method further includes optimizing the revenue distribution weights using a revenue distribution weight optimization model when changing consensus nodes in the consortium blockchain. The expression for the revenue distribution weight optimization model is as follows: (twenty two) in, This represents the optimization objective that minimizes the variance of the cost reduction rate of the energy storage power station itself. Calculate the capacity share profit of energy storage power stations under the revenue distribution weights before the change of the consortium blockchain; Calculate the capacity share profit of energy storage power stations under the revenue distribution weight after the change of the consortium blockchain; Compare the capacity sharing profits of the energy storage power stations before and after the change to the consortium blockchain. If the capacity sharing profits of the energy storage power stations after the change to the consortium blockchain are higher than those before the change, then each energy storage power station accepts the change; otherwise, each energy storage power station rejects the change.

[0044] This invention, through a revenue distribution weight optimization model, can dynamically adjust the revenue distribution weight based on the actual operation and data of energy storage power stations, making the revenue distribution more consistent with the actual contribution and cost of each energy storage power station in the process of sharing capacity, and further improving the fairness and rationality of revenue distribution.

[0045] When the consensus nodes in the consortium blockchain are changed, the revenue distribution weights can be optimized and adjusted in a timely manner, enabling the system to better adapt to changes in the energy storage power station network, such as the addition of new energy storage power stations or the exit of existing energy storage power stations. This ensures that the revenue distribution mechanism is always in the optimal state, improves the system's adaptability and flexibility, and provides support for the dynamic optimization and sustainable development of the energy storage power station network.

[0046] By calculating the capacity-sharing profits of energy storage power stations before and after the change to the consortium blockchain and comparing the differences, it is possible to clearly determine whether the changed revenue distribution weight has truly improved the profitability of energy storage power stations. Only when the changed capacity-sharing profits are higher than before the change will each energy storage power station accept the change, thereby ensuring that each optimization adjustment brings actual economic benefits and improving the effectiveness and reliability of the optimization results.

[0047] The independent method and the shared method proposed in this invention are compared and analyzed. MATLAB software is used to model and simulate consortium blockchain, smart contracts and income distribution strategies, and genetic algorithm is used to solve and optimize the model.

[0048] This embodiment selects the IEEE 33-node power system. Its base voltage is set to 35kV. Figure 2 The node diagram of the power plant in the IEEE 33-bus power system is as follows: Figure 2 As shown, the system comprises four energy storage stations, three solar power stations, and three wind power stations. The capacity and initial service relationship for each power station are provided.

[0049] This embodiment simulates continuous operation for 365 days a year, with an optimization cycle of 15 minutes. Within this cycle, the buffer period for the capacity-sharing blockchain consortium is set to 10 minutes, and the challenge period is 5 minutes. Time-of-use pricing is used as the real-time electricity price, as shown in Table 1. Figure 3 Typical daily wind and solar power generation and their forecast biases are shown. Short-term forecast bias is approximately 8%. Peak-shaving charge / discharge schemes and the state of charge (SOC) of energy storage devices in energy storage stations are also shown. Figure 4 As shown.

[0050] Table 1 Time-of-use electricity prices

[0051] The energy storage module has a charge / discharge rate (C-Rate) of 0.5C, and the real-time charge / discharge rate ranges from -0.5 to 0.5. The efficiency functions for each energy device are as follows: (twenty three) (twenty four) (25) This example uses a mixed-integer nonlinear programming method to solve for the optimal shared scheduling plan, which includes six real-time service relationships as integer variables and four rational variables representing the reference power of energy storage stations. The reward ratio for the optimal shared scheduling plan is set at 10%. A genetic algorithm with two rational variables is used to solve for the values ​​of the reward allocation weights.

[0052] Results analysis: Through simulation and optimization of annual operations, the weights of capacity investment, opportunity cost before sharing, and opportunity cost after sharing are 0.21, 0.84, and -0.15, respectively. Figure 5 For the annual costs and profits of consortium blockchains, such as Figure 5 As shown, the annual opportunity cost before sharing in the consortium blockchain is 10.5 million yuan, and the annual opportunity cost after sharing is 7.74 million yuan. The total capacity sharing profit of the consortium blockchain is 2.76 million yuan, of which 280,000 yuan is awarded to the optimal sharing scheduling plan, and 2.48 million yuan is allocated to the energy storage power station. The average profit per unit capacity of the consortium blockchain is 45.93 yuan / kWh. Therefore, the annual cost reduction rate of the consortium blockchain is 26.25%, and the rate of return per megawatt of capacity is 23.62%. These data demonstrate the feasibility and economic benefits of the consortium blockchain.

[0053] The annual costs and profits of energy storage power stations at nodes 6, 15, 24, and 32 are as follows: Figure 6As shown, the opportunity costs before sharing were RMB 3.05 million, RMB 11,800, RMB 38,100, and RMB 2.46 million, respectively. The opportunity costs after sharing were RMB 2.26 million, RMB 8,700, RMB 28,100, and RMB 1.81 million, respectively. The profits allocated to them were RMB 720,000, RMB 280,000, RMB 890,000, and RMB 590,000, respectively. Their revenue per megawatt of capacity was RMB 47.91, RMB 2.52, RMB 44.75, and RMB 39.31 per kilowatt-hour, respectively. The revenue share of each power station was 28.97%, 11.17%, 36.08%, and 23.77%, respectively, and their own cost reduction rates were 23.53%, 23.56%, 23.50%, and 23.96%, respectively. These data fully verify the fairness of the revenue distribution.

[0054] Table 2 shows the service relationship ratio between energy storage power stations and renewable energy power stations (wind power stations and photovoltaic power stations), which is largely consistent with the initial service relationship. It is worth noting that node 6 is the most active energy storage power station, providing services to each renewable energy power station at least 15%, with an average of 32%. Furthermore, node 6 replaces node 15 as the primary service node for node 12. This is mainly because node 6 is located at the topology center and is adjacent to multiple renewable energy power stations. These data indicate that optimized service relationships can improve the flexibility of energy storage power stations.

[0055] Table 2. Service Relationship between Energy Storage Power Stations and Renewable Energy Power Stations

[0056] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0057] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of devices, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0058] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0059] Any changes, modifications, substitutions, and variations made to the embodiments without departing from the principles and spirit of the present invention still fall within the protection scope of the present invention.

Claims

1. A collaborative scheduling method for energy storage power stations within a consortium blockchain, characterized in that, The method includes: Construct a blockchain alliance for sharing energy storage capacity with energy storage power stations as nodes; Construct a smart contract containing a mathematical model for solving the shared scheduling plan, and obtain the revenue of the shared capacity of each energy storage power station under the optimal shared scheduling plan based on the smart contract; Each energy storage power station solves the shared scheduling plan through real-time information. The smart contract compares the benefits under each shared scheduling plan and obtains the shared scheduling plan with the highest total benefit as the optimal shared scheduling plan. Each energy storage power station executes the optimal shared scheduling plan.

2. The cooperative scheduling method as described in claim 1, characterized in that, The benefits of shared capacity among energy storage power stations under the optimal shared scheduling plan, derived from smart contracts, include: Establish an energy storage power station model to describe the relationship between the installed capacity, charge / discharge rate, charge / discharge efficiency, state of charge, and charge / discharge power of the energy storage power station. Establish power output models for wind turbines and photovoltaic modules to obtain the deviation between predicted and actual power generation values; Based on the deviation between the predicted and actual power generation values, the opportunity cost of each energy storage power station is calculated. Based on the deviation between the predicted and actual power generation and the opportunity cost of each energy storage power station, the total revenue of the shared capacity of energy storage power stations in the consortium blockchain is calculated.

3. The cooperative scheduling method as described in claim 2, characterized in that, Each energy storage power station solves the shared scheduling plan using real-time information. The smart contract compares the revenue under each shared scheduling plan, and the shared scheduling plan with the highest total revenue is the optimal shared scheduling plan. The maximum total revenue expression for each energy storage power station executing the optimal shared scheduling plan is: (21) in, This represents the optimization objective of maximizing the shared profits of total capacity. This represents the total revenue generated from the shared capacity of several energy storage power stations. Indicates the first The charging and discharging power of an energy storage power station , This represents the power loss of the power grid. Indicates the first The power deviation between the actual power generation and the predicted power generation of a wind turbine , Indicates the first The power deviation between the actual power generation and the predicted power generation of each photovoltaic module , This indicates the total number of energy storage power stations. This indicates the total number of wind power stations. This indicates the total number of photovoltaic power plants. Indicates the running time The service relationship of the wind power station Indicates the running time The service relationship of photovoltaic module power plants. Indicates the time of execution No. The state of charge of an energy storage power station This indicates the charging and discharging efficiency of the energy storage power station. Indicates the first The installed capacity of an energy storage power station Indicates the first The charge / discharge rate of an energy storage power station.

4. The cooperative scheduling method as described in claim 3, characterized in that, The relationship between the installed capacity, charge / discharge rate, charge / discharge efficiency, state of charge, and charge / discharge power of an energy storage power station is expressed as follows: (1) in, This indicates the installed capacity of the energy storage power station. This indicates the charge / discharge rate of the energy storage power station. This indicates the charging and discharging efficiency of the energy storage power station. Indicates the state of charge of the energy storage power station. This indicates the charging and discharging power of the energy storage power station; Indicates discharge. Indicates charging; The relationship between charge / discharge efficiency and charge / discharge power is expressed as follows: (2) in, This indicates the real-time charge and discharge rate of the energy storage power station; The formula for energy loss during charging and discharging in the operation of an energy storage power station is: (3) in, This indicates the energy loss during charging and discharging of the energy storage power station; The state of charge formula for an energy storage power station is: (4) in, It is the interval between execution times. This indicates the current state of charge of the energy storage power station. This indicates the state of charge of the energy storage power station at the previous moment.

5. The cooperative scheduling method as described in claim 4, characterized in that, Establish power output models for wind turbines and photovoltaic modules to obtain the deviation between predicted and actual power generation values, specifically including: For wind turbines, the power output formula is: (5) in, This indicates the actual power generation capacity of the wind turbine. Indicates wind speed; For photovoltaic modules, the power output formula is: (6) in, This indicates the actual power generation of the photovoltaic module. Indicates solar radiation intensity; The power deviations between the actual and predicted power generation of wind turbines and photovoltaic modules are as follows: ， (7) in, This indicates the power deviation between the actual power output and the predicted power output of a wind turbine. This indicates the power deviation between the actual power generation of a photovoltaic module and its predicted power generation. This indicates the predicted power generation capacity of the wind turbine. This indicates the predicted power generation of the photovoltaic module.

6. The cooperative scheduling method as described in claim 5, characterized in that, Based on the deviation between the predicted and actual power generation values, the opportunity cost of each energy storage power station is calculated, specifically including: The formula for calculating the operating revenue of an energy storage power station is as follows: (8) in, This represents the operating revenue of the energy storage power station. express The charging and discharging power of the energy storage power station at all times. express The purchase and sale price of electricity at any given time; Assuming the predicted power output of wind power plants and photovoltaic modules matches the actual power output, then the entire installed capacity of energy storage power stations is used for peak shaving, and the expression for peak shaving revenue is: (9) in, This represents revenue within a peak-shaving cycle. Indicates peak electricity price, This indicates the off-peak electricity price; Due to the discrepancy between the predicted and actual power generation, the power discharged during peak electricity price periods is shifted to other periods, reducing discharge revenue. The expression for this revenue reduction is: (10) The discrepancy between the predicted and actual power generation results in charging power shifting from off-peak electricity price periods to other periods, increasing charging costs. The expression for this cost increase is: (11) in, express Income that is constantly decreasing express The cost increases constantly; Before joining a capacity-sharing consortium blockchain, the opportunity cost of operating an energy storage power station is expressed as: (12)。 7. The cooperative scheduling method as described in claim 6, characterized in that, Based on the discrepancy between the predicted and actual power generation values ​​and the opportunity cost of each energy storage power station, the total revenue from the shared capacity of energy storage power stations in the consortium blockchain is calculated, specifically including: The expression for the total revenue from capacity sharing of energy storage power stations in a consortium blockchain is: (13) in, This represents the total benefits of capacity sharing. This represents the opportunity cost of sharing the capacity of several energy storage power stations. This indicates the energy loss in the power grid caused by the shared operation mode; Under the capacity-sharing model, the power balance equation for renewable energy power plants and energy storage power plants that include wind power and photovoltaic power generation is expressed as: (14) in, This indicates the power loss of the power grid; The cost of energy loss on the power grid can be expressed as: (15)。 8. A method for distributing benefits in the collaborative scheduling method as described in any one of claims 1-7, characterized in that, The method includes: A revenue distribution model for each energy storage power station is constructed based on its installed capacity, opportunity cost, and actual cost. The total revenue of the alliance is then distributed to each energy storage power station based on this revenue distribution model.

9. The profit distribution method as described in claim 8, characterized in that, The revenue distribution model for energy storage power stations is expressed as follows: (16) (17) (18) (19) (20) in, This represents the percentage of revenue used to reward the optimal shared scheduling plan. This indicates the weight of factors contributing to installed capacity. This indicates the weight of the opportunity cost contribution factor before sharing. This indicates the weight of the opportunity cost contribution factor after sharing. This indicates the profit sharing based on the capacity of the energy storage power station. Indicates the factors contributing to installed capacity. This indicates the contribution of opportunity cost before sharing. This indicates the contribution factor of opportunity cost after sharing.

10. The profit distribution method as described in claim 9, characterized in that, The method further includes optimizing the revenue distribution weights using a revenue distribution weight optimization model when changing consensus nodes in the consortium blockchain. The expression for the revenue distribution weight optimization model is as follows: (22) in, This represents the optimization objective that minimizes the variance of the cost reduction rate of the energy storage power station itself. Calculate the capacity share profit of energy storage power stations under the revenue distribution weights before the change of the consortium blockchain; Calculate the capacity share profit of energy storage power stations under the revenue distribution weight after the change of the consortium blockchain; Compare the capacity sharing profits of the energy storage power stations before and after the change to the consortium blockchain. If the capacity sharing profits of the energy storage power stations after the change to the consortium blockchain are higher than those before the change, then each energy storage power station accepts the change; otherwise, each energy storage power station rejects the change.

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