Shared energy storage dynamic pricing method considering new energy prediction deviation and energy storage charge state

Abstract

The invention discloses a shared energy storage dynamic pricing method considering new energy prediction deviation and an energy storage charge state. The method comprises the following steps: a, constructing a shared energy storage operator model; b, constructing a new energy field station model; according to the method, the comprehensive influence of the output deviation and the energy storage charge state of the new energy station is considered, the market bargaining capability and the income of an energy storage operator are improved by optimizing the electricity price strategy, meanwhile, the interest demands of multiple new energy stations are considered, and the strategies of the two parties are promoted to reach the Nash equilibrium state.

Description

Technical Field

[0001] This invention belongs to the field of new energy technology, and more specifically relates to a dynamic pricing method for shared energy storage. Background Technology

[0002] The deepening of electricity market reforms has increasingly highlighted the importance of energy storage as an independent market player. However, the traditional fixed-price trading model is gradually losing its ability to incentivize energy storage development and is struggling to cope with the challenges posed by forecasting deviations in renewable energy output and the uncertainties arising from the multi-scenario applications of energy storage in actual operation. These uncertainties often lead to significant conflicts between the energy storage dispatch strategies formulated recently and actual operation.

[0003] To address these issues, a shared energy storage operation model is proposed, resolving the problems of low utilization rates and poor economic efficiency of self-contained energy storage at renewable energy power plants. Centralized shared energy storage power stations are independently funded, constructed, and operated by third-party energy storage operators. These operators leverage the spatiotemporal complementarity of demand from various power plants to establish centralized shared energy storage at the renewable energy cluster's convergence point, meeting the diverse needs of each plant. The shared energy storage operator, as the market leader, sets its charging and discharging service prices, aiming to maximize its own profits. Considering the spatiotemporal complementarity of demand, it determines the interaction between energy storage and various stakeholders at different times. Renewable energy power plants, as followers, determine their own transaction volume based on prices, aiming to minimize their own costs. To mitigate renewable energy fluctuations, they consider energy storage service prices to minimize penalties caused by prediction errors, determining their transaction volume with the energy storage operator at different times.

[0004] To improve the utilization rate and economic benefits of energy storage resources, it is necessary to propose a collaborative pricing mechanism between energy storage operators and new energy power plants that takes into account the output prediction deviation of new energy power plants and the sufficiency of energy storage resources. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a dynamic pricing method for shared energy storage that considers new energy prediction deviations and energy storage state of charge. This dynamic pricing mechanism takes into account both the energy storage state of charge and the output deviation of new energy clusters, thereby enhancing the market bargaining power of shared energy storage operators and increasing their revenue.

[0006] The technical solution adopted by the present invention to solve the above-mentioned technical problems is as follows:

[0007] A dynamic pricing method for shared energy storage that considers new energy prediction bias and energy storage state of charge, the method steps are as follows:

[0008] a. Construction of a shared energy storage operator model

[0009] As the dominant player, shared energy storage operators prioritize setting shared energy storage electricity prices, with the objective function being to maximize their own profits. Total revenue is comprised of the revenue from energy storage service fees provided to power plants. Cost of purchasing and selling electricity from the grid Annual investment cost of energy storage Composition, specifically, can be represented as

[0010] ;

[0011] b. New Energy Power Station Model Construction

[0012] As followers, new energy power stations generate their own benefits. Maximizing the total revenue as the objective function, the total revenue is determined by the revenue from grid connection of new energy sources. Penalties for deviations in new energy output and energy storage service fees The composition can be specifically represented as:

[0013] ;

[0014] c. Construction of dynamic pricing model

[0015] Shared energy storage operators play a leading role, taking the lead in setting shared energy storage electricity prices; secondly, new energy power plants follow suit and determine the volume of energy trading; finally, both parties continuously iterate on energy storage electricity prices and energy trading volumes until a balance is reached.

[0016] Preferably, in step a,

[0017] 1) Revenue from energy storage services

[0018] The revenue generated by shared energy storage power stations for charging and discharging services provided to renewable energy power plants includes the cost of electricity purchased from the energy storage facility and the revenue from selling the electricity.

[0019]

[0020] In the formula, and The electricity purchase and sale price for the shared energy storage operator at time t; and For the new energy power station at time t The amount of electricity purchased / sold to shared energy storage power stations;

[0021] 2) Electricity purchase and sale costs

[0022] Shared energy storage operators can generate additional revenue by charging idle energy storage during off-peak electricity prices.

[0023]

[0024] In the formula, , These represent the time-of-use electricity price and the on-grid electricity price of new energy sources at time t, respectively. , These represent the electricity purchased and sold from the grid by the shared energy storage operator at time t, respectively.

[0025] 3) Annual investment cost

[0026] The annual investment cost of shared energy storage includes the construction cost and operation and maintenance cost of the energy storage:

[0027]

[0028] In the formula, is the discount rate; n is the lifespan of the device; The proportion of energy storage operation and maintenance costs to construction costs; , This refers to the unit construction cost of the equipment.

[0029] Preferably, in step a, the constraints of the shared energy storage operator model are as follows:

[0030] 1) Energy storage capacity constraints

[0031] Energy storage systems should maintain energy balance at all times.

[0032]

[0033] In the formula, The energy balance constraint for shared energy storage at time t; and These are the charging and discharging efficiencies of the energy storage system; The state of charge of the energy storage system.

[0034] 2) Power balance constraints

[0035] Because power changes in real time, the power of an energy storage system must be kept in real time balance.

[0036]

[0037] In the formula, and These are the charging power and discharging power of the shared energy storage device, respectively.

[0038] 3) Charge and discharge state constraints

[0039] At the same time, energy storage systems cannot charge and discharge simultaneously.

[0040]

[0041] In the formula, These are the state variables for charging and discharging the energy storage system, and are 0-1 variables.

[0042] Preferably, in step b,

[0043] 1) Revenue from grid connection of new energy sources

[0044] Revenue from grid connection of new energy sources is the main source of revenue for new energy sources.

[0045]

[0046] In the formula, For time t, the station Internet power,

[0047] 2) Deviation penalty

[0048] When the actual grid-connected power of a renewable energy power plant deviates from its planned output, it will be subject to a grid deviation penalty. However, by adjusting the total output through transactions with energy storage operators, the grid deviation penalty can be reduced to some extent.

[0049]

[0050] In the formula, It is always a positive number and serves as a substitute decision variable for the deviation in electricity consumption. For power generation Internet access deviation penalty coefficient,

[0051] The power balance constraints for new energy power plants are as follows:

[0052]

[0053] In the formula, For new energy power stations A 0-1 random variable at time t; For new energy power stations Prediction bias threshold.

[0054] Preferably, in step c,

[0055] 1) Energy storage electricity purchase price

[0056]

[0057] In the formula, This represents the minimum electricity purchase price for energy storage operators.

[0058] 2) Energy storage electricity sales price

[0059]

[0060] In the formula, For the feed-in tariff of new energy, This refers to the time-of-use electricity price for the power grid.

[0061] The beneficial effects that can be achieved by adopting the above-mentioned technical solution in this invention are:

[0062] This approach balances the interests of energy storage operators and multiple renewable energy power plants, while simultaneously enhancing the bargaining power of energy storage operators in the market and increasing their revenue. By integrating key factors such as the state of charge (SOC) of energy storage and the output deviation of renewable energy clusters, this dynamic pricing mechanism can more accurately reflect changes in market supply and demand, thereby optimizing energy storage dispatch, ultimately improving the bargaining power of shared energy storage operators, and ensuring their basic revenue. Attached Figure Description

[0063] Figure 1 This is a transaction framework diagram between the shared energy storage operator and the new energy power station and power grid of this invention;

[0064] Figure 2 This is a framework diagram of the interactive mode of the present invention. Detailed Implementation

[0065] Depend on Figure 1 and Figure 2 As shown, a dynamic pricing method for shared energy storage that considers new energy prediction bias and energy storage state of charge is presented. The method steps are as follows:

[0066] a. Construction of a shared energy storage operator model

[0067] As the dominant player, shared energy storage operators prioritize setting shared energy storage electricity prices, with the objective function being to maximize their own profits. Total revenue is comprised of the revenue from energy storage service fees provided to power plants. Cost of purchasing and selling electricity from the grid Annual investment cost of energy storage Composition, specifically, can be represented as

[0068]

[0069] 1) Revenue from energy storage services

[0070] The revenue generated by shared energy storage power stations for charging and discharging services provided to renewable energy power plants includes the cost of electricity purchased from the energy storage facility and the revenue from selling the electricity.

[0071]

[0072] In the formula, and The electricity purchase and sale price for the shared energy storage operator at time t; and For the new energy power station at time t The amount of electricity purchased / sold to shared energy storage power stations;

[0073] 2) Electricity purchase and sale costs

[0074] Shared energy storage operators can generate additional revenue by using idle energy storage to charge electricity during off-peak hours when grid electricity prices are low.

[0075]

[0076] In the formula, , These represent the time-of-use electricity price and the on-grid electricity price of new energy sources at time t, respectively. , These represent the power purchased and sold to the grid by the shared energy storage operator at time t.

[0077] 3) Annual investment cost

[0078] The annual investment cost of shared energy storage includes the construction cost and operation and maintenance cost of the energy storage:

[0079]

[0080] In the formula, is the discount rate; n is the lifespan of the device; The proportion of energy storage operation and maintenance costs to construction costs; , This refers to the unit construction cost of the equipment.

[0081] The constraints of the shared energy storage operator model are as follows:

[0082] 1) Energy storage capacity constraints

[0083] Energy storage systems should maintain energy balance at all times.

[0084]

[0085] In the formula, The energy balance constraint for shared energy storage at time t; and These are the charging and discharging efficiencies of the energy storage system; This refers to the state of charge of the energy storage system.

[0086] 2) Power balance constraints

[0087] Because power changes in real time, the power of an energy storage system must be kept in real time balance.

[0088]

[0089] In the formula, and These are the charging power and discharging power of the shared energy storage device, respectively.

[0090] 3) Charge and discharge state constraints

[0091] At the same time, the energy storage system cannot charge and discharge simultaneously.

[0092]

[0093] In the formula, These are the state variables for charging and discharging the energy storage system, and are 0-1 variables.

[0094] b. New Energy Power Station Model Construction

[0095] As followers, new energy power stations generate their own benefits. Maximizing the total revenue as the objective function, the total revenue is determined by the revenue from grid connection of new energy sources. Penalties for deviations in new energy output and energy storage service fees The composition can be specifically represented as:

[0096]

[0097] 1) Revenue from grid connection of new energy sources

[0098] Revenue from grid connection of new energy sources is the main source of revenue for new energy sources.

[0099]

[0100] In the formula, For time t, the station Internet power.

[0101] 2) Deviation penalty

[0102] If the actual grid-connected power output of a renewable energy power plant deviates from the planned output, it will be subject to grid deviation penalties. However, adjusting the total output through transactions with energy storage operators can mitigate these penalties to some extent.

[0103]

[0104] In the formula, It is always a positive number, serving as a substitute decision variable for the deviation in electricity consumption above the grid. For power generation Internet access deviation penalty coefficient.

[0105] The power balance constraints for new energy power plants are as follows:

[0106]

[0107] In the formula, For new energy power stations A 0-1 random variable at time t; For new energy power stations Prediction bias threshold.

[0108] c. Construction of dynamic pricing model

[0109] The core objective is to enhance the market bargaining power of shared energy storage operators and increase their revenue. In an ideal scenario, if the predicted output of renewable energy power plants perfectly matches the actual output (SDR=1), there is no need to trade with energy storage. In this case, the purchase and sale price of energy storage will only be affected by fluctuations in grid time-of-use pricing and the remaining available capacity (SOAC) of energy storage. However, in a non-ideal scenario (SDR≠1), the purchase and sale price of energy storage will be simultaneously affected by the combined effects of the renewable energy cluster's demand ratio (SDR), grid time-of-use pricing, and SOAC.

[0110] Shared energy storage operators play a leading role, taking the lead in setting shared energy storage electricity prices; secondly, new energy power plants follow suit and determine the volume of energy trading; finally, both parties continuously iterate on energy storage electricity prices and energy trading volumes until a balance is reached.

[0111] This electricity pricing model is based on dynamic pricing, which comprehensively considers both renewable energy forecasting bias and the state of charge (SOC) of energy storage, thereby enhancing the bargaining power of energy storage operators. As market leaders, shared energy storage operators' core strategy is to maximize operational revenue by optimizing the electricity pricing mechanism. Conversely, each renewable energy power station, as a market follower, adjusts its charging and discharging strategies based on the energy storage purchase and sale price, aiming to minimize its electricity costs. This dynamic interaction prompts both parties to continuously optimize their strategies until the market reaches Nash equilibrium, ensuring that the electricity pricing strategy of energy storage operators can effectively guide the trading behavior of renewable energy power stations, thereby achieving overall system optimization and maximizing efficiency.

[0112] 1) Energy storage electricity purchase price

[0113]

[0114] In the formula, This is the minimum electricity purchase price for energy storage operators.

[0115] 2) Energy storage electricity sales price

[0116]

[0117] In the formula, For the feed-in tariff of new energy, This refers to the time-of-use electricity price for the power grid.

Claims

1. A dynamic pricing method for shared energy storage that considers new energy prediction bias and energy storage state of charge, characterized in that... The steps are as follows: a. Construction of a shared energy storage operator model As the dominant player, shared energy storage operators prioritize setting shared energy storage electricity prices, with the objective function being to maximize their own profits. Total revenue is comprised of the revenue from energy storage service fees provided to power plants. Cost of purchasing and selling electricity from the grid Annual investment cost of energy storage Composition, specifically, can be represented as ； b. New Energy Power Station Model Construction As followers, new energy power stations generate their own benefits. Maximizing the total revenue as the objective function, the total revenue is determined by the revenue from grid connection of new energy sources. Penalties for deviations in new energy output and energy storage service fees The composition can be specifically represented as: ； c. Construction of dynamic pricing model Shared energy storage operators play a leading role, taking the lead in setting shared energy storage electricity prices; secondly, new energy power plants follow suit and determine the volume of energy trading; finally, both parties continuously iterate on energy storage electricity prices and energy trading volumes until a balance is reached.

2. The shared energy storage dynamic pricing method considering new energy prediction deviation and energy storage state of charge as described in claim 1, characterized in that, In step a, 1) Revenue from energy storage services The revenue generated by shared energy storage power stations for charging and discharging services provided to renewable energy power plants includes the cost of electricity purchased from the energy storage facility and the revenue from selling the electricity. In the formula, and The electricity purchase and sale price for the shared energy storage operator at time t; and For the new energy power station at time t The amount of electricity purchased / sold to shared energy storage power stations; 2) Electricity purchase and sale costs Shared energy storage operators can generate additional revenue by charging idle energy storage during off-peak electricity prices. In the formula, , These represent the time-of-use electricity price and the on-grid electricity price of new energy sources at time t, respectively. , These represent the electricity purchased and sold from the grid by the shared energy storage operator at time t, respectively. 3) Annual investment cost The annual investment cost of shared energy storage includes the construction cost and operation and maintenance cost of the energy storage: In the formula, is the discount rate; n is the lifespan of the device; The proportion of energy storage operation and maintenance costs to construction costs; , This refers to the unit construction cost of the equipment.

3. The shared energy storage dynamic pricing method considering new energy prediction deviation and energy storage state of charge as described in claim 2, characterized in that, In step a, the constraints of the shared energy storage operator model are as follows: 1) Energy storage capacity constraints Energy storage systems should maintain energy balance at all times. In the formula, The energy balance constraint for shared energy storage at time t; and These are the charging and discharging efficiencies of the energy storage system; The state of charge of the energy storage system. 2) Power balance constraints Because power changes in real time, the power of an energy storage system must be kept in real time balance. In the formula, and These are the charging power and discharging power of the shared energy storage device, respectively. 3) Charge and discharge state constraints At the same time, energy storage systems cannot charge and discharge simultaneously. In the formula, These are the state variables for charging and discharging the energy storage system, and are 0-1 variables.

4. The shared energy storage dynamic pricing method considering new energy prediction deviation and energy storage state of charge as described in claim 1, characterized in that, In step b, 1) Revenue from grid connection of new energy sources Revenue from grid connection of new energy sources is the main source of revenue for new energy sources. In the formula, For time t, the station Internet power, 2) Deviation penalty When the actual grid-connected power of a renewable energy power plant deviates from its planned output, it will be subject to a grid deviation penalty. However, by adjusting the total output through transactions with energy storage operators, the grid deviation penalty can be reduced to some extent. In the formula, It is always a positive number and serves as a substitute decision variable for the deviation in electricity consumption. For power generation Internet access deviation penalty coefficient, The power balance constraints for new energy power plants are as follows: In the formula, For new energy power stations A 0-1 random variable at time t; For new energy power stations Prediction bias threshold.

5. The shared energy storage dynamic pricing method considering new energy prediction deviation and energy storage state of charge as described in claim 1, characterized in that, In step c, 1) Energy storage electricity purchase price In the formula, This represents the minimum electricity purchase price for energy storage operators. 2) Energy storage electricity sales price In the formula, For the on-grid tariff of new energy, This refers to the time-of-use pricing for electricity on the power grid.

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