Pricing method of shared energy storage capacity leasing and energy transaction mechanism

Abstract

The invention provides a pricing method for a shared energy storage capacity lease and energy transaction mechanism, and the method comprises the steps: firstly, proposing a'capacity lease + energy transaction 'operation mode of a shared energy storage operator, and enabling the shared energy storage operator to establish a target function with the maximization of the own income as a target, comprising energy transaction income, capacity lease income and energy storage charge and discharge loss cost; the method comprises the following steps that: firstly, a new energy station also establishes an objective function by taking own income maximization as an objective, and the objective function comprises power generation grid-connected income, energy storage transaction cost, energy storage capacity leasing cost, power grid output deviation assessment punishment and electricity abandoning cost, and secondly, in order to give consideration to the income of a shared energy storage operator and the energy storage service cost of the new energy station, the new energy station establishes an objective function; according to the method, the requirements of energy storage users such as new energy stations and the like on a multi-form sharing service mode are fully considered; the service demand of the user for short-time leasing is met, and differentiated pricing of each service mode is realized.

Description

Technical Field

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

[0002] Shared energy storage leverages the complementarity and diversity of energy storage demand to improve energy storage efficiency and reduce operating costs, thereby achieving the goal of cost reduction and efficiency improvement. This is a crucial path to promote the large-scale development of the energy storage industry. In the early stages of shared energy storage development, exploring service models is of great significance for promoting its practical application. Current research on shared energy storage service models mainly focuses on resource allocation under a single sharing model, neglecting the needs of energy storage users such as new energy power plants for multiple forms of sharing service models. Furthermore, in capacity leasing services, the main approach is to adopt a leasing model with a fixed leasing period of a full dispatch day, which fails to meet users' service needs for short-term leasing, and the advantages of shared energy storage in dispatch flexibility and utilization efficiency are not fully realized. Considering all these factors, it is necessary to propose a two-stage trading mechanism based on time-sharing leased energy storage capacity and energy sharing, and to implement differentiated pricing for each service model. Summary of the Invention

[0003] This invention addresses the aforementioned technical problems by proposing a pricing method for a shared energy storage capacity leasing and energy trading mechanism. First, it proposes an operational model of "capacity leasing + energy trading" for shared energy storage operators and describes the interactive pricing process between shared energy storage operators and new energy power plants. Second, to balance the revenue of shared energy storage operators with the energy storage service costs of new energy power plants, a two-stage model is established for solution.

[0004] The technical solution adopted by the present invention to solve the above-mentioned technical problems is as follows:

[0005] A pricing method for a shared energy storage capacity leasing and energy trading mechanism, comprising the following steps:

[0006] a. Construction of the operation model

[0007] Centralized shared energy storage power stations are independently funded, constructed, and operated by third-party energy storage operators. New energy power plants, aiming to reduce power generation deviations and increase new energy consumption, report their energy storage capacity leasing and energy trading needs to the shared energy storage operators based on their own power output characteristics. After summarizing the capacity and energy demands submitted by each new energy power plant, the energy storage operators provide shared energy storage capacity leasing and energy sharing services to the plants through the allocation and scheduling of energy storage resources.

[0008] The day-ahead transaction process for shared energy storage services will be divided into two phases: the first phase is the allocation of energy storage resources between capacity leasing and energy trading services; the second phase is the bidding and winning results for shared energy storage service needs based on the resource allocation, thereby completing the day-ahead transaction contract for shared energy storage services.

[0009] b. Construction of the pricing mechanism

[0010] (1) Capacity leasing pricing strategy based on lease duration,

[0011] (2) Energy trading pricing strategy based on supply-demand ratio;

[0012] c. Construction of a decision-making model for energy storage demand at new energy power stations

[0013] The day-ahead dispatch revenue of renewable energy power station i includes power generation grid connection revenue, energy storage trading costs, energy storage capacity leasing costs, grid output deviation assessment penalties, and curtailment costs, namely:

[0014]

[0015] In the formula, For the day-ahead dispatch revenue of new energy power station i These represent the power generation and grid-connected electricity sales revenue of the power station, the energy storage trading cost, the energy storage capacity leasing cost, the output deviation penalty cost, and the curtailment cost, respectively. Let i be the grid-connected power of the renewable energy power station during time period t. This refers to the electricity price for grid-connected power sales.

[0016] The first item in the energy storage capacity leasing cost is the fixed leasing cost related to the leased capacity, and the second item is the variable leasing cost related to the lease duration. When the actual grid-connected power of a renewable energy power plant is lower than the predicted grid-connected power, a power output deviation penalty will be paid to the grid based on the difference between the actual and predicted power. For the day-ahead predicted power generation of renewable energy power station i, The penalty cost per unit output deviation is calculated as follows: Due to output deviations in wind and solar power, when the actual power generation capacity of new energy sources exceeds the planned grid-connected power, the power station needs to adjust the operating status of the generators to reduce the actual output. The equipment loss costs incurred during this adjustment process are modeled as the cost of power curtailment. Cost per unit of power abandoned This represents the amount of electricity abandoned by renewable energy power station i during time period t.

[0017] d. Construction of a model for energy storage operator resource allocation and bidding decision-making.

[0018] The day-ahead dispatch revenue of energy storage operators includes energy trading revenue, capacity leasing revenue, and also the loss costs of energy storage charging and discharging, namely:

[0019]

[0020] In the formula, For the total revenue of energy storage operators, , The revenue generated from providing energy sharing and capacity leasing services to energy storage operators, respectively. The cost of energy storage due to losses during charging and discharging. , These represent the actual charging and discharging power provided by the energy storage operator to the site i; This indicates the number of lease periods actually won in the capacity leasing demand of energy storage unit u from site i; , These represent the actual charging and discharging power of the energy storage operator. Cost per unit of power loss;

[0021] e. Model linearization processing

[0022] The Big M method is used to linearize the model by introducing several auxiliary variables, thereby achieving an accurate solution to the model.

[0023] The shared energy storage capacity leasing cost for site i is:

[0024]

[0025] In the formula: , These are all nonlinear terms and require equivalent transformations.

[0026] (1) Number of time periods included in the lease term transformation

[0027] First, mark the lease period. The included time periods, drawing on the treatment of start-stop constraints in unit combination theory, introduce Boolean variables to mark the start and end of the lease period. and If and only if station i begins leasing energy storage unit u during time period t. The value is 1, indicating that the energy storage unit u is no longer leased by the site i in time period t. The value is 1, which represents the total number of lease periods for energy storage unit u at power station i. Also available This means, that is:

[0028]

[0029] In the formula: This represents a constant of a large order of magnitude. , , Its meaning is that the variable is marked as such before the lease term ends. When the value is 0, the variable Based on lease status variables The number of values ​​of 1 is incremented; the flag is only set at the end of the lease term. When the value is 1, the time period count variable will be cleared. This enables the management of each lease term. The distinction between them and the statistics of the number of time periods they include.

[0030] (2) Linearization of capacity leasing cost function

[0031] Will Substituting this into the second item, which represents the cost of rent paid according to the lease term, this item can be converted into... ,in and All of these are non-linear terms and require further transformation. First, we introduce auxiliary variables. ,make Then this term can be equivalently transformed into:

[0032]

[0033] Then introduce auxiliary variables. ,make Then this term can be equivalently transformed into:

[0034]

[0035]

[0036] in: , All variables are integers, thus the MILP model for the new energy power station side can be obtained, and the model can be solved accurately.

[0037] Preferably, the specific contents of the two stages in step a are as follows:

[0038] (1) Resource allocation stage

[0039] In the first phase, energy storage operators will decide on the resource allocation between capacity leasing and energy trading services for shared energy storage. The operators will pre-inform each renewable energy power station of the individual capacity of available energy storage units for leasing. After deciding on their leasing needs for different capacity types of energy storage units and their energy trading needs for shared energy storage, the power stations will report their needs to the energy storage operators. The operators, aiming to maximize the operational efficiency of energy storage, will optimize the allocation of energy storage resources between capacity leasing and energy trading, and determine the number of energy storage units used for capacity leasing services, thus completing the energy storage capacity resource allocation process.

[0040] (2) Decision-making stage of multiple rounds of bidding - winning bid results

[0041] Based on the energy storage resource allocation results obtained in the first phase, new energy power plants and energy storage operators conduct multiple rounds of bidding and winning decisions for shared energy storage demand. Power plants determine the required leasing capacity and lease period for each new round of bidding based on the latest winning bid information released by the energy storage operators. Energy storage operators, after summarizing the bidding demand from each round, combine it with historical winning bid results to determine the winning bid for capacity leasing in the current round. Simultaneously, energy storage operators will also leverage the complementary nature of energy demand among different power plants to facilitate direct energy transactions between them, and indirectly share energy with power plants through energy storage charging or discharging.

[0042] When each site no longer submits new capacity leasing bids, or when the energy storage operator no longer meets new bids, the multi-round bidding-winning decision-making stage ends. After summarizing the results of the previous rounds of winning bids, the energy storage operator and the new energy site sign a shared energy storage day-ahead transaction contract based on capacity leasing and energy trading services.

[0043] Preferably, in step b, the capacity leasing pricing strategy based on the lease duration is as follows:

[0044] Under the capacity leasing model based on continuous time periods, the leasing fee to be borne by the new energy power station is determined by the capacity of the leased energy storage unit and the lease duration. Let the total number of energy storage units be U, denoted as U... Each energy storage unit is numbered, and the rated capacity and rated power of energy storage unit u are respectively... and Let the total number of lease terms for energy storage units u at site i be . The numbering of each lease period is done using It means, record The unit price per capacity and the unit price per rental period for energy storage unit u during the first rental period are respectively... and This paper proposes a capacity leasing period unit price pricing strategy based on leasing duration: the more leasing periods included in the lease period, the lower the unit price for those periods, thereby incentivizing power stations to improve the continuity of their energy storage leasing demand. The specific relationship can be expressed as: :

[0045]

[0046] In the formula, This indicates that station i is in the lease period The total number of rental periods included. and These are the coefficient of the linear term and the constant term of the unit price function for segment rental, respectively.

[0047] Preferably, in step b, the energy trading pricing strategy based on the supply-demand ratio is as follows:

[0048] In shared energy storage trading services, renewable energy power plants can directly report their charging or discharging power demands for each time period to energy storage operators based on the deviation between predicted and actual power generation. The energy storage operators then aggregate the power demands from each renewable energy power plant and formulate a charging and discharging scheduling plan for energy storage resources used in the energy trading service to meet the power regulation needs of the power plants. and These represent the charging and discharging power demands submitted by site i to the energy storage operator during time period t. It can be expressed as an equation :

[0049]

[0050] The higher the charging power, the more energy is supplied. The higher; conversely The lower,

[0051]

[0052]

[0053] In the formula, and These represent the charging / discharging electricity prices for energy storage at time t; and These are the benchmark values ​​for charging and discharging electricity prices, respectively; and This is a constant coefficient in the energy trading pricing strategy.

[0054] Preferably, in step c,

[0055] The constraints consist of the state of charge constraints of the leased energy storage units, power balance constraints, power constraints of the leased energy storage units, mutual exclusion constraints of capacity leasing bidding decisions, and constraints on the curtailment rate of new energy power plants.

[0056] (1) State of charge constraints of leased energy storage units

[0057] To avoid severe lifespan loss caused by overcharging or over-discharging, it is necessary to limit the state of charge of the energy storage unit, namely:

[0058]

[0059]

[0060] in: This indicates the state of charge of energy storage unit u during the lease period at site i. and These represent the charging and discharging efficiencies, respectively. It is necessary to constrain the state of charge range of the energy storage unit u, where... and These represent the upper and lower limits of the state of charge of the energy storage unit u, respectively. This is a Boolean variable describing the leasing status of energy storage unit u by power station i during time period t. A value of 1 indicates that there is leasing demand, while a value of 0 indicates that there is no leasing demand.

[0061] (2) Power constraints of leased energy storage units

[0062] To avoid severe lifespan loss caused by overcharging or over-discharging, it is necessary to limit the state of charge of the energy storage unit, namely:

[0063]

[0064]

[0065] (3) Power balance constraint

[0066]

[0067] in: This represents the power generation capacity of renewable energy power station i during time period t. and These represent the power demand for charging and discharging of the leased energy storage unit u by power station i during time period t, respectively.

[0068] (4) Mutually exclusive constraints on capacity leasing bidding decisions

[0069] Let the historical bidding results of station i be as follows: Then the following constraints apply:

[0070]

[0071] Where: Boolean variables are used This represents the historical bidding results for energy storage unit u at site j during time period t, thus avoiding conflicts between site i and site j regarding their already successful bidding decisions.

[0072] (5) Constraints on curtailment rate of new energy power plants

[0073] The amount of wind and solar power curtailed by the power station during the dispatch period should meet the following constraints:

[0074]

[0075] in: The curtailment rate refers to the percentage of curtailed power in all time periods that is not greater than the total renewable power. .

[0076] Preferably, in step d,

[0077] The constraints consist of constraints on energy storage resource allocation, coupling constraints on the bidding period for capacity leasing, constraints on the state of charge of energy storage, and constraints on the charging and discharging power of energy storage transactions.

[0078] (1) Constraints on the allocation of energy storage resources

[0079] When energy storage participates in energy sharing transactions, its charging and discharging power shall not exceed its own rated power, and shall not exceed the net load demand of all users' energy transactions, that is:

[0080]

[0081] In the formula: For the rated capacity of energy storage, Rated energy storage capacity for providing energy trading services; This is the rated power of the energy storage. The rated power of energy storage unit u used to provide energy trading services,

[0082] Whether energy storage is used to provide capacity leasing or energy trading services, its capacity and power must meet the capacity-power ratio conditions of the original energy storage, that is:

[0083]

[0084] in: This is the capacity-power ratio factor.

[0085] (2) Coupling constraints of the bidding period for capacity leasing

[0086] The capacity leasing demands reported by energy storage users to energy storage operators have a continuous leasing period, i.e., the leasing period is... The included time periods have an "AND" requirement for winning bids, meaning they are "packaged" into a "lease package": when deciding whether to lease storage capacity to energy storage users, energy storage operators can only choose to win bids for all time periods within the lease term, or to lose bids for none of the time periods. They cannot only meet the capacity leasing needs of a portion of the time periods. As a description of the A Boolean variable is used to determine whether a lease term was won. A value of 1 indicates a successful bid for that lease term, while a value of 0 indicates a failed bid. Simultaneously, when deciding on the winning bid for capacity leasing, energy storage operators must ensure that the winning bid periods for energy storage capacity leasing by different renewable energy power plants do not conflict. That is, an energy storage unit u can only be leased by one power plant within time period t. Furthermore, in multiple rounds of bidding, the winning bid decision cannot conflict with historical winning bid results. These constraints can be expressed as:

[0087]

[0088] In the formula: This indicates the leasing status of energy storage unit u by power station i during time period t. A value of 1 indicates leasing, and a value of 0 indicates no leasing. This is a Boolean variable describing the historical bidding status of leases. A value of 1 indicates that the lease has been completed in the historical bidding process; otherwise, it indicates that the lease is idle.

[0089] (3) Energy storage state of charge constraints

[0090] When energy storage is used for charging and discharging operations to provide energy trading services, its state of charge must also meet corresponding limit constraints, as follows:

[0091]

[0092] In the formula: The state of charge of the energy storage during time period t. and These are the upper and lower limits of the energy storage state of charge, respectively.

[0093] (4) Constraints on charging and discharging power of energy storage trading

[0094] When energy storage participates in energy sharing transactions, its charging and discharging power shall not exceed its own rated power, and shall not exceed the net load demand of all users' energy transactions, that is:

[0095]

[0096] In the formula: This indicates that x takes the larger value between 0 and x.

[0097] The beneficial effects that the present invention can achieve by adopting the above-mentioned technical solution are as follows: Compared with the prior art, the present invention fully considers the needs of energy storage users such as new energy power stations for multiple forms of shared service modes; at the same time, in capacity leasing services, it meets the service needs of users for short-term leasing, highlights the scheduling flexibility and utilization efficiency advantages of shared energy storage, and realizes differentiated pricing for each service mode. Attached Figure Description

[0098] Figure 1 This is a transaction framework diagram between producers / consumers, shared energy storage, and the power grid proposed in this invention.

[0099] Figure 2 This is a flowchart of the solution process proposed in this invention. Detailed Implementation

[0100] A pricing method for a shared energy storage capacity leasing and energy trading mechanism, the specific steps of which are as follows:

[0101] a. Construction of the operation model

[0102] like Figure 1 The diagram illustrates the transaction framework between shared energy storage operators and renewable energy power plants. Centralized shared energy storage power plants are independently funded, constructed, and operated by third-party energy storage operators. Renewable energy power plants, aiming to reduce power generation deviations and increase renewable energy consumption, report their energy storage capacity leasing and energy trading needs to the shared energy storage operators based on their own power output characteristics. After compiling the capacity and energy demands submitted by each renewable energy power plant, the energy storage operators provide shared energy storage capacity leasing and energy sharing services to the plants through the allocation and scheduling of energy storage resources.

[0103] To further clarify resource allocation and actual dispatch, the day-ahead transaction process for shared energy storage services will be divided into two phases: the first phase is the allocation of energy storage resources between capacity leasing and energy trading services; the second phase is the decision on the bidding and winning results for shared energy storage service needs based on resource allocation, thereby completing the day-ahead transaction contract for shared energy storage services.

[0104] (1) Resource allocation stage

[0105] In the first phase, energy storage operators will decide on the resource allocation between capacity leasing and energy trading services for shared energy storage. The operators will pre-inform each renewable energy power station of the individual capacity of the energy storage units available for leasing. After deciding on their leasing needs for different capacity types of energy storage units and their energy trading needs for shared energy storage, the power stations will report their needs to the energy storage operators. The operators, aiming to maximize the operational efficiency of energy storage, will optimize the allocation of energy storage resources between capacity leasing and energy trading, and determine the number of energy storage units used to provide capacity leasing services, thus completing the energy storage capacity resource allocation process.

[0106] (2) Decision-making stage of multiple rounds of bidding - winning bid results

[0107] Based on the energy storage resource allocation results obtained in the first phase, new energy power plants and energy storage operators conduct multiple rounds of bidding and winning decisions for shared energy storage demand. Power plants determine the rental capacity and rental period requirements for the new round of bidding based on the latest winning bid information for energy storage units released by energy storage operators. Energy storage operators, after summarizing the bidding requirements of each round, determine the winning bid results for the capacity rental of the current round by combining historical winning bid results. At the same time, energy storage operators will also utilize the complementary characteristics between the energy demands of each power plant to complete direct energy transactions between power plants, and indirectly share energy with power plants through energy storage charging or discharging.

[0108] The introduction of a multi-round bidding mechanism helps power plants maximize the utilization of their leasable energy storage capacity, while retaining historical bidding results reduces the workload associated with retendering. When power plants no longer submit new capacity leasing bids, or when energy storage operators no longer meet new bidding demands, the multi-round bidding-winning decision phase ends. After summarizing the historical bidding results, the energy storage operator signs a shared energy storage day-ahead trading contract with the new energy power plant, based on capacity leasing and energy trading services.

[0109] b. Construction of the pricing mechanism

[0110] (1) Capacity leasing pricing strategy based on lease duration

[0111] Under the capacity leasing model based on continuous time periods, the leasing fee to be borne by the new energy power station is determined by the capacity of the leased energy storage unit and the lease duration. Let the total number of energy storage units be U, denoted as U... Each energy storage unit is numbered, and the rated capacity and rated power of energy storage unit u are respectively... and Let the total number of lease terms for energy storage units u at site i be . The numbering of each lease period is done using It means, record The unit price per capacity and the unit price per rental period for energy storage unit u during the first rental period are respectively... and To improve the continuity of energy storage leasing at power plants and avoid idle and wasted energy storage resources due to numerous fragmented leasing periods, this method proposes a capacity leasing period unit price pricing strategy based on the lease duration: the more leasing periods included in the lease period, the lower the unit price for that period, thereby incentivizing power plants to improve the continuity of their energy storage leasing demand. The specific relationship can be expressed as: :

[0112]

[0113] In the formula, This indicates that station i is in the lease period The total number of rental periods included. and These are the coefficient of the linear term and the constant term of the unit price function for segment rental, respectively.

[0114] (2) Energy trading pricing strategy based on supply and demand ratio

[0115] In shared energy storage trading services, renewable energy power plants can directly report their charging or discharging power demands for each time period to energy storage operators based on the deviation between predicted and actual power generation. Energy storage operators then aggregate the power demands from each renewable energy power plant and formulate a charging and discharging scheduling plan for energy storage resources used in the energy trading service to meet the power regulation needs of the power plants. The SDR-based pricing strategy can reflect the energy supply and demand situation during the trading process and demonstrate the scarcity of resources through price. Let... and These represent the charging and discharging power demands submitted by site i to the energy storage operator during time period t. It can be expressed as an equation :

[0116]

[0117] The higher the charging power, the more energy is supplied. The higher; conversely The lower,

[0118]

[0119]

[0120] In the formula, and These represent the charging / discharging electricity prices for energy storage at time t; and These are the benchmark values ​​for charging and discharging electricity prices, respectively; and This is a constant coefficient in the energy trading pricing strategy.

[0121] c. Construction of a decision-making model for energy storage demand at new energy power plants

[0122] The day-ahead dispatch revenue of renewable energy power station i includes power generation grid connection revenue, energy storage trading costs, energy storage capacity leasing costs, grid output deviation assessment penalties, and curtailment costs, namely:

[0123]

[0124] In the formula, For the day-ahead dispatch revenue of new energy power station i These represent the power generation and grid-connected electricity sales revenue of the power station, the energy storage trading cost, the energy storage capacity leasing cost, the output deviation penalty cost, and the curtailment cost, respectively. Let i be the grid-connected power of the renewable energy power station during time period t. This refers to the electricity price for grid-connected power sales.

[0125] The first item in the energy storage capacity leasing cost is the fixed leasing cost related to the leased capacity, and the second item is the variable leasing cost related to the lease duration. When the actual grid-connected power of a renewable energy power plant is lower than the predicted grid-connected power, a power output deviation penalty will be paid to the grid based on the difference between the actual and predicted power. For the day-ahead predicted power generation of renewable energy power station i, The penalty cost per unit output deviation is calculated as follows: Due to output deviations in wind and solar power, when the actual power generation capacity of new energy sources exceeds the planned grid-connected power, the power station needs to adjust the operating status of the generators to reduce the actual output. The equipment loss costs incurred during this adjustment process are modeled as the cost of power curtailment. Cost per unit of power abandoned This represents the amount of electricity abandoned by renewable energy power station i during time period t.

[0126] The constraints consist of the state of charge constraints of the leased energy storage units, power balance constraints, power constraints of the leased energy storage units, mutual exclusion constraints of capacity leasing bidding decisions, and constraints on the curtailment rate of new energy power plants.

[0127] (1) State of charge constraints of leased energy storage units

[0128] New energy power plants have the right to dispatch and use energy storage units during the lease period. To avoid severe lifespan loss caused by overcharging or over-discharging, it is necessary to limit the state of charge of the energy storage units, namely:

[0129]

[0130]

[0131] in: This indicates the state of charge of energy storage unit u during the lease period at site i. and These represent the charging and discharging efficiencies, respectively. It is necessary to constrain the state of charge range of the energy storage unit u, where... and These represent the upper and lower limits of the state of charge of the energy storage unit u, respectively. This is a Boolean variable describing the leasing status of energy storage unit u by power station i during time period t. A value of 1 indicates that there is a leasing demand, while a value of 0 indicates that there is no leasing demand.

[0132] (2) Power constraints of leased energy storage units

[0133] New energy power plants have the right to dispatch and use energy storage units during the lease period. To avoid severe lifespan loss caused by overcharging or over-discharging, it is necessary to limit the state of charge of the energy storage units, namely:

[0134]

[0135]

[0136] (3) Power balance constraint

[0137]

[0138] in: This represents the power generation capacity of renewable energy power station i during time period t. and These represent the power demand of power station i for charging and discharging the leased energy storage unit u during time period t.

[0139] (4) Mutually exclusive constraints on capacity leasing bidding decisions

[0140] In the multi-round capacity leasing bidding process, new energy power plants need to consider their historical bidding results in each round, meaning they cannot be bid on again within a lease period that has already been won. Let the historical bidding results of power plant i be... Then the following constraints apply:

[0141]

[0142] Where: Boolean variables are used This represents the historical bidding results of energy storage unit u for site j during time period t, thereby avoiding conflicts between site i and site j regarding their successful bidding decisions.

[0143] (5) Constraints on curtailment rate of new energy power plants

[0144] The amount of wind and solar power curtailed by the power station during the dispatch period should meet the following constraints:

[0145]

[0146] in: The curtailment rate refers to the percentage of curtailed power in all time periods that is not greater than the total renewable power. .

[0147] d. Construction of energy storage resource allocation and bidding decision-making model for energy storage operators

[0148] The day-ahead dispatch revenue of energy storage operators includes energy trading revenue, capacity leasing revenue, and also the loss costs of energy storage charging and discharging, namely:

[0149]

[0150] In the formula, For the total revenue of energy storage operators, , The revenue generated from providing energy sharing and capacity leasing services to energy storage operators, respectively. The cost of energy storage due to losses during charging and discharging. , These represent the actual charging and discharging power provided by the energy storage operator to the site i; This indicates the number of lease periods actually won in the capacity leasing demand of energy storage unit u from site i; , These represent the actual charging and discharging power of the energy storage operator. Cost per unit of power loss.

[0151] The constraints consist of constraints on energy storage resource allocation, coupling constraints on the bidding period of capacity leasing, constraints on the state of charge of energy storage, and constraints on the charging and discharging power of energy storage transactions.

[0152] (1) Constraints on the allocation of energy storage resources

[0153] When energy storage participates in energy sharing transactions, its charging and discharging power shall not exceed its own rated power, and shall not exceed the net load demand of all users' energy transactions, that is:

[0154]

[0155] In the formula: For the rated capacity of energy storage, Rated energy storage capacity for providing energy trading services; This is the rated power of the energy storage. The rated power of the energy storage unit u used to provide energy trading services.

[0156] Meanwhile, to ensure a reasonable match between the capacity and power characteristics of energy storage, thereby improving the utilization efficiency of energy storage resources, regardless of whether energy storage is used to provide capacity leasing or energy trading services, its capacity and power must meet the original capacity-power ratio conditions of energy storage, that is:

[0157]

[0158] in: This is the capacity-power ratio factor.

[0159] (2) Coupling constraints of the bidding period for capacity leasing

[0160] The capacity leasing demands reported by energy storage users to energy storage operators have a continuous leasing period, i.e., the leasing period is... The included time periods have an "AND" requirement for winning bids, meaning they are "packaged" into a "lease package": when deciding whether to lease storage capacity to energy storage users, energy storage operators can only choose to win bids for all time periods within the lease term, or to lose bids for none of the time periods. They cannot only meet the capacity leasing needs of a portion of the time periods. As a description of the A Boolean variable is used to determine whether a lease term was won. A value of 1 indicates a successful bid for that lease term, while a value of 0 indicates a failed bid. Simultaneously, when deciding on the winning bid for capacity leasing, energy storage operators must ensure that the winning bid periods for energy storage capacity leasing by different renewable energy power plants do not conflict. That is, an energy storage unit u can only be leased by one power plant within time period t. Furthermore, in multiple rounds of bidding, the winning bid decision cannot conflict with historical winning bid results. These constraints can be expressed as:

[0161]

[0162] In the formula: This indicates the leasing status of energy storage unit u by power station i during time period t. A value of 1 indicates leasing, and a value of 0 indicates no leasing. This is a Boolean variable that describes the status of historical lease bids. A value of 1 indicates that the lease has been completed in the historical bids, while the other value indicates that the lease is idle.

[0163] (3) Energy storage state of charge constraints

[0164] When energy storage is used for charging and discharging operations to provide energy trading services, its state of charge must also meet corresponding limit constraints, as follows:

[0165]

[0166] In the formula: The state of charge of the energy storage during time period t. and These are the upper and lower limits of the energy storage state of charge, respectively.

[0167] (4) Constraints on charging and discharging power of energy storage trading

[0168] When energy storage participates in energy sharing transactions, its charging and discharging power shall not exceed its own rated power, and shall not exceed the net load demand of all users' energy transactions, that is:

[0169]

[0170] In the formula: This indicates that x takes the larger value between 0 and x.

[0171] e. Model linearization

[0172] like Figure 2 The diagram shown illustrates the solution process framework proposed in this invention. However, the aforementioned decision-making models for new energy power plants and energy storage operators all contain nonlinear terms. The Big M method is used to linearize the model by introducing several auxiliary variables, thereby achieving an accurate solution.

[0173] The shared energy storage capacity leasing cost for site i is:

[0174]

[0175] In the formula: , These are all nonlinear terms and require equivalent transformations.

[0176] (1) Number of time periods included in the lease term transformation

[0177] First, mark the lease period. The included time periods, drawing on the treatment of start-stop constraints in unit combination theory, introduce Boolean variables to mark the start and end of the lease period. and If and only if station i begins leasing energy storage unit u during time period t. The value is 1, indicating that the energy storage unit u is no longer leased by the site i in time period t. The value is 1, which represents the total number of lease periods for energy storage unit u at power station i. Also available This means, that is:

[0178]

[0179] In the formula: This represents a constant of a large order of magnitude. , , Its meaning is that the variable is marked as such before the lease term ends. When the value is 0, the variable Based on lease status variables The number of values ​​of 1 is incremented; the flag is only set at the end of the lease term. When the value is 1, the time period count variable will be cleared. This enables the management of each lease term. The distinction between them and the statistics of the number of time periods they include.

[0180] (2) Linearization of capacity leasing cost function

[0181] Will Substituting this into the second item, which represents the cost of rent paid according to the lease term, this item can be converted into... ,in and All of these are non-linear terms and require further transformation. First, we introduce auxiliary variables. ,make Then this term can be equivalently transformed into:

[0182]

[0183] Then introduce auxiliary variables. ,make Then this term can be equivalently transformed into:

[0184]

[0185]

[0186] in: , All variables are integers, thus the MILP model for the new energy power station side can be obtained, and the model can be solved accurately.

Claims

1. A pricing method for a shared energy storage capacity leasing and energy trading mechanism, characterized in that... The steps are as follows: a. Construction of the operation model Centralized shared energy storage power stations are independently funded, constructed, and operated by third-party energy storage operators. New energy power plants, aiming to reduce power generation deviations and increase new energy consumption, report their energy storage capacity leasing and energy trading needs to the shared energy storage operators based on their own power output characteristics. After summarizing the capacity and energy demands submitted by each new energy power plant, the energy storage operators provide shared energy storage capacity leasing and energy sharing services to the plants through the allocation and scheduling of energy storage resources. The day-ahead transaction process for shared energy storage services will be divided into two phases: the first phase is the allocation of energy storage resources between capacity leasing and energy trading services; the second phase is the bidding and winning results for shared energy storage service needs based on the resource allocation, thereby completing the day-ahead transaction contract for shared energy storage services. b. Construction of the pricing mechanism (1) Capacity leasing pricing strategy based on lease duration, (2) Energy trading pricing strategy based on supply-demand ratio; c. Construction of a decision-making model for energy storage demand at new energy power stations The day-ahead dispatch revenue of renewable energy power station i includes power generation grid connection revenue, energy storage trading costs, energy storage capacity leasing costs, grid output deviation assessment penalties, and curtailment costs, namely: In the formula, For the day-ahead dispatch revenue of new energy power station i These represent the power generation and grid-connected electricity sales revenue of the power station, the energy storage trading cost, the energy storage capacity leasing cost, the output deviation penalty cost, and the curtailment cost, respectively. Let i be the grid-connected power of the renewable energy power station during time period t. For grid-connected electricity sales price, The first item in the energy storage capacity leasing cost is the fixed leasing cost related to the leased capacity, and the second item is the variable leasing cost related to the lease duration. When the actual grid-connected power of a renewable energy power plant is lower than the predicted grid-connected power, a power output deviation penalty will be paid to the grid based on the difference between the actual and predicted power. For the day-ahead predicted power generation of renewable energy power station i, The penalty cost per unit output deviation is calculated as follows: Due to output deviations in wind and solar power, when the actual power generation capacity of new energy sources exceeds the planned grid-connected power, the power station needs to adjust the operating status of the generators to reduce the actual output. The equipment loss costs incurred during this adjustment process are modeled as the cost of power curtailment. Cost per unit of power abandoned This represents the amount of electricity abandoned by renewable energy power station i during time period t. d. Construction of a model for energy storage operator resource allocation and bidding decision-making. The day-ahead dispatch revenue of energy storage operators includes energy trading revenue, capacity leasing revenue, and also the loss costs of energy storage charging and discharging, namely: In the formula, For the total revenue of energy storage operators, , The revenue generated from providing energy sharing and capacity leasing services to energy storage operators, respectively. The cost of energy storage due to losses during charging and discharging. , These represent the actual charging and discharging power provided by the energy storage operator to the site i; This indicates the number of lease periods actually won in the capacity leasing demand of energy storage unit u from site i; , These represent the actual charging and discharging power of the energy storage operator. Cost per unit power loss; e. Model linearization processing The Big M method is used to linearize the model by introducing several auxiliary variables, thereby achieving an accurate solution to the model. The shared energy storage capacity leasing cost for site i is: In the formula: , These are all nonlinear terms and require equivalent transformations. (1) Number of time periods included in the lease term transformation First, mark the lease period. The included time periods, drawing on the treatment of start-stop constraints in unit combination theory, introduce Boolean variables to mark the start and end of the lease period. and If and only if station i begins leasing energy storage unit u during time period t. The value is 1, indicating that the energy storage unit u is no longer leased by the site i in time period t. The value is 1, which represents the total number of lease periods for energy storage unit u at power station i. Also available This means, that is: In the formula: This represents a constant of a large order of magnitude. , , Its meaning is that the variable is marked as such before the lease term ends. When the value is 0, the variable Based on lease status variables The number of values ​​of 1 is incremented; the flag is only set at the end of the lease term. When the value is 1, the time period count variable will be cleared. This enables the management of each lease term. The distinction between them and the statistics of the number of time periods they include. (2) Linearization of capacity leasing cost function Will Substituting this into the second item, which represents the cost of rent paid according to the lease term, this item can be converted into... ,in and All of these are non-linear terms and require further transformation. First, we introduce auxiliary variables. ,make Then this term can be equivalently transformed into: Then introduce auxiliary variables. ,make Then this term can be equivalently transformed into: in: , All variables are integers, thus the MILP model for the new energy power station side can be obtained, and the model can be solved accurately.

2. The pricing method for a shared energy storage capacity leasing and energy trading mechanism according to claim 1, characterized in that, In step a, the specific contents of the two stages are as follows: (1) Resource allocation stage In the first phase, energy storage operators will decide on the resource allocation between capacity leasing and energy trading services for shared energy storage. The operators will pre-inform each renewable energy power station of the individual capacity of available energy storage units for leasing. After deciding on their leasing needs for different capacity types of energy storage units and their energy trading needs for shared energy storage, the power stations will report their needs to the energy storage operators. The operators, aiming to maximize the operational efficiency of energy storage, will optimize the allocation of energy storage resources between capacity leasing and energy trading, and determine the number of energy storage units used for capacity leasing services, thus completing the energy storage capacity resource allocation process. (2) Decision-making stage of multiple rounds of bidding - winning bid results Based on the energy storage resource allocation results obtained in the first phase, new energy power plants and energy storage operators conduct multiple rounds of bidding and winning decisions for shared energy storage demand. Power plants determine the required leasing capacity and lease period for each new round of bidding based on the latest winning bid information released by the energy storage operators. Energy storage operators, after summarizing the bidding demand from each round, combine it with historical winning bid results to determine the winning bid for capacity leasing in the current round. Simultaneously, energy storage operators will also leverage the complementary nature of energy demand among different power plants to facilitate direct energy transactions between them, and indirectly share energy with power plants through energy storage charging or discharging. When each site no longer submits new capacity leasing bids, or when the energy storage operator no longer meets new bids, the multi-round bidding-winning decision-making stage ends. After summarizing the results of the previous rounds of winning bids, the energy storage operator and the new energy site sign a shared energy storage day-ahead transaction contract based on capacity leasing and energy trading services.

3. The pricing method for a shared energy storage capacity leasing and energy trading mechanism according to claim 1, characterized in that, In step b, the capacity leasing pricing strategy based on the lease duration is as follows: Under the capacity leasing model based on continuous time periods, the leasing fee to be borne by the new energy power station is determined by the capacity of the leased energy storage unit and the lease duration. Let the total number of energy storage units be U, denoted as U... Each energy storage unit is numbered, and the rated capacity and rated power of energy storage unit u are respectively... and Let the total number of lease terms for energy storage units u at site i be . The numbering of each lease period is done using It means, record The unit price per capacity and the unit price per rental period for energy storage unit u during the first rental period are respectively... and This paper proposes a capacity leasing period unit price pricing strategy based on leasing duration: the more leasing periods included in the lease period, the lower the unit price for those periods, thereby incentivizing power stations to improve the continuity of their energy storage leasing demand. The specific relationship can be expressed as: : In the formula, This indicates that station i is in the lease period The total number of rental periods included. and These are the coefficient of the linear term and the constant term of the unit price function for segment rental, respectively.

4. The pricing method for a shared energy storage capacity leasing and energy trading mechanism according to claim 1, characterized in that, In step b, the energy trading pricing strategy based on the supply-demand ratio is as follows: In shared energy storage trading services, renewable energy power plants can directly report their charging or discharging power demands for each time period to energy storage operators based on the deviation between predicted and actual power generation. The energy storage operators then aggregate the power demands from each renewable energy power plant and formulate a charging and discharging scheduling plan for energy storage resources used in the energy trading service to meet the power regulation needs of the power plants. and These represent the charging and discharging power demands submitted by site i to the energy storage operator during time period t. It can be expressed as an equation : The higher the charging power, the more energy is supplied. The higher; conversely The lower, In the formula, and These represent the charging / discharging electricity prices for energy storage at time t; and These are the benchmark values ​​for charging and discharging electricity prices, respectively; and This is a constant coefficient in the energy trading pricing strategy.

5. The pricing method for a shared energy storage capacity leasing and energy trading mechanism according to claim 1, characterized in that, In step c, The constraints consist of the state of charge constraints of the leased energy storage units, power balance constraints, power constraints of the leased energy storage units, mutual exclusion constraints of capacity leasing bidding decisions, and constraints on the curtailment rate of new energy power plants. (1) State of charge constraints of leased energy storage units To avoid severe lifespan loss caused by overcharging or over-discharging, it is necessary to limit the state of charge of the energy storage unit, namely: in: This indicates the state of charge of energy storage unit u during the lease period at site i. and These represent the charging and discharging efficiencies, respectively. It is necessary to constrain the state of charge range of the energy storage unit u, where... and These represent the upper and lower limits of the state of charge of the energy storage unit u, respectively. This is a Boolean variable describing the leasing status of energy storage unit u by power station i during time period t. A value of 1 indicates that there is leasing demand, while a value of 0 indicates that there is no leasing demand. (2) Power constraints of leased energy storage units To avoid severe lifespan loss caused by overcharging or over-discharging, it is necessary to limit the state of charge of the energy storage unit, namely: (3) Power balance constraint in: This represents the power generation capacity of renewable energy power station i during time period t. and These represent the power demand for charging and discharging of the leased energy storage unit u by power station i during time period t, respectively. (4) Mutually exclusive constraints on capacity leasing bidding decisions Let the historical bidding results of station i be as follows: Then the following constraints apply: Where: Boolean variables are used This represents the historical bidding results for energy storage unit u at site j during time period t, thus avoiding conflicts between site i and site j regarding their already successful bidding decisions. (5) Constraints on curtailment rate of new energy power plants The amount of wind and solar power curtailed by the power station during the dispatch period should meet the following constraints: in: The curtailment rate refers to the percentage of curtailed power in all time periods that is not greater than the total renewable power. .

6. The pricing method for a shared energy storage capacity leasing and energy trading mechanism according to claim 1, characterized in that, In step d, The constraints consist of constraints on energy storage resource allocation, coupling constraints on the bidding period for capacity leasing, constraints on the state of charge of energy storage, and constraints on the charging and discharging power of energy storage transactions. (1) Constraints on the allocation of energy storage resources When energy storage participates in energy sharing transactions, its charging and discharging power shall not exceed its own rated power, and shall not exceed the net load demand of all users' energy transactions, that is: In the formula: For the rated capacity of energy storage, Rated energy storage capacity for providing energy trading services; This is the rated power of the energy storage. The rated power of energy storage unit u used to provide energy trading services, Whether energy storage is used to provide capacity leasing or energy trading services, its capacity and power must meet the capacity-power ratio conditions of the original energy storage, that is: in: This is the capacity-power ratio factor. (2) Coupling constraints of the bidding period for capacity leasing The capacity leasing demands reported by energy storage users to energy storage operators have a continuous leasing period, i.e., the leasing period is... The included time periods have an "AND" bidding requirement, meaning they are "packaged" into a "lease package": when deciding whether to lease storage capacity to energy storage users, energy storage operators can only choose to win bids for all time periods within the lease term, or to lose bids for none of the time periods. They cannot only meet the capacity leasing needs of some time periods. As a description of the A Boolean variable is used to determine whether a lease term was won. A value of 1 indicates a successful bid for that lease term, while a value of 0 indicates a failed bid. Simultaneously, when deciding on the winning bid for capacity leasing, energy storage operators must ensure that the winning bid periods for energy storage capacity leasing by different renewable energy power plants do not conflict. That is, an energy storage unit u can only be leased by one power plant within time period t. Furthermore, in multiple rounds of bidding, the winning bid decision cannot conflict with historical winning bid results. These constraints can be expressed as: In the formula: This indicates the leasing status of energy storage unit u by power station i during time period t. A value of 1 indicates leasing, and a value of 0 indicates no leasing. This is a Boolean variable describing the historical bidding status of leases. A value of 1 indicates that the lease has been completed in the historical bidding process; otherwise, it indicates that the lease is idle. (3) Energy storage state of charge constraints When energy storage is used for charging and discharging operations to provide energy trading services, its state of charge must also meet corresponding limit constraints, as follows: In the formula: The state of charge of the energy storage during time period t. and These are the upper and lower limits of the energy storage state of charge, respectively. (4) Constraints on charging and discharging power of energy storage trading When energy storage participates in energy sharing transactions, its charging and discharging power shall not exceed its own rated power, and shall not exceed the net load demand of all users' energy transactions, that is: In the formula: This indicates that x takes the larger value between 0 and x.

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