Method and device for determining transaction scheme of energy storage power station

Abstract

The invention is suitable for the technical field of energy storage data processing, and provides an energy storage power station transaction scheme determination method and device, and the method comprises the steps: determining the transaction scheme of an energy storage power station according to the number of energy storage power stations, the bid-winning discharge power and charging power of the energy storage power stations in an electric energy market, and the bid-winning frequency modulation capacity and frequency modulation mileage of the energy storage power stations in a frequency modulation market; establishing an energy storage power station transaction decision model by taking the maximum sum of benefits of the energy storage power station on the electric energy market and the frequency modulation market as a target; according to the number of the conventional units, the generating capacity of the conventional units in the electric energy market, and the frequency modulation capacity and the frequency modulation mileage of the conventional units in the frequency modulation market, establishing a combined clearing model of the electric energy and the frequency modulation market by taking the minimum sum of the electricity purchase cost and the auxiliary service cost as a target; and determining an energy storage power station transaction scheme based on the energy storage power station transaction decision model and the joint clearing model. According to the invention, the optimal transaction scheme of the energy storage power station can be obtained, resources are fully utilized, resource waste is reduced, and earnings of the energy storage power station are increased.

Description

Technical Field

[0001] The present application belongs to the field of energy storage data processing technology, and in particular, to a method and device for determining a transaction plan for an energy storage power station. Background Art

[0002] With the rapid increase in the scale of renewable energy power generation, there is still a lot of room for growth in my country's energy storage ratio (the ratio of energy storage to renewable energy installed capacity). The types of power markets that energy storage power stations participate in mainly include the electric energy market, the auxiliary service market, and the capacity market, giving full play to the comprehensive value of energy storage, thereby achieving multi-channel income. In the process of participating in market transactions, the transaction price of energy storage power stations will become the key to whether they can successfully bid and obtain benefits, and it is also a key factor in ensuring full utilization of resources and reducing resource waste.

[0003] At present, there are few studies on the trading strategies of independent energy storage power stations participating in the spot market and the impact of the competitive relationship between the participating entities on the energy storage transaction price and market clearing results. If the energy in the energy storage power station is not processed in time, it will cause energy waste. Therefore, unreasonable trading prices will also lead to the inability to fully utilize resources and reduce resource waste. Summary of the invention

[0004] The embodiments of the present application provide a method and device for determining a transaction plan for an energy storage power station, which comprehensively considers the situation of the energy storage power station itself and the coupling of the electric energy market and the frequency regulation auxiliary service market to obtain the optimal transaction plan for the energy storage power station, thereby making full use of resources, reducing resource waste, and increasing the revenue of the energy storage power station.

[0005] This application is implemented through the following technical solutions:

[0006] In a first aspect, an embodiment of the present application provides a method for determining a transaction plan for an energy storage power station, including:

[0007] According to the number of energy storage power stations, the discharge power and charging power of the energy storage power stations bid in the electric energy market, the frequency regulation capacity and frequency regulation mileage of the energy storage power stations bid in the frequency regulation market, a transaction decision model for energy storage power stations is established with the goal of maximizing the sum of the revenues of the energy storage power stations in the electric energy market and the frequency regulation market.

[0008] According to the number of conventional units, the power generation of conventional units in the electric energy market, the frequency regulation capacity and frequency regulation mileage of conventional units in the frequency regulation market, a joint clearing model for the electric energy and frequency regulation markets is established with the goal of minimizing the sum of electricity purchase costs and ancillary service costs.

[0009] Based on the energy storage power station transaction decision model and joint clearing model, the energy storage power station transaction plan is determined.

[0010] In combination with the first aspect, in some possible implementations, the energy storage power station transaction decision model includes a first objective function and a first constraint condition.

[0011] The first objective function is:

[0012]

[0013] Among them, F U N represents the sum of the revenue of the energy storage power station in the electric energy market and the frequency regulation market. ESS represents the number of energy storage power stations, represents the discharge power of the energy storage station k at time t, represents the charging power of the energy storage station k at time t, represents the frequency regulation capacity of the energy storage power station k that won the bid at time t, represents the frequency regulation mileage of energy storage power station k at time t, λ t Indicates the electricity price, represents the frequency regulation capacity clearing price, Indicates the frequency modulation mileage clearing price.

[0014] In combination with the first aspect, in some possible implementations, the first constraint condition includes: energy storage charging and discharging constraint, energy storage charge state constraint, energy storage declared capacity constraint and energy storage quotation constraint.

[0015] The formula for energy storage charging and discharging constraints is:

[0016]

[0017] in, represents the discharge power declared by energy storage station k at time t, represents the charging power declared by energy storage station k at time t, represents the maximum discharge power of the energy storage station k, represents the maximum charging power of energy storage station k, is a 0-1 variable representing the discharge state of the energy storage station k. It is a 0-1 variable representing the charging status of the energy storage station k.

[0018] The formula for energy storage charge state constraint is:

[0019]

[0020] in, represents the maximum capacity allowed by the energy storage station k, represents the minimum capacity allowed by the energy storage station k, represents the remaining capacity of energy storage station k at time t, represents the discharge efficiency of the energy storage power station k, Represents the charging efficiency of the energy storage station k.

[0021] The formula for energy storage capacity constraints is:

[0022]

[0023] in, represents the frequency regulation capacity declared by energy storage power station k at time t, represents the frequency regulation mileage declared by energy storage power station k at time t, represents the maximum frequency regulation capacity of the energy storage station k, Represents the frequency regulation mileage multiplier of energy storage station k.

[0024] The formula for energy storage bidding constraints is:

[0025]

[0026] in, represents the discharge price declared by energy storage power station k at time t, represents the charging price declared by energy storage station k at time t, represents the frequency regulation capacity price of energy storage power station k at time t, represents the frequency regulation mileage price declared by energy storage station k at time t, represents the upper limit of the discharge price, Indicates the upper limit of charging price, represents the upper limit of the frequency regulation capacity price, Indicates the upper limit of the frequency modulation mileage price.

[0027] In combination with the first aspect, in some possible implementations, the joint clearing model includes: a second objective function and a second constraint condition.

[0028] The formula of the second objective function is:

[0029]

[0030] Among them, N G Indicates the number of conventional units, represents the winning power generation of conventional unit m at time t, represents the frequency regulation capacity of conventional unit m at time t, represents the frequency regulation mileage of conventional unit m at time t, represents the power generation price declared by conventional unit m at time t, represents the frequency regulation capacity price declared by conventional unit m at time t, It represents the frequency regulation mileage price declared by conventional unit m at time t.

[0031] In combination with the first aspect, in some possible implementations, the second constraint condition includes: grid operation constraints, frequency regulation capacity and mileage demand constraints, and market clearing rule constraints.

[0032] The formula for grid operation constraints is:

[0033]

[0034] θ n =1:ε1,n=1

[0035] Among them, φ g (n) represents the set of conventional unit loads at node n, φ ess (n) represents the set of energy storage power station loads at node n, φ d (n) represents the set of power loads on node n, φ d (n) represents the set of all nodes connected to node n, Ψ(n) represents all branches connected to node n, represents the load of node n at time t on day d, B nq represents the line admittance between nodes n and q, θ n,t represents the phase angle of node n at time t, θ q,t represents the phase angle of node q at time t, L l represents the transmission capacity limit of line l, λ n,t represents the dual variable of the node power balance constraint, and represents the dual variable of the transmission capacity constraint of each line, and ε1 represents the dual variable of the phase angle constraint of the equilibrium node.

[0036] The formula for frequency regulation capacity and mileage demand constraints is:

[0037]

[0038] in, represents the frequency modulation capacity requirement, Indicates frequency modulation mileage requirement.

[0039] The formula for the market clearing rule constraint is:

[0040]

[0041] in, Indicates the upper limit of active output of conventional unit m, Indicates the lower limit of active output of conventional unit m, represents the frequency regulation mileage multiplier of conventional unit m,

[0042] and represents the dual variable of the bidding capacity constraints of energy storage power stations and conventional units, and represents the dual variable of the winning mileage constraint, and represents the dual variable of the charging and discharging power constraints of the energy storage power station, and Represents the dual variable of the conventional unit output constraint.

[0043] In conjunction with the first aspect, in some possible implementations, based on the energy storage power station transaction decision model and the joint clearing model, determining the energy storage power station transaction plan includes:

[0044] The joint clearing model is transformed into the third constraint condition through KKT conditions and duality theory.

[0045] Based on the third constraint and the energy storage power station transaction decision model, the energy storage power station transaction plan is determined.

[0046] In combination with the first aspect, in some possible implementations, the formula of the third constraint condition is:

[0047]

[0048] θ n =1:ε1,n=1

[0049]

[0050]

[0051] In combination with the first aspect, in some possible implementations, based on the third constraint condition and the energy storage power station transaction decision model, determining the energy storage power station transaction plan includes:

[0052] The third constraint condition and the energy storage power station transaction decision model are linearized to obtain a linearized model.

[0053] The linearized model is solved by a commercial solver to obtain the electricity price, frequency regulation capacity clearing price and frequency regulation mileage clearing price, that is, to determine the energy storage power station trading plan.

[0054] In combination with the first aspect, in some possible implementations, the third constraint condition and the energy storage power station transaction decision model are linearized to obtain a linearized model, including:

[0055] The third constraint condition is linearized by the big M method to obtain the linearized constraint condition.

[0056] The first objective function is linearized through strong duality theory and KKT optimal conditions to obtain the linearized objective function.

[0057] Based on the linearized constraints and the linearized objective function, a linearized model is obtained.

[0058] In a second aspect, an embodiment of the present application provides a device for determining a transaction plan for an energy storage power station, including:

[0059] The first modeling module is used to establish a transaction decision model for energy storage power stations based on the number of energy storage power stations, the discharge power and charging power bid by the energy storage power stations in the electric energy market, and the frequency regulation capacity and frequency regulation mileage bid by the energy storage power stations in the frequency regulation market, with the goal of maximizing the sum of the profits of the energy storage power stations in the electric energy market and the frequency regulation market.

[0060] The second modeling module is used to establish a joint clearing model for the electric energy and frequency regulation markets based on the number of conventional units, the power generation bid by conventional units in the electric energy market, the frequency regulation capacity and frequency regulation mileage bid by conventional units in the frequency regulation market, with the goal of minimizing the sum of electricity purchase costs and ancillary service costs.

[0061] The result output module is used to determine the energy storage power station transaction plan based on the energy storage power station transaction decision model and the joint clearing model.

[0062] It can be understood that the beneficial effects of the second aspect mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0063] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0064] This application fully considers the quotation information of energy storage power stations and conventional units, as well as the coupling relationship between the electric energy and frequency regulation markets, and realizes the strategic bidding of energy storage power stations when participating in the electric energy and frequency regulation auxiliary service markets at the same time, so as to maximize their own interests. When energy storage power stations participate in the electric energy and frequency regulation auxiliary service markets at the same time, they use more electricity to provide frequency regulation services to obtain corresponding benefits. At the same time, due to its better frequency regulation performance, energy storage is called first in the frequency regulation market, and can undertake most of the frequency regulation tasks of the system, and can fully call on the resources of the storage power station, reducing resource waste while ensuring the benefits of the energy storage power station.

[0065] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present specification. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0067] Figure 1 It is a flowchart of a method for determining a transaction plan for an energy storage power station provided in an embodiment of the present application;

[0068] Figure 2 It is a structural diagram of a device for determining a transaction plan for an energy storage power station provided in one embodiment of the present application. DETAILED DESCRIPTION

[0069] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0070] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0071] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0072] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0073] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0074] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0075] The present application embodiment provides a method for determining a transaction plan for an energy storage power station. Figure 1 is a schematic diagram of the process of determining a transaction plan for an energy storage power station provided in an embodiment of the present application, with reference to Figure 1 The method for determining the transaction plan for the energy storage power station is described in detail as follows:

[0076] Step 101, based on the number of energy storage power stations, the discharge power and charging power of the energy storage power stations bid in the electric energy market, and the frequency regulation capacity and frequency regulation mileage of the energy storage power stations bid in the frequency regulation market, a transaction decision model for energy storage power stations is established with the goal of maximizing the sum of the revenues of the energy storage power stations in the electric energy market and the frequency regulation market.

[0077] Exemplarily, the energy storage power station transaction decision model may include a first objective function and a first constraint condition.

[0078] The first objective function can be:

[0079]

[0080] Among them, F U N represents the sum of the revenue of the energy storage power station in the electric energy market and the frequency regulation market. ESS represents the number of energy storage power stations, represents the discharge power of the energy storage station k at time t, represents the charging power of the energy storage station k at time t, represents the frequency regulation capacity of the energy storage power station k that won the bid at time t, represents the frequency regulation mileage of energy storage power station k at time t, λ t Indicates the electricity price, represents the frequency regulation capacity clearing price, Indicates the frequency modulation mileage clearing price.

[0081] For example, the bidding of energy storage power stations needs to consider constraints in terms of declared price and capacity limit as well as charging and discharging capacity. The first constraint condition may include: energy storage charging and discharging constraint, energy storage state of charge constraint, energy storage declared capacity constraint and energy storage quotation constraint.

[0082] The formula for energy storage charging and discharging constraints can be:

[0083]

[0084] in, represents the discharge power declared by energy storage station k at time t, represents the charging power declared by energy storage station k at time t, represents the maximum discharge power of the energy storage station k, represents the maximum charging power of energy storage station k, is a 0-1 variable representing the discharge state of the energy storage station k. It is a 0-1 variable representing the charging status of the energy storage station k.

[0085] The formula for energy storage charge state constraint can be:

[0086]

[0087] in, represents the maximum capacity allowed by the energy storage station k, represents the minimum capacity allowed by the energy storage station k, represents the remaining capacity of energy storage station k at time t, represents the discharge efficiency of the energy storage power station k, Represents the charging efficiency of the energy storage station k.

[0088] The formula for energy storage capacity constraints can be:

[0089]

[0090] in, represents the frequency regulation capacity declared by energy storage power station k at time t, represents the frequency regulation mileage declared by energy storage power station k at time t, represents the maximum frequency regulation capacity of energy storage station k, Represents the frequency regulation mileage multiplier of energy storage station k.

[0091] The formula for energy storage bidding constraints can be:

[0092]

[0093] in, represents the discharge price declared by energy storage power station k at time t, represents the charging price declared by energy storage station k at time t, represents the frequency regulation capacity price of energy storage power station k at time t, represents the frequency regulation mileage price declared by energy storage station k at time t, represents the upper limit of the discharge price, Indicates the upper limit of charging price, represents the upper limit of the frequency regulation capacity price, Indicates the upper limit of the frequency modulation mileage price.

[0094] Step 102, based on the number of conventional units, the power generation bid by conventional units in the electric energy market, the frequency regulation capacity and frequency regulation mileage bid by conventional units in the frequency regulation market, a joint clearing model for the electric energy and frequency regulation markets is established with the goal of minimizing the sum of the power purchase cost and the ancillary service fee.

[0095] Exemplarily, the joint clearing model may include: a second objective function and a second constraint.

[0096] The formula of the second objective function can be:

[0097]

[0098] Among them, N G Indicates the number of conventional units, represents the winning power generation of conventional unit m at time t, represents the frequency regulation capacity of conventional unit m at time t, represents the frequency regulation mileage of conventional unit m at time t, represents the power generation price declared by conventional unit m at time t, represents the frequency regulation capacity price declared by conventional unit m at time t, It represents the frequency regulation mileage price declared by conventional unit m at time t.

[0099] Exemplarily, market clearing needs to comply with clearing rules and grid operation constraints. The second constraint may include: grid operation constraints, frequency regulation capacity and mileage demand constraints, and market clearing rule constraints.

[0100] The formula for grid operation constraints can be:

[0101]

[0102] θ n =1:ε1,n=1

[0103] Among them, φ g (n) represents the set of conventional unit loads at node n, φ ess (n) represents the set of energy storage power station loads at node n, φ d(n) represents the set of power loads on node n, φ d (n) represents the set of all nodes connected to node n, Ψ(n) represents all branches connected to node n, represents the load of node n at time t on day d, B nq represents the line admittance between nodes n and q, θ n,t represents the phase angle of node n at time t, θ q,t represents the phase angle of node q at time t, L l represents the transmission capacity limit of line l, λ n,t represents the dual variable of the node power balance constraint, and represents the dual variable of the transmission capacity constraint of each line, and ε1 represents the dual variable of the phase angle constraint of the equilibrium node.

[0104] The formula for frequency regulation capacity and mileage demand constraints can be:

[0105]

[0106] in, represents the frequency modulation capacity requirement, Indicates frequency modulation mileage requirement.

[0107] The formula for the market clearing rule constraint can be:

[0108]

[0109] in, Indicates the upper limit of active output of conventional unit m, Indicates the lower limit of active output of conventional unit m, represents the frequency regulation mileage multiplier of conventional unit m,

[0110] and represents the dual variable of the bidding capacity constraints of energy storage power stations and conventional units, and represents the dual variable of the winning mileage constraint, and represents the dual variable of the charging and discharging power constraints of the energy storage power station, and Represents the dual variable of the conventional unit output constraint.

[0111] Step 103: Determine the energy storage power station transaction plan based on the energy storage power station transaction decision model and the joint clearing model.

[0112] Specifically, there is a strong coupling relationship between the two models, and the model contains nonlinear terms, which makes it difficult to solve directly. In order to facilitate the solution, the joint clearing model can be converted into the constraints of the energy storage power station transaction decision model to facilitate the solution.

[0113] Exemplarily, based on the energy storage power station transaction decision model and the joint clearing model, determining the energy storage power station transaction plan may include:

[0114] The joint clearing model is transformed into the third constraint condition through KKT conditions and duality theory.

[0115] Based on the third constraint and the energy storage power station transaction decision model, the energy storage power station transaction plan is determined.

[0116] Exemplarily, the formula of the third constraint condition may be:

[0117]

[0118] θ n =1:ε1,n=1

[0119]

[0120]

[0121]

[0122] Exemplarily, determining the energy storage power station transaction plan based on the third constraint condition and the energy storage power station transaction decision model may include:

[0123] The third constraint condition and the energy storage power station transaction decision model are linearized to obtain a linearized model.

[0124] The linearized model is solved by a commercial solver to obtain the electricity price, frequency regulation capacity clearing price and frequency regulation mileage clearing price, that is, to determine the energy storage power station trading plan.

[0125] Specifically, the constraints in the third constraint condition are still nonlinear, and can be linearized using the big M method. By introducing 0-1 variables, the complementary constraint condition of the form 0≤af⊥b≥0 is transformed into:

[0126] af≤M·v

[0127] b≤M·(1-v)

[0128] Among them, M is a sufficiently large constant and v is a 0-1 variable.

[0129] Exemplarily, linearizing the third constraint condition and the energy storage power station transaction decision model to obtain a linearized model may include:

[0130] The third constraint condition is linearized by the big M method to obtain the linearized constraint condition.

[0131] The first objective function is linearized through strong duality theory and KKT optimal conditions to obtain the linearized objective function.

[0132] Based on the linearized constraints and the linearized objective function, a linearized model is obtained.

[0133] Exemplarily, the linearized objective function may be:

[0134]

[0135] Specifically, when the commercial solver solves the linearized model, the objective function is the linearized objective function, and the constraints at this time are the first constraint and the linearized constraint. After the objective function and the constraints are input into the commercial solver, the electricity price, the frequency regulation capacity clearing price and the frequency regulation mileage clearing price of the energy storage power station can be obtained, and then the energy storage power station transaction plan can be obtained according to the amount of the winning bid.

[0136] The above-mentioned method for determining the transaction plan of the energy storage power station fully considers the quotation information of the energy storage power station and conventional units and the coupling relationship between the electric energy and frequency regulation markets, and realizes the strategic bidding of the energy storage power station when participating in the electric energy and frequency regulation auxiliary service markets at the same time, so as to maximize its own interests. When the energy storage power station participates in the electric energy and frequency regulation auxiliary service markets at the same time, it uses more electricity to provide frequency regulation services to obtain corresponding benefits. At the same time, due to its better frequency regulation performance, energy storage is called first in the frequency regulation market, and can undertake most of the frequency regulation tasks of the system, which can fully call the resources of the storage power station, reduce resource waste and ensure the benefits of the energy storage power station.

[0137] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0138] Corresponding to the method for determining the energy storage power station transaction plan described in the above embodiment, Figure 2 A structural block diagram of a device for determining a transaction plan for an energy storage power station provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0139] See also Figure 2 , the energy storage power station transaction plan determination device in the embodiment of the present application may include:

[0140] The first modeling module 201 is used to establish an energy storage power station transaction decision model based on the number of energy storage power stations, the discharge power and charging power of the energy storage power stations bid in the electric energy market, and the frequency regulation capacity and frequency regulation mileage of the energy storage power stations bid in the frequency regulation market, with the goal of maximizing the sum of the revenues of the energy storage power stations in the electric energy market and the frequency regulation market;

[0141] The second modeling module 202 is used to establish a joint clearing model for the electric energy and frequency regulation markets with the goal of minimizing the sum of the power purchase cost and the ancillary service fee according to the number of conventional units, the power generation bid by the conventional units in the electric energy market, and the frequency regulation capacity and frequency regulation mileage bid by the conventional units in the frequency regulation market;

[0142] The result output module 203 is used to determine the energy storage power station transaction plan based on the energy storage power station transaction decision model and the joint clearing model.

[0143] Exemplarily, the energy storage power station transaction decision model may include a first objective function and a first constraint condition.

[0144] The first objective function can be:

[0145]

[0146] Among them, F U N represents the sum of the revenue of the energy storage power station in the electric energy market and the frequency regulation market. ESS represents the number of energy storage power stations, represents the discharge power of the energy storage station k at time t, represents the charging power of the energy storage station k at time t, represents the frequency regulation capacity of the energy storage power station k that won the bid at time t, represents the frequency regulation mileage of energy storage power station k at time t, λ t Indicates the electricity price, represents the frequency regulation capacity clearing price, Indicates the frequency modulation mileage clearing price.

[0147] Exemplarily, the first constraint condition may include: energy storage charging and discharging constraint, energy storage charge state constraint, energy storage declared capacity constraint and energy storage quotation constraint.

[0148] The formula for energy storage charging and discharging constraints can be:

[0149]

[0150] in, represents the discharge power declared by energy storage station k at time t, represents the charging power declared by energy storage station k at time t, represents the maximum discharge power of the energy storage station k, represents the maximum charging power of energy storage station k, is a 0-1 variable representing the discharge state of the energy storage station k. It is a 0-1 variable representing the charging status of the energy storage station k.

[0151] The formula for energy storage charge state constraint can be:

[0152]

[0153] in, represents the maximum capacity allowed by the energy storage station k, represents the minimum capacity allowed by the energy storage station k, represents the remaining capacity of energy storage station k at time t, represents the discharge efficiency of the energy storage power station k, Represents the charging efficiency of the energy storage station k.

[0154] The formula for energy storage capacity constraints can be:

[0155]

[0156] in, represents the frequency regulation capacity declared by energy storage power station k at time t, represents the frequency regulation mileage declared by energy storage power station k at time t, represents the maximum frequency regulation capacity of energy storage station k, Represents the frequency regulation mileage multiplier of energy storage station k.

[0157] The formula for energy storage bidding constraints can be:

[0158]

[0159] in, represents the discharge price declared by energy storage power station k at time t, represents the charging price declared by energy storage station k at time t, represents the frequency regulation capacity price of energy storage power station k at time t, represents the frequency regulation mileage price declared by energy storage station k at time t, represents the upper limit of the discharge price, Indicates the upper limit of charging price, represents the upper limit of the frequency regulation capacity price, Indicates the upper limit of the frequency modulation mileage price.

[0160] Exemplarily, the joint clearing model may include: a second objective function and a second constraint.

[0161] The formula of the second objective function can be:

[0162]

[0163] Among them, N G Indicates the number of conventional units, represents the winning power generation of conventional unit m at time t, represents the frequency regulation capacity of conventional unit m at time t, represents the frequency regulation mileage of conventional unit m at time t, represents the power generation price declared by conventional unit m at time t, represents the frequency regulation capacity price declared by conventional unit m at time t, It represents the frequency regulation mileage price declared by conventional unit m at time t.

[0164] Exemplarily, the second constraint condition may include: grid operation constraints, frequency regulation capacity and mileage demand constraints, and market clearing rule constraints.

[0165] The formula for grid operation constraints can be:

[0166]

[0167] θ n =1:ε1,n=1

[0168] Among them, φ g (n) represents the set of conventional unit loads at node n, φ ess (n) represents the set of energy storage power station loads at node n, φ d (n) represents the set of power loads on node n, φ d (n) represents the set of all nodes connected to node n, Ψ(n) represents all branches connected to node n, represents the load of node n at time t on day d, B nq represents the line admittance between nodes n and q, θ n,t represents the phase angle of node n at time t, θ q,t represents the phase angle of node q at time t, L l represents the transmission capacity limit of line l, λ n,t represents the dual variable of the node power balance constraint, and represents the dual variable of the transmission capacity constraint of each line, and ε1 represents the dual variable of the phase angle constraint of the equilibrium node.

[0169] The formula for frequency regulation capacity and mileage demand constraints can be:

[0170]

[0171] in, represents the frequency modulation capacity requirement, Indicates frequency modulation mileage requirement.

[0172] The formula for the market clearing rule constraint can be:

[0173]

[0174] in, Indicates the upper limit of active output of conventional unit m, Indicates the lower limit of active output of conventional unit m, represents the frequency regulation mileage multiplier of conventional unit m,

[0175] and represents the dual variable of the bidding capacity constraints of energy storage power stations and conventional units, and represents the dual variable of the winning mileage constraint, and represents the dual variable of the charging and discharging power constraints of the energy storage power station, and Represents the dual variable of the conventional unit output constraint.

[0176] Exemplarily, the result output module 203 may also be used for:

[0177] The joint clearing model is transformed into the third constraint condition through KKT conditions and duality theory.

[0178] Based on the third constraint and the energy storage power station transaction decision model, the energy storage power station transaction plan is determined.

[0179] Exemplarily, the formula of the third constraint condition may be:

[0180]

[0181] θ n =1:ε1,n=1

[0182]

[0183]

[0184] Exemplarily, the result output module 203 may also be used for:

[0185] The third constraint condition and the energy storage power station transaction decision model are linearized to obtain a linearized model.

[0186] The linearized model is solved by a commercial solver to obtain the electricity price, frequency regulation capacity clearing price and frequency regulation mileage clearing price, that is, to determine the energy storage power station trading plan.

[0187] Exemplarily, the result output module 203 may also be used for:

[0188] The third constraint condition is linearized by the big M method to obtain the linearized constraint condition.

[0189] The first objective function is linearized through strong duality theory and KKT optimal conditions to obtain the linearized objective function.

[0190] Based on the linearized constraints and the linearized objective function, a linearized model is obtained.

[0191] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0192] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0193] Those of ordinary skill in the art will appreciate that the templates, units, and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0194] If the module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, it can implement the steps of the above-mentioned various energy storage power station transaction scheme determination method embodiments. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory, random access memory, electrical carrier signal, telecommunication signal and software distribution medium.

[0195] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for determining a transaction plan for an energy storage power station, characterized in that: include: According to the number of energy storage power stations, the discharge power and charging power of energy storage power stations in the electric energy market, and the frequency regulation capacity and frequency regulation mileage of energy storage power stations in the frequency regulation market, a transaction decision model for energy storage power stations is established with the goal of maximizing the sum of the revenue of energy storage power stations in the electric energy market and the frequency regulation market; According to the number of conventional units, the power generation of conventional units in the electric energy market, the frequency regulation capacity and frequency regulation mileage of conventional units in the frequency regulation market, a joint clearing model of the electric energy and frequency regulation market is established with the goal of minimizing the sum of the power purchase cost and the ancillary service fee. Based on the energy storage power station transaction decision model and the joint clearing model, an energy storage power station transaction plan is determined.

2. The method for determining a transaction plan for an energy storage power station according to claim 1, characterized in that: The energy storage power station transaction decision model includes a first objective function and a first constraint condition; The first objective function is: Among them, F U N represents the sum of the revenue of the energy storage power station in the electric energy market and the frequency regulation market. ESS represents the number of energy storage power stations, represents the discharge power of the energy storage station k at time t, represents the charging power of the energy storage station k at time t, represents the frequency regulation capacity of the energy storage power station k that won the bid at time t, represents the frequency regulation mileage of energy storage power station k at time t, t Indicates the electricity price, represents the frequency regulation capacity clearing price, Indicates the frequency modulation mileage clearing price.

3. The method for determining a transaction plan for an energy storage power station according to claim 2, characterized in that: The first constraint conditions include: energy storage charging and discharging constraint, energy storage charge state constraint, energy storage declared capacity constraint and energy storage quotation constraint; The formula for the energy storage charge and discharge constraint is: in, represents the discharge power declared by energy storage station k at time t, represents the charging power declared by energy storage station k at time t, represents the maximum discharge power of the energy storage station k, represents the maximum charging power of energy storage station k, is a 0-1 variable representing the discharge state of the energy storage station k. is a 0-1 variable indicating the charging state of the energy storage station k; The formula for the energy storage charge state constraint is: in, represents the maximum capacity allowed by the energy storage station k, represents the minimum capacity allowed by the energy storage station k, represents the remaining capacity of energy storage station k at time t, represents the discharge efficiency of the energy storage power station k, represents the charging efficiency of the energy storage station k; The formula for energy storage capacity constraint is: in, represents the frequency regulation capacity declared by energy storage power station k at time t, represents the frequency regulation mileage declared by energy storage power station k at time t, represents the maximum frequency regulation capacity of the energy storage station k, represents the frequency regulation mileage multiplier of the energy storage power station k; The formula for the energy storage bidding constraint is: in, represents the discharge price declared by energy storage power station k at time t, represents the charging price declared by energy storage station k at time t, represents the frequency regulation capacity price of energy storage power station k at time t, represents the frequency regulation mileage price declared by energy storage power station k at time t, represents the upper limit of the discharge price, Indicates the upper limit of charging price, represents the upper limit of the frequency regulation capacity price, Indicates the upper limit of the frequency modulation mileage price.

4. The method for determining a transaction plan for an energy storage power station according to claim 3, characterized in that: The joint clearing model includes: a second objective function and a second constraint condition; The formula of the second objective function is: Among them, N G Indicates the number of conventional units, represents the winning power generation of conventional unit m at time t, represents the frequency regulation capacity of conventional unit m at time t, represents the frequency regulation mileage of conventional unit m at time t, represents the power generation price declared by conventional unit m at time t, represents the frequency regulation capacity price declared by conventional unit m at time t, It represents the frequency regulation mileage price declared by conventional unit m at time t.

5. The method for determining a transaction plan for an energy storage power station according to claim 4, characterized in that: The second constraint conditions include: power grid operation constraints, frequency regulation capacity and mileage demand constraints, and market clearing rule constraints; The formula for the grid operation constraint is: i n =1:ε1,n=1 Among them, φ g (n) represents the set of conventional unit loads at node n, φ ess (n) represents the set of energy storage power station loads at node n, φ d (n) represents the set of power loads on node n, φ d (n) represents the set of all nodes connected to node n, Ψ(n) represents all branches connected to node n, represents the load of node n at time t on day d, B nq represents the line admittance between nodes n and q, θ n,t represents the phase angle of node n at time t, θ q,t represents the phase angle of node q at time t, L l represents the transmission capacity limit of line l, λ n,t represents the dual variable of the node power balance constraint, and represents the dual variable of the transmission capacity constraint of each line, ε1 represents the dual variable of the phase angle constraint of the equilibrium node; The formula for the frequency modulation capacity and mileage requirement constraints is: in, represents the frequency modulation capacity requirement, Indicates frequency modulation mileage requirement; The formula for the market clearing rule constraint is: in, Indicates the upper limit of active output of conventional unit m, Indicates the lower limit of active output of conventional unit m, represents the frequency regulation mileage multiplier of conventional unit m, and represents the dual variable of the bidding capacity constraints of energy storage power stations and conventional units, and represents the dual variable of the winning mileage constraint, and represents the dual variable of the charging and discharging power constraints of the energy storage power station, and Represents the dual variable of the conventional unit output constraint.

6. The method for determining a transaction plan for an energy storage power station according to claim 5, characterized in that: The step of determining the energy storage power station transaction plan based on the energy storage power station transaction decision model and the joint clearing model includes: The joint clearing model is transformed into the third constraint condition through KKT condition and duality theory; Based on the third constraint condition and the energy storage power station transaction decision model, an energy storage power station transaction plan is determined.

7. The method for determining a transaction plan for an energy storage power station according to claim 6, characterized in that: The formula of the third constraint condition is: i n =1:ε1,n=1 8. The method for determining a transaction plan for an energy storage power station according to claim 6, characterized in that: The determining of the energy storage power station transaction plan based on the third constraint condition and the energy storage power station transaction decision model includes: Linearizing the third constraint condition and the energy storage power station transaction decision model to obtain a linearized model; The linearized model is solved by a commercial solver to obtain the electricity price, the frequency regulation capacity clearing price and the frequency regulation mileage clearing price, that is, to determine the energy storage power station transaction plan.

9. The method for determining a transaction plan for an energy storage power station according to claim 1, characterized in that: The linearization process of the third constraint condition and the energy storage power station transaction decision model to obtain a linearized model includes: Linearize the third constraint condition by using the Big M method to obtain a linearized constraint condition; The first objective function is linearized by using strong duality theory and KKT optimal conditions to obtain a linearized objective function; Based on the linearization constraint condition and the linearization objective function, the linearization model is obtained.

10. A device for determining a transaction plan for an energy storage power station, characterized in that: include: The first modeling module is used to establish an energy storage power station transaction decision model based on the number of energy storage power stations, the discharge power and charging power of the energy storage power stations bid in the electric energy market, and the frequency regulation capacity and frequency regulation mileage of the energy storage power stations bid in the frequency regulation market, with the goal of maximizing the sum of the benefits of the energy storage power stations in the electric energy market and the frequency regulation market; The second modeling module is used to establish a joint clearing model for the electric energy and frequency regulation markets with the goal of minimizing the sum of the power purchase cost and the ancillary service fee based on the number of conventional units, the power generation bid by conventional units in the electric energy market, and the frequency regulation capacity and frequency regulation mileage bid by conventional units in the frequency regulation market; The result output module is used to determine the energy storage power station transaction plan based on the energy storage power station transaction decision model and the joint clearing model.

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