Capacity and operation planning method and system of energy storage system under electric power spot mechanism

Abstract

The invention provides a capacity and operation planning method and system for an energy storage system under an electric power spot mechanism, and the method comprises the steps: carrying out the modeling of a planning index, operation loss and utilization degree of energy storage under the spot mechanism based on a framework in which the energy storage participates in the electric power spot mechanism; establishing an energy storage full life cycle planning index model, converting an energy storage full life cycle planning index into a single day through a capital recovery coefficient, and establishing a daily operation total loss model of the conventional thermal power generating unit; according to clearing requirements of a spot mechanism, balance constraints are established, and a DC power flow model is adopted to establish power transmission network linear power flow constraints; the method comprises the following steps: establishing a first-stage energy storage capacity configuration optimization model by combining a balance constraint and a power transmission network linear power flow constraint and by taking minimum energy storage daily planning indexes and conventional unit operation loss as targets, and solving optimal capacity configuration of energy storage; and in order to improve the energy storage utilization rate and reduce the system loss, establishing a second-stage energy storage optimization operation model, and solving to obtain an energy storage optimal operation plan.

Description

Technical Field

[0001] The present invention relates to the technical field of power system energy storage planning and power market operation, and in particular to a capacity and operation planning method and system for an energy storage system under a power spot mechanism, as well as a corresponding computer terminal and a computer-readable storage medium. Background Art

[0002] With the gradual opening of the power market and the establishment of the power spot market, energy storage systems in the power system have begun to play an increasingly important role. Energy storage systems can not only balance power supply and demand and improve the stability and reliability of the power system, but also obtain economic benefits by participating in the power market. However, in the power spot market environment, the capacity configuration and operation strategy of energy storage systems face many challenges.

[0003] First, the price volatility in the electricity spot market is large, and the energy storage system needs to charge when the electricity price is low and discharge when the electricity price is high to maximize profits. However, the uncertainty of electricity prices will cause the energy storage system to face higher operational risks.

[0004] Secondly, the spot market has high requirements for system response speed and accuracy. When participating in frequency regulation auxiliary services, energy storage systems need to respond quickly to frequency changes and provide regulation capabilities, which places higher requirements on the charging and discharging rates and control systems of energy storage equipment.

[0005] In addition, the life cycle cost of energy storage systems is high, and there will be certain losses during the frequent charging and discharging process, which will affect the economy and sustainability of the system. In order to maximize benefits and cost-effectiveness, reasonable optimization is needed in terms of capacity configuration and operation planning.

[0006] In response to the above challenges, some energy storage system planning methods have been proposed. However, most of these methods have the following problems:

[0007] These methods lack comprehensive consideration of the dynamic characteristics of the electricity spot market, especially when electricity prices fluctuate greatly or frequency regulation needs are frequent, the flexibility and adaptability of the planning model are low. In addition, most methods fail to fully consider the full life cycle cost of the energy storage system in the optimization model, resulting in the economic performance not meeting expectations in practical applications.

[0008] Therefore, in practical applications, these methods often fail to achieve the effect of both ensuring system operation stability and improving the economic benefits of the energy storage system. Summary of the invention

[0009] In view of the above-mentioned deficiencies in the prior art, the present invention provides a method and system for capacity and operation planning of an energy storage system under a power spot mechanism, and also provides a corresponding computer terminal and computer-readable storage medium.

[0010] According to one aspect of the present invention, a method for capacity and operation planning of an energy storage system under a power spot mechanism is provided, comprising:

[0011] Based on the framework of energy storage participating in the electricity spot mechanism, the planning indicators, operating losses and utilization of energy storage under the spot mechanism are modeled; wherein the spot mechanism includes: spot electricity energy mechanism and frequency regulation auxiliary service mechanism;

[0012] Establish a life cycle planning indicator model for energy storage, and convert the life cycle planning indicators of energy storage to a single day through the capital recovery coefficient. At the same time, establish a daily operation total loss model for conventional thermal power units;

[0013] According to the clearing requirements of the spot power mechanism and the frequency regulation auxiliary service mechanism, the balance constraints under the two mechanisms are established, and the DC power flow model is used to establish the linear power flow constraints of the transmission network;

[0014] Combining the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network, with the goal of minimizing the daily planning indicators of energy storage and the operating losses of conventional units, an optimization model for energy storage capacity configuration in the first stage is established to solve the optimal capacity configuration of energy storage.

[0015] Combining the optimal capacity configuration of energy storage and the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network, with the goal of improving energy storage utilization and reducing system losses, a second-stage energy storage optimization operation model is established to solve the optimal operation plan of energy storage.

[0016] Preferably, the framework based on energy storage participating in the electricity spot mechanism models the planning indicators, operating losses and utilization of energy storage under the spot mechanism, including:

[0017] The model of energy storage system participating in spot electricity energy mechanism and frequency regulation auxiliary service mechanism as an independent entity is analyzed; among which:

[0018] Under the spot electricity energy mechanism, conventional thermal power units report loss coefficients, energy storage systems report operating parameters and charge-discharge loss coefficients, and users report electricity demand;

[0019] In the frequency regulation auxiliary service mechanism, independent energy storage simultaneously applies for frequency regulation capacity and mileage as well as capacity and mileage loss coefficients during the day-ahead electricity energy application stage;

[0020] Define the index of energy storage as j, the index and set of time period as t and Γ respectively, then the planning index of energy storage j under the spot electricity energy mechanism and frequency regulation auxiliary service mechanism is expressed as:

[0021]

[0022] In the formula, is the planning indicator of energy storage j under the spot electricity energy mechanism; It is the planning indicator of energy storage j under the frequency regulation auxiliary service mechanism; are the charging and discharging powers reported by energy storage j in time period t respectively; are the charging and discharging losses reported by energy storage j in time period t respectively. are the frequency regulation capacity and mileage declared by energy storage j in time period t, respectively; are the frequency regulation capacity loss and mileage loss reported by energy storage j in time period t, respectively;

[0023] According to the load forecast and frequency regulation requirements, the joint optimization of electric energy and auxiliary services is performed, and the total utilization is calculated. The index of the node where the energy storage is located is defined as s. Then the utilization of energy storage j in the spot electric energy mechanism and the frequency regulation auxiliary service mechanism is expressed as:

[0024]

[0025] In the formula, is the utilization of energy storage j under the spot electricity energy mechanism; is the utilization of energy storage j under the frequency regulation auxiliary service mechanism; are the discharge and charge capacities of energy storage j in time period t respectively; are the frequency regulation capacity and mileage of energy storage j in time period t; LMP s,t is the utilization coefficient of node s in time period t; are the frequency regulation capacity loss and mileage utilization coefficient in time period t respectively.

[0026] Preferably, a life cycle planning indicator model for energy storage is established, and the life cycle planning indicators for energy storage are converted to a single day through the capital recovery coefficient, including:

[0027] Model the full life cycle planning indicators of the energy storage system and define the total planned energy storage power as P ESS (MW), the total planned capacity is W ESS (MWh), then:

[0028]

[0029] In the formula, is the initial one-time configuration indicator of energy storage j; is the annual maintenance index of energy storage j; is the energy storage j retirement recovery index. α and β are the energy storage power planning index coefficient (MW / yuan) and capacity planning index coefficient (MWh / yuan) respectively; γ is the energy storage annual maintenance index coefficient; r is the equipment residual value rate;

[0030] Using the capital recovery factor δ, the full life cycle planning indicators of energy storage are converted to daily, and the result is:

[0031]

[0032] In the formula, ν is the annual profit rate; T is the energy storage life; is the daily average planning index of energy storage j.

[0033] Preferably, the establishment of a daily operation total loss model for conventional thermal power units includes:

[0034] Assume that the index of the conventional thermal power unit is i and the output is In time period t, the running state is y i,t ,y i,t =1 means the unit is in operation, y i,t =0 means the unit is in shutdown state. The index and set of the number of segments allowed to be declared by the spot electricity energy mechanism are k and K respectively. The startup loss coefficient is The running and starting losses are expressed as:

[0035]

[0036] In the formula, F i Ene,CG is the operating loss of conventional thermal power unit i under the spot electricity energy mechanism; F i Sta,CG is the starting loss index of conventional thermal power unit i; is the loss coefficient of conventional thermal power unit i in the kth output stage; is the output declared by conventional thermal power unit i in the kth output section of time period t, and the sum of the outputs of each section is

[0037] The loss of conventional thermal power units participating in the frequency regulation auxiliary service mechanism is expressed as follows:

[0038]

[0039] In the formula, F i Aux,CG is the loss of conventional thermal power unit i in the frequency regulation auxiliary service mechanism; and are the frequency regulation capacity and mileage loss of conventional thermal power unit i in period t respectively; They are the frequency regulation capacity and mileage declared by conventional thermal power unit i in time period t respectively.

[0040] Preferably, according to the clearing requirements of the spot electric energy mechanism and the frequency regulation auxiliary service mechanism, the balance constraints under the two mechanisms are established, and the DC power flow model is used to establish the linear power flow constraints of the transmission network, including:

[0041] Assume that the index of the system node is n, and the load of node n in period t is L n,t , the frequency regulation capacity and mileage requirements in time period t are Then the balance constraints under the two mechanisms are expressed as:

[0042]

[0043] Among them, formula (14) is the electric energy balance constraint, which is used to balance the power generation and consumption; formula (15) is the frequency regulation capacity balance constraint, which is used to balance the system frequency regulation capacity demand; formula (16) is the frequency regulation mileage balance constraint, which is used to balance the system frequency regulation mileage demand;

[0044] In the formula, The output of conventional thermal power units; and are the charging and discharging powers reported by energy storage j in time period t respectively; is the frequency regulation capacity declared for conventional thermal power unit i in time period t; is the frequency regulation capacity declared by energy storage j in time period t; is the mileage reported by conventional thermal power unit i in period t; is the mileage reported by energy storage j in time period t;

[0045] Using the DC power flow model, let S n,l is the power flow sensitivity coefficient of node n to line l, The power flow of line l in time period t establishes the linear power flow constraint of the transmission network as:

[0046]

[0047] Among them, formula (17) is the calculation method of line power flow under the DC power flow model, and formulas (18) and (19) are the power flow safety constraints of the transmission line;

[0048] In the formula, They are the thermal power, energy storage charging power, and energy storage discharging power of node n in the time period respectively; is the capacity of line l.

[0049] Preferably, the said combining the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network, taking the energy storage daily planning index and the minimum operation loss of conventional units as the goal, establishing a first-stage energy storage capacity configuration optimization model, and solving to obtain the optimal capacity configuration of energy storage, including:

[0050] Taking minimizing the energy storage full-cycle life planning index, the planning index under the spot mechanism, the operation loss of conventional thermal power units, the start-stop loss and the system frequency regulation loss as the optimization goal, the objective function is expressed as:

[0051]

[0052] In the formula, is the daily average planning index of energy storage j; is the planning indicator of energy storage j under the spot electricity energy mechanism; is the planning indicator of energy storage j under the frequency regulation auxiliary service mechanism; F i Ene,CG is the operating loss of conventional thermal power unit i under the spot electricity energy mechanism; F i Sta,CG is the starting loss index of conventional thermal power unit i; F i Aux,CG is the loss of conventional thermal power unit i in the frequency regulation auxiliary service mechanism;

[0053] Combining the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network, the constraints of the first-stage capacity configuration model are expressed as:

[0054]

[0055]

[0056] Equations (21) and (22) are the energy storage configuration capacity and power constraints, where W max is the upper limit of the single-node energy storage configuration capacity, ρ is the maximum proportion of energy storage power to capacity, and are the capacity and power of energy storage j respectively; Equation (23) is the system power balance constraint;

[0057] Formula (24) and (25) are the system frequency regulation demand constraints; Formula (26) and (27) are the line power flow constraints; Formula (28) to (31) are the conventional thermal power unit operation constraints, where P i min,CG , P i max,CG are the minimum and maximum output of unit i, respectively. Respectively represent the upper limit of landslide and climbing of unit i; T i on 、T i off are the minimum operating time and minimum downtime of unit i respectively;

[0058] Formula (32) to (36) are energy storage operation constraints, where d j,tis a 0-1 variable representing the charge and discharge state of energy storage j in time period t, d j,t =1 means discharge, d j,t =0 means charging, W j,t is the remaining capacity of energy storage j in time period t, η ch , η dis are the charging and discharging efficiencies of energy storage j, W j,0 , W j,Γ Represent the power of the initial and ending periods respectively;

[0059] The first-stage capacity configuration model is solved to obtain the optimal configuration capacity and power of energy storage, that is, the optimal capacity configuration result.

[0060] Preferably, the optimal capacity configuration of energy storage and the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network are combined to establish a second-stage energy storage optimization operation model with the goal of improving energy storage utilization and reducing system losses, and solve to obtain the optimal energy storage operation plan, including:

[0061] According to the forecast load and system frequency regulation requirements, the joint optimization of electric energy and auxiliary services is implemented, and the minimum total system loss and the maximum energy storage utilization are taken as the optimization goals. The objective function is expressed as:

[0062]

[0063] Combining the optimal capacity configuration results of energy storage and the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network, the second-stage energy storage optimization operation model is expressed as:

[0064]

[0065] The second-stage energy storage optimization operation model is solved to obtain the charging and discharging amount of energy storage in each period, the winning capacity of frequency regulation auxiliary service and the winning mileage of frequency regulation auxiliary service, thus obtaining the independent energy storage optimization operation results.

[0066] According to another aspect of the present invention, a capacity and operation planning system for an energy storage system under a power spot mechanism is provided, comprising:

[0067] An indicator modeling module, based on the framework of energy storage participating in the electricity spot mechanism, models the planning indicators, operating losses and utilization of energy storage under the spot mechanism; wherein the spot mechanism includes: spot electricity energy mechanism and frequency regulation auxiliary service mechanism; establishes an energy storage full life cycle planning indicator model, and converts the energy storage full life cycle planning indicators to a single day through the capital recovery coefficient, and at the same time establishes a daily total operating loss model for conventional thermal power units;

[0068] Constraint modeling module, which establishes the balance constraints under the spot power mechanism and the frequency regulation auxiliary service mechanism according to the clearing requirements of the two mechanisms, and uses the DC power flow model to establish the linear power flow constraints of the transmission network;

[0069] The optimal capacity configuration module combines the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network. It takes the energy storage daily planning indicators and the minimum operating losses of conventional units as the goals, establishes the first-stage energy storage capacity configuration optimization model, and solves the optimal capacity configuration of energy storage.

[0070] The optimal operation planning module combines the optimal capacity configuration of energy storage and the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network. With the goal of improving energy storage utilization and reducing system losses, it establishes the second-stage energy storage optimization operation model and solves the optimal energy storage operation plan.

[0071] According to a third aspect of the present invention, there is provided a computer terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, can be used to execute any one of the methods described above in the present invention, or to run the system described above in the present invention.

[0072] According to a fourth aspect of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, can be used to execute any of the methods described above in the present invention, or to run the system described above in the present invention.

[0073] Due to the adoption of the above technical solution, the present invention has at least one of the following beneficial effects compared with the prior art:

[0074] Energy storage capacity configuration optimization model based on spot mechanism: By constructing a capacity configuration optimization model, the energy storage capacity can be reasonably allocated under spot market conditions, so that discharging can be carried out when the electricity price is high and charging can be carried out when the electricity price is low, thereby maximizing profits. This solves the problem of the impact of electricity price fluctuations on the profitability of the energy storage system, and enables the energy storage system to optimize the charging and discharging strategy when the electricity price fluctuates greatly, thereby improving the economic benefits of the system.

[0075] Full life cycle planning indicator model: By establishing a full life cycle planning model, the life cycle cost of energy storage is reasonably allocated to daily operations, so that cost control and benefit evaluation can be carried out more scientifically. This solves the problem that the life cycle cost of the energy storage system is not fully considered in the existing methods. Under frequent charging and discharging conditions, the overall economy of the energy storage system can be improved, and the loss cost of energy storage operation can be effectively controlled.

[0076] Balance constraints between the electric energy mechanism and the frequency regulation ancillary service mechanism: This technology combines the balance constraints of electric energy and frequency regulation needs to enable the energy storage system to flexibly switch between the spot market and the ancillary service market, thereby achieving effective regulation of electric energy and ancillary services. This solves the problem that the energy storage system cannot take into account multiple service needs, allowing the energy storage system to not only participate in the electric energy market, but also efficiently participate in frequency regulation ancillary services, thereby increasing revenue without sacrificing response speed.

[0077] Phased optimization model (capacity configuration and operation planning): Through the phased optimization model, the energy storage system can first perform capacity configuration, and then perform optimal operation planning based on the configuration results, so that the system can gradually approach the optimal state. This solves the problem of insufficient linkage between capacity configuration and operation planning in traditional methods, improves the flexibility and adaptability of the energy storage system in different market environments, and effectively achieves a balance between revenue and system utilization. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0079] Figure 1 The present invention is a flowchart of a method for capacity and operation planning of an energy storage system under a power spot mechanism in a preferred embodiment of the present invention.

[0080] Figure 2 It is a schematic diagram of the components of the capacity and operation planning system of the energy storage system under the electricity spot mechanism in a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0081] The following is a detailed description of the embodiments of the present invention: This embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation method and a specific operation process are given. It should be pointed out that for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention.

[0082] An embodiment of the present invention provides a capacity and operation planning method for an energy storage system under an electricity spot mechanism. The purpose of the method is to consider the participation of independent energy storage in the electricity energy and ancillary service spot mechanism to achieve capacity and operation optimization of the energy storage system under the electricity spot mechanism.

[0083] Specifically, Figure 1 As shown, the capacity and operation planning method of the energy storage system under the electricity spot mechanism provided in this embodiment may include the following operations:

[0084] S1, based on the framework of energy storage participating in the electricity spot mechanism, model the planning indicators, operating losses and utilization of energy storage under the spot mechanism; the spot mechanism includes: spot electricity energy mechanism and frequency regulation auxiliary service mechanism;

[0085] S2, establish a life cycle planning indicator model for energy storage, and convert the life cycle planning indicators of energy storage to a single day through the capital recovery coefficient, and establish a daily operation total loss model for conventional thermal power units;

[0086] S3, according to the clearing requirements of the spot power mechanism and the frequency regulation auxiliary service mechanism, establish the balance constraints under the two mechanisms, and use the DC power flow model to establish the linear power flow constraints of the transmission network;

[0087] S4, combining the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network, taking the energy storage daily planning indicators and the minimum operating losses of conventional units as the goal, establish the first-stage energy storage capacity configuration optimization model, and solve the optimal capacity configuration of energy storage;

[0088] S5, combining the optimal capacity configuration of energy storage and the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network, with the goal of improving energy storage utilization and reducing system losses, establishes the second-stage energy storage optimization operation model and solves the optimal energy storage operation plan.

[0089] In some preferred implementations, the above S1, based on the framework of energy storage participating in the electricity spot mechanism, models the planning indicators, operating losses and utilization of energy storage under the spot mechanism, and may further include the following operations:

[0090] S11, analyze the model of energy storage system as an independent entity participating in the spot electricity energy mechanism and frequency regulation auxiliary service mechanism; among them:

[0091] Under the spot electricity energy mechanism, conventional thermal power units report loss coefficients, energy storage systems report operating parameters and charge-discharge loss coefficients, and users report electricity demand;

[0092] In the frequency regulation auxiliary service mechanism, independent energy storage simultaneously applies for frequency regulation capacity and mileage as well as capacity and mileage loss coefficients during the day-ahead electricity energy application stage;

[0093] Define the index of energy storage as j, the index and set of time period as t and Γ respectively, then the planning index of energy storage j under the spot electricity energy mechanism and frequency regulation auxiliary service mechanism is expressed as:

[0094]

[0095] In the formula, is the planning indicator of energy storage j under the spot electricity energy mechanism; It is the planning indicator of energy storage j under the frequency regulation auxiliary service mechanism; are the charging and discharging powers reported by energy storage j in time period t respectively; are the charging and discharging losses reported by energy storage j in time period t respectively. are the frequency regulation capacity and mileage declared by energy storage j in time period t, respectively; are the frequency regulation capacity loss and mileage loss reported by energy storage j in time period t, respectively;

[0096] S12, based on load forecasting and frequency regulation requirements, the joint optimization of electric energy and auxiliary services is cleared, and the total utilization is calculated. The index of the node where the energy storage is located is defined as s, and the utilization of energy storage j in the spot electric energy mechanism and the frequency regulation auxiliary service mechanism is expressed as:

[0097]

[0098] In the formula, is the utilization of energy storage j under the spot electricity energy mechanism; is the utilization of energy storage j under the frequency regulation auxiliary service mechanism; are the discharge and charge capacities of energy storage j in time period t respectively; are the frequency regulation capacity and mileage of energy storage j in time period t; LMP s,t is the utilization coefficient of node s in time period t; are the frequency regulation capacity loss and mileage utilization coefficient in time period t respectively.

[0099] In some preferred implementations, the above S2, establishing a life cycle planning indicator model for energy storage, and converting the life cycle planning indicators for energy storage to a single day through a capital recovery coefficient, may further include the following operations:

[0100] S21, model the full life cycle planning indicators of the energy storage system and define the total planned energy storage power as P ESS (MW), the total planned capacity is W ESS (MWh), then:

[0101]

[0102] In the formula, is the initial one-time configuration indicator of energy storage j; is the annual maintenance index of energy storage j; is the energy storage j retirement recovery index. α and β are the energy storage power planning index coefficient (MW / yuan) and capacity planning index coefficient (MWh / yuan) respectively; γ is the energy storage annual maintenance index coefficient; r is the equipment residual value rate;

[0103] S22, using the capital recovery factor δ, converts the energy storage life cycle planning indicators to daily, and obtains:

[0104]

[0105] In the formula, ν is the annual profit rate; T is the energy storage life; is the daily average planning index of energy storage j.

[0106] In some preferred implementations, the above S2, establishing a daily operation total loss model for conventional thermal power units, may further include the following operations:

[0107] S23, let the index of the conventional thermal power unit be i, and the output be In time period t, the running state is y i,t ,y i,t =1 means the unit is in operation, y i,t =0 means the unit is in shutdown state. The index and set of the number of segments allowed to be declared by the spot electricity energy mechanism are k and K respectively. The startup loss coefficient is The running and starting losses are expressed as:

[0108]

[0109]

[0110] In the formula, F i Ene,CG is the operating loss of conventional thermal power unit i under the spot electricity energy mechanism; F i Sta,CG is the starting loss index of conventional thermal power unit i; is the loss coefficient of conventional thermal power unit i in the kth output stage; is the output declared by conventional thermal power unit i in the kth output section of time period t, and the sum of the outputs of each section is

[0111] S24, the loss of conventional thermal power units participating in the frequency regulation auxiliary service mechanism is expressed as follows:

[0112]

[0113] In the formula, F i Aux,CG is the loss of conventional thermal power unit i in the frequency regulation auxiliary service mechanism; and are the frequency regulation capacity and mileage loss of conventional thermal power unit i in period t respectively; They are the frequency regulation capacity and mileage declared by conventional thermal power unit i in time period t respectively.

[0114] In some preferred implementations, the above S3, based on the clearing requirements of the spot power energy mechanism and the frequency regulation auxiliary service mechanism, establishes the balance constraints under the two mechanisms, and uses the DC power flow model to establish the linear power flow constraints of the transmission network, and may further include the following operations:

[0115] S31, let the index of the system node be n, and the load of node n in period t be L n,t , the frequency regulation capacity and mileage requirements in time period t are Then the balance constraints under the two mechanisms are expressed as:

[0116]

[0117] Among them, formula (14) is the electric energy balance constraint, which is used to balance the power generation and consumption; formula (15) is the frequency regulation capacity balance constraint, which is used to balance the system frequency regulation capacity demand; formula (16) is the frequency regulation mileage balance constraint, which is used to balance the system frequency regulation mileage demand;

[0118] In the formula, The output of conventional thermal power units; and are the charging and discharging powers reported by energy storage j in time period t respectively; is the frequency regulation capacity declared for conventional thermal power unit i in time period t; is the frequency regulation capacity declared by energy storage j in time period t; is the mileage reported by conventional thermal power unit i in period t; is the mileage reported by energy storage j in time period t;

[0119] S32, using the DC power flow model, assuming S n,l is the power flow sensitivity coefficient of node n to line l, The power flow of line l in time period t establishes the linear power flow constraint of the transmission network as:

[0120]

[0121] Among them, formula (17) is the calculation method of line power flow under the DC power flow model, and formulas (18) and (19) are the power flow safety constraints of the transmission line;

[0122] In the formula, They are the thermal power, energy storage charging power, and energy storage discharging power of node n in the time period respectively; is the capacity of line l.

[0123] In some preferred implementations, the above S4, combining the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network, takes the energy storage daily planning index and the minimum operation loss of conventional units as the goal, establishes a first-stage energy storage capacity configuration optimization model, and solves to obtain the optimal capacity configuration of energy storage, and can further include the following operations:

[0124] S41, taking minimization of the energy storage full cycle life planning index, the planning index under the spot mechanism, the operation loss of conventional thermal power units, the start-stop loss and the system frequency regulation loss as the optimization goal, the objective function is expressed as:

[0125]

[0126] In the formula, is the daily average planning index of energy storage j; is the planning indicator of energy storage j under the spot electricity energy mechanism; is the planning indicator of energy storage j under the frequency regulation auxiliary service mechanism; F i Ene,CG is the operating loss of conventional thermal power unit i under the spot electricity energy mechanism; F i Sta,CG is the starting loss index of conventional thermal power unit i; F i Aux,CG is the loss of conventional thermal power unit i in the frequency regulation auxiliary service mechanism;

[0127] S42, combining the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network, the constraints of the first stage capacity configuration model are expressed as:

[0128]

[0129]

[0130] Equations (21) and (22) are the energy storage configuration capacity and power constraints, where W max is the upper limit of the single-node energy storage configuration capacity, ρ is the maximum proportion of energy storage power to capacity, and are the capacity and power of energy storage j respectively; Equation (23) is the system power balance constraint;

[0131] Formula (24) and (25) are the system frequency regulation demand constraints; Formula (26) and (27) are the line power flow constraints; Formula (28) to (31) are the conventional thermal power unit operation constraints, where P i min,CG , P i max,CG are the minimum and maximum output of unit i, respectively. Respectively represent the upper limit of landslide and climbing of unit i; Ti on 、T i off are the minimum operating time and minimum downtime of unit i respectively;

[0132] Formula (32) to (36) are energy storage operation constraints, where d j,t is a 0-1 variable representing the charge and discharge state of energy storage j in time period t, d j,t =1 means discharge, d j,t =0 means charging, W j,t is the remaining capacity of energy storage j in time period t, η ch , η dis are the charging and discharging efficiencies of energy storage j, W j,0 , W j,Γ Represent the power of the initial and ending periods respectively;

[0133] S43, solving the capacity configuration model of the first stage to obtain the optimal configuration capacity and power of the energy storage, that is, the optimal capacity configuration result.

[0134] In some preferred implementations, the above S5, combined with the optimal capacity configuration of energy storage and the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network, aims to improve the utilization rate of energy storage and reduce system losses, establishes a second-stage energy storage optimization operation model, and solves to obtain the optimal energy storage operation plan, and may further include the following operations:

[0135] S51, based on the predicted load and system frequency regulation requirements, implement the joint optimization of electric energy and auxiliary services, and take the minimum total system loss and the maximum energy storage utilization rate as the optimization goals. The objective function is expressed as:

[0136]

[0137] S52, combined with the optimal capacity configuration results of energy storage and the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network, the second-stage energy storage optimization operation model is expressed as:

[0138]

[0139] S53, solving the second-stage energy storage optimization operation model to obtain the charging and discharging amount of energy storage in each period, the frequency regulation auxiliary service bid-winning capacity and the frequency regulation auxiliary service bid-winning mileage, and thus obtaining the independent energy storage optimization operation result.

[0140] Based on the same inventive concept, an embodiment of the present invention also provides a capacity and operation planning system for an energy storage system under a spot electricity mechanism.

[0141] Specifically, Figure 2As shown, the capacity and operation planning system of the energy storage system under the electricity spot mechanism provided in this embodiment may include:

[0142] The indicator modeling module is based on the framework of energy storage participating in the electricity spot mechanism, and models the planning indicators, operating losses and utilization of energy storage under the spot mechanism. The spot mechanism includes: spot electricity energy mechanism and frequency regulation auxiliary service mechanism. The energy storage full life cycle planning indicator model is established, and the energy storage full life cycle planning indicators are converted to a single day through the capital recovery coefficient. At the same time, a daily operating total loss model of conventional thermal power units is established.

[0143] Constraint modeling module, which establishes the balance constraints under the spot power mechanism and the frequency regulation auxiliary service mechanism according to the clearing requirements of the two mechanisms, and uses the DC power flow model to establish the linear power flow constraints of the transmission network;

[0144] The optimal capacity configuration module combines the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network. It takes the energy storage daily planning indicators and the minimum operating losses of conventional units as the goals, establishes the first-stage energy storage capacity configuration optimization model, and solves the optimal capacity configuration of energy storage.

[0145] The optimal operation planning module combines the optimal capacity configuration of energy storage and the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network. With the goal of improving energy storage utilization and reducing system losses, it establishes the second-stage energy storage optimization operation model and solves the optimal energy storage operation plan.

[0146] The working contents of each functional module of the system provided by this embodiment are further described below.

[0147] The indicator modeling module considers the framework of energy storage participating in the electricity spot mechanism and models its operating losses and evaluation indicators under the spot mechanism; establishes an energy storage full life cycle planning indicator model and converts it to a single day through the capital recovery coefficient; and establishes a daily operating total loss model for conventional thermal power units.

[0148] Furthermore, the work content of the indicator modeling module includes:

[0149] 1. Consider the framework of energy storage participating in the electricity spot mechanism and model its operating losses and evaluation indicators under the spot mechanism:

[0150] The model of energy storage system participating in the spot electricity energy mechanism and frequency regulation auxiliary service mechanism as an independent subject is analyzed. Under the electricity energy mechanism, conventional thermal power units report loss coefficients, energy storage needs to report operating parameters and charging and discharging loss coefficients, and the user side reports electricity demand; in the frequency regulation auxiliary service mechanism, independent energy storage needs to simultaneously apply for frequency regulation capacity and mileage as well as capacity and mileage loss coefficients during the day-ahead electricity energy reporting stage; the index of energy storage is defined as j, and the index and set of time periods are t and Γ respectively. Then the planning indicators of energy storage j under the electricity energy spot mechanism and auxiliary service mechanism can be expressed as:

[0151]

[0152] In the formula, is the planning index of energy storage j under the electric energy mechanism; It is the planning indicator of energy storage j under the frequency regulation auxiliary service mechanism; are the charging and discharging powers reported by energy storage j in time period t respectively; are the charging and discharging losses reported by energy storage j in time period t respectively. are the frequency regulation capacity and mileage declared by energy storage j in time period t, respectively; They are the frequency regulation capacity loss and mileage loss reported by energy storage j in time period t respectively.

[0153] The mechanism operator performs joint optimization clearing of electric energy and ancillary services according to load forecast and system frequency regulation requirements, and calculates the total utilization. The higher the utilization, the higher the utilization rate of energy storage. The index of the node where the energy storage is located is defined as s, then the utilization of energy storage in the electric energy mechanism and ancillary service mechanism of energy storage j can be expressed as:

[0154]

[0155] In the formula, is the utilization of energy storage j under the electric energy mechanism; is the utilization of energy storage j under the frequency regulation auxiliary service mechanism; are the discharge and charge capacities of energy storage j in time period t respectively; are the frequency regulation capacity and mileage of energy storage j in time period t; LMP s,t is the utilization coefficient of node s in time period t; are the frequency regulation capacity loss and mileage utilization coefficient in time period t respectively.

[0156] 2. Establish a life cycle planning indicator model for energy storage and convert it to a single day through the capital recovery coefficient; at the same time, establish a daily operation total loss model for conventional thermal power units:

[0157] First, we need to model the indicators of the entire life cycle of the energy storage system, including the initial one-time configuration indicators, maintenance indicators, and decommissioning recovery indicators. The total planned power of energy storage is defined as P ESS (MW), the total planned capacity is W ESS (MWh), the relevant planning indicators are as follows:

[0158]

[0159] In the formula, is the initial one-time configuration indicator of energy storage j; is the annual maintenance index of energy storage j; is the energy storage j recovery index. α and β are the energy storage power planning index coefficient (MW / yuan) and capacity planning index coefficient (MWh / yuan), respectively; γ is the energy storage annual maintenance index coefficient; r is the equipment residual value rate.

[0160] For the sake of convenience, the present invention uses the capital recovery coefficient δ to convert the energy storage planning index to daily:

[0161]

[0162] In the formula, ν is the annual profit rate; T is the energy storage life; is the daily average planning index of energy storage j.

[0163] The operating loss of conventional thermal power units is in the form of a quadratic curve. The spot mechanism usually allows them to declare the loss value in segments and in increasing linearity according to the output segment. The index of the conventional unit is set as i. There are usually two important parameters, namely, the output and the running state y in period t i,t ,y i,t =1 means the unit is in operation, y i,t =0 means the unit is in shutdown state. The index and set of the number of sections allowed to be declared by the electric energy mechanism are k and K respectively. The startup loss coefficient is The running and starting losses can be expressed as:

[0164]

[0165] In the formula, F i Ene,CG is the operating loss of unit i under the electricity spot mechanism; F i Sta,CG is the starting loss index of unit i; is the loss coefficient of unit i in the kth output section; The output declared by unit i in the kth output section in time period t, the sum of the outputs of each section is

[0166] In addition, the losses of conventional units participating in the frequency regulation mechanism can be as follows:

[0167]

[0168] In the formula, F i Aux,CG is the loss of unit i in the frequency regulation auxiliary service mechanism; and are the frequency regulation capacity and mileage loss of unit i in period t respectively; They are the frequency regulation capacity and mileage declared by unit i in time period t respectively.

[0169] The constraint modeling module establishes the balance constraints of the two mechanisms according to the clearing requirements of the electric energy spot mechanism and the frequency regulation auxiliary service mechanism; and uses the DC power flow model to establish the linear power flow constraints of the transmission network.

[0170] Furthermore, the working content of the constraint modeling module includes:

[0171] Assume that the index of the system node is n, and the load of node n in period t is L n,t , the frequency regulation capacity and mileage requirements in time period t are Then the electric energy balance constraint and the frequency regulation auxiliary service balance constraint can be expressed as:

[0172]

[0173] Formula (14) is the power balance constraint between power generation and consumption, formula (15) guarantees the system frequency regulation capacity requirement, and formula (16) guarantees the system frequency regulation mileage requirement.

[0174] For independent energy storage at the system level, the power flow safety of the transmission network is of great significance to system operation and energy storage planning. The present invention uses the DC power flow model to set S n,l is the power flow sensitivity coefficient of node n to line l, The power flow of line l in time period t is:

[0175]

[0176] Formula (17) is the calculation method of line power flow under the DC power flow model, and formulas (18)-(19) are the power flow safety constraints of the transmission line.

[0177] The optimal capacity configuration module, combined with the above constraints, takes the energy storage daily planning indicators and the minimum operating losses of conventional units as the goal, establishes the first-stage energy storage capacity configuration optimization model, and solves the optimal capacity configuration of energy storage.

[0178] Furthermore, the working content of the optimal capacity configuration module includes:

[0179] The first stage of the present invention is the capacity configuration optimization of independent energy storage. The objective function is to minimize the energy storage full cycle life planning index, the operating index under the spot mechanism, the conventional unit operating loss, the start-stop loss and the system frequency regulation loss. The objective function can be expressed as:

[0180]

[0181] Combining the electric energy balance constraint, frequency regulation capacity balance constraint, frequency regulation mileage balance constraint and transmission network linear power flow constraint, the constraints of the first stage capacity configuration model are expressed as follows:

[0182]

[0183]

[0184] Formulas (21)-(22) represent the energy storage configuration capacity and power constraints, where W max is the upper limit of the single-node energy storage configuration capacity, ρ is the maximum proportion of energy storage power to capacity, and are the capacity and power configured for energy storage j respectively; formula (23) is the system power balance constraint.

[0185] Formulas (24)-(25) are the system frequency regulation demand constraints; Formulas (26)-(27) are the line power flow constraints; Formulas (28)-(31) are the conventional thermal power unit operation constraints. i min,CG , P i max,CG are the minimum and maximum output of unit i, respectively. Respectively represent the upper limit of landslide and climbing of unit i; T i on 、T i off are the minimum operating time and minimum downtime of unit i respectively.

[0186] Formulas (32)-(36) are energy storage operation constraints, where d j,t is a 0-1 variable representing the charge and discharge state of energy storage j in time period t, d j,t =1 means discharge, d j,t =0 means charging, W j,t is the remaining capacity of energy storage j in time period t, η ch , η dis are the charging and discharging efficiencies of energy storage j, W j,0 , W j,Γ Represents the power at the initial and end time periods respectively.

[0187] By solving the first-stage capacity configuration model, we can obtain the optimal configuration capacity and power of energy storage, that is, the capacity planning result.

[0188] The optimal operation planning module combines the optimal configuration of energy storage with the power balance constraints, ancillary service balance constraints and power flow constraints, and establishes the second-stage energy storage optimization operation model with the goal of improving energy storage utilization and reducing system losses, and solves the optimal energy storage operation strategy.

[0189] Furthermore, the work content of the optimal operation planning module includes:

[0190] The second stage model of the present invention is an independent energy storage operation optimization model. From the perspective of the operating organization, according to the predicted load and system frequency regulation requirements, the electric energy and auxiliary services are jointly optimized and cleared. The objective function is to minimize the total system loss and maximize the energy storage utilization rate. The objective function can be expressed as:

[0191]

[0192] It is necessary to combine the energy storage capacity configuration results, electric energy balance constraints, frequency regulation capacity balance constraints, frequency regulation mileage balance constraints, and transmission network linear power flow constraints, so the constraints can be expressed as:

[0193]

[0194]

[0195] The model is established as a mixed integer linear programming model, which can be efficiently solved by a solver to obtain the charging and discharging amount of energy storage in each time period, the winning capacity of frequency regulation auxiliary service, and the winning mileage of frequency regulation auxiliary service. At this point, the optimized operation results of independent energy storage are obtained.

[0196] It should be noted that the steps in the method provided by the present invention can be implemented by using the corresponding components in the system, and those skilled in the art can refer to the technical solution of the system to implement the step flow of the method, and can also refer to the technical solution of the method to implement the composition of the system, that is, the embodiments in the system and the embodiments in the method can be understood as preferred examples of each other, which will not be elaborated here.

[0197] An embodiment of the present invention further provides a computer terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the processor can be used to execute any method of the above-mentioned embodiments of the present invention, or to run any system of the above-mentioned embodiments of the present invention.

[0198] Optionally, the memory is used to store programs; the memory may include volatile memory (English: volatile memory), such as random-access memory (English: random-access memory, abbreviated: RAM), such as static random-access memory (English: static random-access memory, abbreviated: SRAM), double data rate synchronous dynamic random access memory (English: Double Data Rate Synchronous Dynamic Random Access Memory, abbreviated: DDR SDRAM), etc.; the memory may also include non-volatile memory (English: non-volatile memory), such as flash memory (English: flash memory). The memory is used to store computer programs (such as applications, functional modules, etc. that implement the above method), computer instructions, etc., and the above computer programs, computer instructions, etc. can be partitioned and stored in one or more memories. And the above computer programs, computer instructions, data, etc. can be called by the processor.

[0199] The above-mentioned computer programs, computer instructions, etc. may be stored in one or more memories in partitions, and the above-mentioned computer programs, computer instructions, data, etc. may be called by a processor.

[0200] The processor is used to execute the computer program stored in the memory to implement the various steps of the method or various modules of the system involved in the above embodiments. For details, please refer to the relevant descriptions in the above method and system embodiments.

[0201] The processor and the memory may be independent structures or integrated structures. When the processor and the memory are independent structures, the memory and the processor may be coupled and connected via a bus.

[0202] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, it can be used to execute any method of the above embodiments of the present invention, or to run any system of the above embodiments of the present invention.

[0203] Among them, computer-readable media include computer storage media and communication media, wherein the communication media include any media that facilitates the transmission of computer programs from one place to another. The storage medium can be any available medium that can be accessed by a general or special-purpose computer. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be an integral part of the processor. The processor and the storage medium can be located in an ASIC. In addition, the ASIC can be located in a user device. Of course, the processor and the storage medium can also be present in a communication device as discrete components.

[0204] The capacity and operation planning method and system of the energy storage system under the electricity spot mechanism provided in the above-mentioned embodiment of the present invention maximize the economic benefits of the energy storage system, improve the stability of the power system, and reasonably allocate the cost of the whole life cycle by optimizing the capacity configuration and operation strategy of the energy storage system in the electricity spot market, thereby improving the market adaptability of the energy storage system and the economy of long-term operation.

[0205] All matters not covered in the above embodiments of the present invention are well known in the art.

[0206] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art may make various modifications or variations within the scope of the claims, which do not affect the essence of the present invention.

Claims

1. A capacity and operation planning method for an energy storage system under a power spot mechanism, characterized in that: include: Based on the framework of energy storage participating in the electricity spot mechanism, the planning indicators, operating losses and utilization of energy storage under the spot mechanism are modeled; wherein the spot mechanism includes: spot electricity energy mechanism and frequency regulation auxiliary service mechanism; Establish a life cycle planning indicator model for energy storage, and convert the life cycle planning indicators of energy storage to a single day through the capital recovery coefficient. At the same time, establish a daily operation total loss model for conventional thermal power units; According to the clearing requirements of the spot power mechanism and the frequency regulation auxiliary service mechanism, the balance constraints under the two mechanisms are established, and the DC power flow model is used to establish the linear power flow constraints of the transmission network; Combining the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network, with the goal of minimizing the daily planning indicators of energy storage and the operating losses of conventional units, an optimization model for energy storage capacity configuration in the first stage is established to solve the optimal capacity configuration of energy storage. Combining the optimal capacity configuration of energy storage and the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network, with the goal of improving energy storage utilization and reducing system losses, a second-stage energy storage optimization operation model is established to solve the optimal operation plan of energy storage.

2. The capacity and operation planning method of the energy storage system under the electricity spot mechanism according to claim 1 is characterized in that: The framework based on energy storage participating in the electricity spot mechanism models the planning indicators, operating losses and utilization of energy storage under the spot mechanism, including: The model of energy storage system participating in spot electricity energy mechanism and frequency regulation auxiliary service mechanism as an independent entity is analyzed; among which: Under the spot electricity energy mechanism, conventional thermal power units report loss coefficients, energy storage systems report operating parameters and charge-discharge loss coefficients, and users report electricity demand; In the frequency regulation auxiliary service mechanism, independent energy storage simultaneously applies for frequency regulation capacity and mileage as well as capacity and mileage loss coefficients during the day-ahead electricity energy application stage; Define the index of energy storage as j, the index and set of time period as t and Γ respectively, then the planning index of energy storage j under the spot electricity energy mechanism and frequency regulation auxiliary service mechanism is expressed as: In the formula, is the planning indicator of energy storage j under the spot electricity energy mechanism; It is the planning indicator of energy storage j under the frequency regulation auxiliary service mechanism; are the charging and discharging powers reported by energy storage j in time period t respectively; are the charging and discharging losses reported by energy storage j in time period t; are the frequency regulation capacity and mileage declared by energy storage j in time period t, respectively; are the frequency regulation capacity loss and mileage loss reported by energy storage j in time period t, respectively; According to the load forecast and frequency regulation requirements, the joint optimization of electric energy and auxiliary services is performed, and the total utilization is calculated. The index of the node where the energy storage is located is defined as s. Then the utilization of energy storage j in the spot electric energy mechanism and the frequency regulation auxiliary service mechanism is expressed as: In the formula, is the utilization of energy storage j under the spot electricity energy mechanism; is the utilization of energy storage j under the frequency regulation auxiliary service mechanism; are the discharge and charge capacities of energy storage j in time period t respectively; are the frequency regulation capacity and mileage of energy storage j in time period t; LMP s,t is the utilization coefficient of node s in time period t; are the frequency regulation capacity loss and mileage utilization coefficient in time period t respectively.

3. The capacity and operation planning method of the energy storage system under the electricity spot mechanism according to claim 1 is characterized in that: Establish a life cycle planning indicator model for energy storage, and convert the life cycle planning indicators of energy storage to a single day through the capital recovery coefficient, including: Model the planning indicators of the energy storage system throughout its life cycle and define the total planned power of energy storage as P ESS , the total planned capacity is W ESS ,but: In the formula, is the initial one-time configuration indicator of energy storage j; is the annual maintenance index of energy storage j; is the energy storage j retirement recovery index; α and β are the energy storage power planning index coefficient and capacity planning index coefficient respectively; γ is the energy storage annual maintenance index coefficient; r is the equipment residual value rate; Using the capital recovery factor δ, the full life cycle planning indicators of energy storage are converted to daily, and the result is: In the formula, ν is the annual profit rate; T is the energy storage life; is the daily average planning index of energy storage j.

4. The capacity and operation planning method of the energy storage system under the electricity spot mechanism according to claim 1 is characterized in that: The daily operation total loss model of conventional thermal power units is established, including Assume that the index of the conventional thermal power unit is i and the output is In time period t, the running state is y i,t ,y i,t =1 means the unit is in operation, y i,t =0 means the unit is in shutdown state. The index and set of the number of segments allowed to be declared by the spot electricity energy mechanism are k and K respectively. The startup loss coefficient is The running and starting losses are expressed as: In the formula, is the operating loss of conventional thermal power unit i under the spot electricity energy mechanism; is the starting loss index of conventional thermal power unit i; is the loss coefficient of conventional thermal power unit i in the kth output stage; is the output declared by conventional thermal power unit i in the kth output section of time period t, and the sum of the outputs of each section is The loss of conventional thermal power units participating in the frequency regulation auxiliary service mechanism is expressed as follows: In the formula, is the loss of conventional thermal power unit i in the frequency regulation auxiliary service mechanism; and are the frequency regulation capacity and mileage loss of conventional thermal power unit i in period t respectively; They are the frequency regulation capacity and mileage declared by conventional thermal power unit i in time period t respectively.

5. The capacity and operation planning method of the energy storage system under the electricity spot mechanism according to claim 1 is characterized in that: According to the clearing requirements of the spot power energy mechanism and the frequency regulation auxiliary service mechanism, the balance constraints under the two mechanisms are established, and the DC power flow model is used to establish the linear power flow constraints of the transmission network, including: Assume that the index of the system node is n, and the load of node n in period t is L n,t , the frequency regulation capacity and mileage requirements in time period t are Then the balance constraints under the two mechanisms are expressed as: Among them, formula (14) is the electric energy balance constraint, which is used to balance the power generation and consumption; formula (15) is the frequency regulation capacity balance constraint, which is used to balance the system frequency regulation capacity demand; formula (16) is the frequency regulation mileage balance constraint, which is used to balance the system frequency regulation mileage demand; In the formula, The output of conventional thermal power units; and are the charging and discharging powers reported by energy storage j in time period t respectively; is the frequency regulation capacity declared for conventional thermal power unit i in time period t; is the frequency regulation capacity declared by energy storage j in time period t; is the mileage reported by conventional thermal power unit i in period t; is the mileage reported by energy storage j in time period t; Using the DC power flow model, let S n,l is the power flow sensitivity coefficient of node n to line l, The power flow of line l in time period t establishes the linear power flow constraint of the transmission network as: Among them, formula (17) is the calculation method of line power flow under the DC power flow model, and formulas (18) and (19) are the power flow safety constraints of the transmission line; In the formula, They are the thermal power, energy storage charging power, and energy storage discharging power of node n in the time period respectively; is the capacity of line l.

6. The capacity and operation planning method of the energy storage system under the electricity spot mechanism according to claim 1 is characterized in that: The above-mentioned balance constraints under the two mechanisms and the linear power flow constraints of the transmission network are combined, and the energy storage daily planning index and the minimum operation loss of conventional units are taken as the goal to establish the first-stage energy storage capacity configuration optimization model, and the optimal capacity configuration of energy storage is solved, including: Taking minimizing the energy storage full-cycle life planning index, the planning index under the spot mechanism, the operation loss of conventional thermal power units, the start-stop loss and the system frequency regulation loss as the optimization goal, the objective function is expressed as: In the formula, is the daily average planning index of energy storage j; is the planning indicator of energy storage j under the spot electricity energy mechanism; It is the planning indicator of energy storage j under the frequency regulation auxiliary service mechanism; is the operating loss of conventional thermal power unit i under the spot electricity energy mechanism; is the starting loss index of conventional thermal power unit i; is the loss of conventional thermal power unit i in the frequency regulation auxiliary service mechanism; Combining the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network, the constraints of the first-stage capacity configuration model are expressed as: Equations (21) and (22) are the energy storage configuration capacity and power constraints, where W max is the upper limit of the single-node energy storage configuration capacity, ρ is the maximum proportion of energy storage power to capacity, and are the capacity and power of energy storage j respectively; Equation (23) is the system power balance constraint; Formula (24) and (25) are the system frequency regulation demand constraints; Formula (26) and (27) are the line power flow constraints; Formula (28) to (31) are the conventional thermal power unit operation constraints, where: are the minimum and maximum output of unit i, respectively. They represent the upper limits of landslide and climbing of unit i respectively; are the minimum operating time and minimum downtime of unit i respectively; Equations (32) to (36) are energy storage operation constraints, where d j,t is a 0-1 variable representing the charge and discharge state of energy storage j in time period t, d j,t =1 means discharge, d j,t =0 means charging, W j,t is the remaining capacity of energy storage j in time period t, η ch , η dis are the charging and discharging efficiencies of energy storage j, W j,0 , W j,Γ Represent the power of the initial and ending periods respectively; The first-stage capacity configuration model is solved to obtain the optimal configuration capacity and power of energy storage, that is, the optimal capacity configuration result.

7. The capacity and operation planning method of the energy storage system under the electricity spot mechanism according to claim 1 is characterized in that: The optimal capacity configuration of energy storage and the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network are combined to establish a second-stage energy storage optimization operation model with the goal of improving energy storage utilization and reducing system losses, and solve the optimal energy storage operation plan, including: According to the forecast load and system frequency regulation requirements, the joint optimization of electric energy and auxiliary services is implemented, and the minimum total system loss and the maximum energy storage utilization are taken as the optimization goals. The objective function is expressed as: Combining the optimal capacity configuration results of energy storage and the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network, the second-stage energy storage optimization operation model is expressed as: The second-stage energy storage optimization operation model is solved to obtain the charging and discharging amount of energy storage in each period, the winning capacity of frequency regulation auxiliary service and the winning mileage of frequency regulation auxiliary service, thus obtaining the independent energy storage optimization operation results.

8. A capacity and operation planning system for energy storage systems under the electricity spot mechanism, characterized in that: include: An indicator modeling module, based on the framework of energy storage participating in the electricity spot mechanism, models the planning indicators, operating losses and utilization of energy storage under the spot mechanism; wherein the spot mechanism includes: spot electricity energy mechanism and frequency regulation auxiliary service mechanism; establishes an energy storage full life cycle planning indicator model, and converts the energy storage full life cycle planning indicators to a single day through the capital recovery coefficient, and at the same time establishes a daily total operating loss model for conventional thermal power units; Constraint modeling module, which establishes the balance constraints under the spot power mechanism and the frequency regulation auxiliary service mechanism according to the clearing requirements of the two mechanisms, and uses the DC power flow model to establish the linear power flow constraints of the transmission network; The optimal capacity configuration module combines the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network. It takes the energy storage daily planning indicators and the minimum operating losses of conventional units as the goals, establishes the first-stage energy storage capacity configuration optimization model, and solves the optimal capacity configuration of energy storage. The optimal operation planning module combines the optimal capacity configuration of energy storage and the balance constraints under the two mechanisms and the linear power flow constraints of the transmission network. With the goal of improving energy storage utilization and reducing system losses, it establishes the second-stage energy storage optimization operation model and solves the optimal energy storage operation plan.

9. A computer terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, it can be used to perform the method described in any one of claims 1 to 7, or to run the system described in claim 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it can be used to perform the method described in any one of claims 1 to 7, or to run the system described in claim 8.

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