CN116632883A - Network side energy storage optimal capacity verification method and system - Google Patents

Network side energy storage optimal capacity verification method and system Download PDF

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CN116632883A
CN116632883A CN202310434266.6A CN202310434266A CN116632883A CN 116632883 A CN116632883 A CN 116632883A CN 202310434266 A CN202310434266 A CN 202310434266A CN 116632883 A CN116632883 A CN 116632883A
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energy storage
power
capacity
constraint
parameters
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张柏林
邵冲
魏博
刘文飞
刘克权
杨勇
郝如海
徐宏雷
牛浩明
张旭军
陈仕彬
祁莹
谢映洲
牛甄
赵进国
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STATE GRID GASU ELECTRIC POWER RESEARCH INSTITUTE
State Grid Gansu Electric Power Co Ltd
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STATE GRID GASU ELECTRIC POWER RESEARCH INSTITUTE
State Grid Gansu Electric Power Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06Q50/06—Energy or water supply
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    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy

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Abstract

The application discloses a network side energy storage optimal capacity verification method and a system, which relate to the field of power system network side planning, wherein the method comprises the following steps: acquiring parameters of each thermal power unit, parameters of each wind power unit, parameters of energy storage equipment, parameters of power users and network topology data of a power system; determining the optimal admittance capacity of the energy storage equipment according to the energy storage capacity verification model; the energy storage capacity verification model comprises constraint conditions and an objective function; the target function is a function established by taking the higher rated power and the larger rated capacity of the energy storage equipment as targets; the optimal admittance capacity of the energy storage device is obtained according to the rated power and rated capacity of the energy storage device. According to the application, constraint condition modeling is carried out on the output of each unit in the system and the charge and discharge conditions of the energy storage equipment, and the configuration capacity of the energy storage equipment in the system is determined by adopting the objective function with the optimal admittance capacity scale, so that accurate guidance is provided for the selection of the energy storage capacity of the power system network side.

Description

Network side energy storage optimal capacity verification method and system
Technical Field
The application relates to the field of power system network side planning, in particular to a network side energy storage optimal capacity verification method and system.
Background
At present, the novel energy storage development at the power grid side is mainly based on a leasing mode, is uniformly managed after the energy storage is built by a power grid company, and plays a role in leasing or checking the form of power transmission and distribution price for other main bodies of the power system. However, general policy suggests that an energy storage power station with 10% -20% of capacity is equipped at a new energy station, but capacity accounting of grid-side energy storage in a system is not clear, and an effective planning guiding model is lacking, so that development of the current grid-side energy storage project in China is blocked. Therefore, the configuration capacity of the power grid side energy storage in the high-proportion new energy power system is calculated, and the method has important significance for accurate configuration of the grid side flexible resources.
Disclosure of Invention
The application aims to provide a network side energy storage optimal capacity verification method and system, which can accurately calculate the optimal configuration capacity of the power system of the power network side energy storage.
In order to achieve the above object, the present application provides the following solutions:
the application provides a network side energy storage optimal capacity verification method, which comprises the following steps:
step 1: acquiring parameters of each thermal power unit, parameters of each wind power unit, parameters of energy storage equipment, parameters of power users and network topology data of a power system;
step 2: determining the optimal admittance capacity of the energy storage equipment according to the energy storage capacity verification model; the energy storage capacity verification model comprises constraint conditions and an objective function; the constraint conditions are set according to the thermal power generating unit parameters, the wind power generating unit parameters, the energy storage equipment parameters, the power user parameters and the network topology data; the objective function is a function established by taking the higher rated power and the larger rated capacity of the energy storage equipment as targets; and the optimal admittance capacity of the energy storage equipment is obtained according to the rated power and rated capacity of the energy storage equipment.
Optionally, the constraint conditions comprise climbing constraint of the thermal power unit, minimum start-stop time constraint of the thermal power unit, output constraint of the thermal power unit, line tide constraint, system power balance constraint, energy storage power and capacity constraint, energy storage charge-discharge start-stop constraint, energy storage charge-discharge constraint and energy storage electric quantity constraint.
Optionally, the objective function is specifically as follows:
wherein C is ib For an optimal admission capacity of the energy storage device,and->Rated power and rated capacity of the energy storage device k; i inv,P And I inv,E The unit power parameter and the unit capacity parameter of the energy storage device k are respectively.
Optionally, the energy storage electric quantity constraint is specifically as follows:
wherein SOC is t,min ≤SOC t ≤SOC t,max ，SOC t Charge amount of energy storage system at t moment and SOC t-1 For the amount of charge of the energy storage system at time t-1,respectively the charge and discharge efficiency and P of the energy storage system at the moment t t cha ,P t dis Respectively the charge power and the discharge power of the energy storage system at the moment t and the SOC t,min The lower limit of the charge quantity of the energy storage system at the moment t is SOC t,max The upper limit of the charge quantity of the energy storage system at the time t.
Optionally, the energy storage power and capacity constraints include an energy storage power constraint and an energy storage capacity constraint;
the stored energy power constraint is as follows:
the energy storage capacity constraint is as follows:
wherein P is load Is the total load of the power system; t is t max And t min As an upper and lower limit for the sustainable discharge time of the energy storage device,and->The rated power and rated capacity of the energy storage device k are respectively, and delta is the energy storage scale of the system which is not higher than the percentage of the total load in the system.
Optionally, the power balance constraint of the power system is specifically as follows:
wherein Ω G Is a collection of thermal power generating units; omega w is a set of wind turbines; omega shape E A collection of energy storage devices; omega shape L In order to use a collection of electrical loads,respectively charging and discharging power of the energy storage device k at the time t; />The output of the thermal power unit i at the time t is obtained; />The output of the wind turbine generator set w at the time t is obtained; />Is the demand of the power system load j at the time t.
Optionally, the minimum start-stop time constraint of the thermal power generating unit is specifically as follows:
wherein T is i on ,T i off The minimum continuous start-up time and the minimum continuous stop time of the ith thermal power generating unit are respectively; u (u) i,t The power-on state at the moment t of the ith thermal power generating unit is the power-on state, and the power-on time u is the power-on time u i,t =1, u at shutdown i,t ＝0。
Optionally, the thermal power generating unit output constraint is specifically as follows:
u i,t P i,min ≤P i,t ≤u i,t P i,max ；
wherein u is i,t The method is characterized in that the method is an on-off state of an ith thermal power generating unit at a time t; p (P) i,max ,P i,min The maximum output and the minimum output of the ith thermal power generating unit are respectively.
Optionally, the climbing constraint of the thermal power generating unit is specifically as follows:
wherein R is i U ,R i D Respectively the upward and downward climbing capacity of the ith thermal power generating unit,for the output of the thermal power unit i at the time t, < >>The output of the ith thermal power generating unit at the time t-1 is obtained.
The application also provides a network side energy storage optimal capacity verification system, which comprises:
the parameter acquisition module is used for acquiring parameters of each thermal power unit, parameters of each wind power unit, parameters of energy storage equipment, parameters of power users and network topology data of the power system;
the capacity calculation module is used for determining the optimal admittance capacity of the energy storage equipment according to the energy storage capacity verification model; the energy storage capacity verification model comprises constraint conditions and an objective function; the constraint conditions are set according to the thermal power generating unit parameters, the wind power generating unit parameters, the energy storage equipment parameters, the power user parameters and the network topology data; the objective function is a function established by taking the higher rated power and the larger rated capacity of the energy storage equipment as targets; and the optimal admittance capacity of the energy storage equipment is obtained according to the rated power and rated capacity of the energy storage equipment.
According to the specific embodiment provided by the application, the application discloses the following technical effects:
the application provides a network side energy storage optimal capacity verification method and a system, wherein the method comprises the following steps: acquiring parameters of each thermal power unit, parameters of each wind power unit, parameters of energy storage equipment, parameters of power users and network topology data of a power system; determining the optimal admittance capacity of the energy storage equipment according to the energy storage capacity verification model; the energy storage capacity verification model comprises constraint conditions and an objective function; the constraint conditions are set according to parameters of each thermal power generating unit, parameters of each wind power generating unit, parameters of energy storage equipment, parameters of power users and network topology data; the objective function is a function established with the aim of increasing the rated power and the rated capacity of the energy storage device; the optimal admittance capacity of the energy storage device is obtained according to the rated power and rated capacity of the energy storage device. According to the application, constraint condition modeling is carried out on the output of each unit and the charge and discharge conditions of the energy storage device, and the configuration capacity of the energy storage device in the system is determined by adopting the objective function of the optimal admittance capacity scale, so that accurate guidance is provided for the selection of the energy storage capacity of the power system.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of a method for verifying the optimal capacity of network-side energy storage provided by an embodiment of the application;
FIG. 2 is a graph of a single daily load provided by an embodiment of the present application;
FIG. 3 is a graph of a 24h projected graph of wind power provided by an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The application aims to provide a network side energy storage optimal capacity verification method and system, which can accurately calculate the optimal admittance capacity of the power system of the power network side energy storage.
In order that the above-recited objects, features and advantages of the present application will become more readily apparent, a more particular description of the application will be rendered by reference to the appended drawings and appended detailed description.
As shown in fig. 1, the present application provides a network side energy storage optimal capacity verification method, which includes:
step 1: and acquiring parameters of each thermal power unit, parameters of each wind power unit, parameters of energy storage equipment, parameters of power users and network topology data of the power system.
Step 2: determining the optimal admittance capacity of the energy storage equipment according to the energy storage capacity verification model; the energy storage capacity verification model comprises constraint conditions and an objective function; the constraint conditions are set according to the thermal power generating unit parameters, the wind power generating unit parameters, the energy storage equipment parameters, the power user parameters and the network topology data; the objective function is a function established by taking the higher rated power and the larger rated capacity of the energy storage equipment as targets; and the optimal admittance capacity of the energy storage equipment is obtained according to the rated power and rated capacity of the energy storage equipment.
Wherein,, the parameters of each thermal power unit of the power system include nodes where the thermal power units are located, output ranges of the thermal power units, power generation functions, climbing ranges and start-stop parameters; the parameters of each wind turbine generator are expected wind power output curves in a typical day; the energy storage equipment parameters comprise energy storage charge and discharge efficiency and charge and discharge ramp rate; the network topology data comprises system node parameters, line parameters and transmission line tide parameters; the power consumer parameter is a load curve for each time period within a typical day.
Before determining the optimal admittance capacity scale of the energy storage device, determining a unit power parameter, a unit capacity parameter and an expected operation life of the energy storage device, wherein the parameters of the energy storage device are specifically shown in table 1:
TABLE 1 energy storage related parameters
In some embodiments, the objective function established according to the target of the high rated power of the energy storage device and the maximum rated capacity of the energy storage device may be specifically as follows:
wherein C is ib For an optimal admission capacity size of the energy storage device,and->Rated power and rated capacity of the energy storage device k; i inv,P And I inv,E The unit power parameter and the unit capacity parameter of the energy storage device k are respectively.
In some embodiments, the constraint conditions include a thermal power unit climbing constraint, a thermal power unit minimum on-off time constraint, a system power balance constraint, a thermal power unit output constraint, a line power flow constraint, an energy storage power and capacity constraint, an energy storage charge-discharge start-off constraint, an energy storage charge-discharge constraint and an energy storage electric quantity constraint, and each constraint condition may specifically be as follows:
specifically, the climbing constraint of the thermal power generating unit is as follows:
in the method, in the process of the application,the climbing capacity of the i thermal power generating unit upwards and downwards is respectively +.>For the output of the thermal power unit i at the time t, < >>The output of the ith thermal power generating unit at the time t-1 is obtained.
Specifically, the minimum start-stop time constraint of the thermal power generating unit is as follows:
wherein T is i on ,T i off The minimum continuous start-up time and the minimum continuous stop time of the ith thermal power generating unit are respectively; u (u) i,t The power-on state of the ith thermal power generating unit is the power-on state of the ith thermal power generating unit, and u is the power-on state of the ith thermal power generating unit when the power generating unit is started i,t =1, u at shutdown i,t ＝0。
Specifically, the thermal power generating unit output constraint is as follows:
u i,t P i,min ≤P i,t ≤u i,t P i,max
P i,min ≤P i,t +r i,t ≤P i,max
wherein u is i,t The method is characterized in that the method is an on-off state of an ith thermal power generating unit at a time t; p (P) i,max ,P i,min The maximum output and the minimum output of the ith thermal power generating unit are respectively.
Specifically, the line flow constraints are as follows:
in omega G Is a collection of thermal power generating units; omega w is a set of wind turbines; omega shape E A collection of energy storage devices; omega shape L Is a collection of electrical loads; delta i,l ,δ w,l ,δ k,l ,δ j,l The power flow distribution factors of the ith thermal power unit, the w wind power unit, the energy storage device k and the load j to the line l are respectively; f (F) l Maximum transmission power allowed for line l.
Specifically, the system power balancing constraints are as follows:
in omega G Is a collection of thermal power generating units; omega w is a set of wind turbines; omega shape E A collection of energy storage devices; omega shape L In order to use a collection of electrical loads,respectively charging and discharging power of the energy storage device k at the time t; />The output of the thermal power unit i at the time t is obtained; />The output of the wind turbine generator set w at the time t is obtained; />Is the demand of the power system load j at the time t. Wherein, the power system load can be obtained from a single-day power load diagram shown in fig. 2; the wind turbine generator output can be obtained from a wind power 24h predicted graph shown in fig. 3.
Specifically, the energy storage power and capacity constraints are as follows:
wherein P is load Is the total load of the system in the area; t is t max And t min Establishing upper and lower limits of energy storage sustainable discharge time;and->Rated power and rated capacity of the energy storage k; δP is the percentage of the total load in the system that the energy storage scale of the system is not higher.
Specifically, the energy storage charge and discharge flag bit constraint (energy storage charge and discharge start-stop constraint) is as follows:
in the method, in the process of the application,the charge and discharge state of the energy storage device k at the time t is marked as +.>To 0 indicates stopping charging and stopping discharging, respectively, when +.>1 indicates the start of charge and the start of discharge, respectively.
Specifically, the energy storage power and capacity constraints include energy storage power constraints as follows:
the stored energy power constraint is as follows:the energy storage capacity constraint is as follows:
wherein P is load Is the total load of the power system; t is t max And t min As an upper and lower limit for the sustainable discharge time of the energy storage device,and->The rated power and rated capacity of the energy storage device k are respectively, and δP is the percentage of the energy storage scale of the system which is not higher than the total load in the system.
Specifically, the stored energy power constraint is as follows:
wherein SOC is t,min ≤SOC t ≤SOC t,max ，SOC t Charge amount of energy storage system at t moment and SOC t-1 For the amount of charge of the energy storage system at time t-1,respectively the charge and discharge efficiency and P of the energy storage system at the moment t t cha ,P t dis Respectively the charge power and the discharge power of the energy storage system at the moment t and the SOC t,min The lower limit of the charge quantity of the energy storage system at the moment t is SOC t,max The upper limit of the charge quantity of the energy storage system at the time t.
In some embodiments, the energy storage capacity verification model can be solved by calling CPLEX through YALMP to obtain the optimal admission capacity scale, wherein the constraint comprising the secondary decision variable is converted by a large M method.
The objective function in the energy storage device scheduling decision model can be flexibly selected and customized according to the actual scheduling cost, constraint conditions can be added and subtracted according to the actual requirements, and the expandability is high.
In some embodiments, the present application may also determine the net-side energy storage optimal capacity based on exotic theory. Where exotic is an economic term, exotic refers to when certain benefits of an action are given or certain costs are imposed on persons not taking part in this decision. Externality can be divided into positive externality (positive externality economic effect) and negative externality (negative externality economic effect). Positive externality refers to the phenomenon that the production or consumption of a subject is beneficial to others without charging the latter; negative externality refers to the phenomenon that the production or consumption of a subject compromises the benefit of others while the former does not compensate for the latter. In the electricity market environment, the charging and discharging behavior of the grid-side energy storage may affect the market trade results, thereby affecting other bodies of the market, and this effect is called the externality of the energy storage. Based on the externality theory, excess profits generated by energy storage for other participants in the market are generally counted as positive externality values of the energy storage, and profit losses generated by other participants in the market are counted as negative externality values of the energy storage. Therefore, the real value of the net-side energy storage to other market members can be analyzed and calculated by relying on the external theory, and the method has theoretical guidance effect on the process of researching the energy storage investment planning and the cost recovery.
The application also provides a network side energy storage optimal capacity verification system, which comprises:
the parameter acquisition module is used for acquiring parameters of each thermal power unit, parameters of each wind power unit, parameters of energy storage equipment, parameters of power users and network topology data of the power system.
The capacity calculation module is used for determining the optimal admittance capacity of the energy storage equipment according to the energy storage capacity verification model; the energy storage capacity verification model comprises constraint conditions and an objective function; the constraint conditions are set according to the thermal power generating unit parameters, the wind power generating unit parameters, the energy storage equipment parameters, the power user parameters and the network topology data; the objective function is a function established by taking the higher rated power and the larger rated capacity of the energy storage equipment as targets; and the optimal admittance capacity of the energy storage equipment is obtained according to the rated power and rated capacity of the energy storage equipment.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present application have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present application and the core ideas thereof; also, it is within the scope of the present application to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the application.

Claims (10)

1. The network side energy storage optimal capacity verification method is characterized by comprising the following steps of:
step 1: acquiring parameters of each thermal power unit, parameters of each wind power unit, parameters of energy storage equipment, parameters of power users and network topology data of a power system;
step 2: determining the optimal admittance capacity of the energy storage equipment according to the energy storage capacity verification model; the energy storage capacity verification model comprises constraint conditions and an objective function; the constraint conditions are set according to the thermal power generating unit parameters, the wind power generating unit parameters, the energy storage equipment parameters, the power user parameters and the network topology data; the objective function is a function established by taking the higher rated power and the larger rated capacity of the energy storage equipment as targets; and the optimal admittance capacity of the energy storage equipment is obtained according to the rated power and rated capacity of the energy storage equipment.
2. The network-side energy storage optimal capacity verification method according to claim 1, wherein the constraint conditions comprise a climbing constraint of a thermal power unit, a minimum on-off time constraint of the thermal power unit, an output constraint of the thermal power unit, a line tide constraint, a system power balance constraint, an energy storage power and capacity constraint, an energy storage charge-discharge start-stop constraint, an energy storage charge-discharge constraint and an energy storage electric quantity constraint.
3. The network-side energy storage optimal capacity verification method according to claim 1, wherein the objective function is specifically as follows:
wherein C is ib For an optimal admission capacity of the energy storage device,and->Rated power and rated capacity of the energy storage device k; i inv,P And I inv,E The unit power parameter and the unit capacity parameter of the energy storage device k are respectively.
4. The network-side energy storage optimal capacity verification method according to claim 2, wherein the energy storage electric quantity constraint is specifically as follows:
SOC t ＝SOC t-1 +(η t cha P t cha -P t dis /η t dis )；
wherein SOC is t,min ≤SOC t ≤SOC t,max ，SOC t Charge amount of energy storage system at t moment and SOC t-1 The charge quantity eta of the energy storage system at the moment t-1 t cha ,η t dis Respectively the charge and discharge efficiency and P of the energy storage system at the moment t t cha ,P t dis Respectively the charge power and the discharge power of the energy storage system at the moment t and the SOC t,min The lower limit of the charge quantity of the energy storage system at the moment t is SOC t,max The upper limit of the charge quantity of the energy storage system at the time t.
5. The network-side energy storage optimal capacity verification method according to claim 2, wherein the energy storage power and capacity constraint comprises an energy storage power constraint and an energy storage capacity constraint;
the stored energy power constraint is as follows:
the energy storage capacity constraint is as follows:
wherein P is load Is the total load of the power system; t is t max And t min As an upper and lower limit for the sustainable discharge time of the energy storage device,and->The rated power and rated capacity of the energy storage device k are respectively, and delta is the energy storage scale of the system which is not higher than the percentage of the total load in the system.
6. The network-side energy storage optimal capacity verification method according to claim 2, wherein the power balance constraint of the power system is as follows:
wherein Ω G Is a collection of thermal power generating units; w is a collection of wind turbines; omega shape E A collection of energy storage devices; omega shape L Is a collection of electrical loads;respectively charging and discharging power of the energy storage device k at the time t; />The output of the thermal power unit i at the time t is obtained; />The output of the wind turbine generator set w at the time t is obtained; />Is the demand of the power system load j at the time t.
7. The network-side energy storage optimal capacity verification method according to claim 2, wherein the thermal power generating unit minimum start-stop time constraint is as follows:
wherein T is i on ,T i off The minimum continuous start-up time and the minimum continuous stop time of the ith thermal power generating unit are respectively; u (u) i,t The power-on state at the moment t of the ith thermal power generating unit is the power-on state, and the power-on time u is the power-on time u i,t =1, u at shutdown i,t ＝0。
8. The network-side energy storage optimal capacity verification method according to claim 2, wherein the thermal power generating unit output constraint is specifically as follows:
u i,t P i,min ≤P i,t ≤u i,t P i,max ；
wherein u is i,t The method is characterized in that the method is an on-off state of an ith thermal power generating unit at a time t; p (P) i,max ,P i,min The maximum output and the minimum output of the ith thermal power generating unit are respectively.
9. The network-side energy storage optimal capacity verification method according to claim 2, wherein the climbing constraint of the thermal power generating unit is specifically as follows:
wherein R is i U ,R i D Respectively the upward and downward climbing capacity of the ith thermal power generating unit,for the output of the thermal power unit i at the time t, < >>The output of the ith thermal power generating unit at the time t-1 is obtained.
10. An energy storage equipment decision-making system based on wind-fire storage joint operation index is optimal, which is characterized by comprising:
the parameter acquisition module is used for acquiring parameters of each thermal power unit, parameters of each wind power unit, parameters of energy storage equipment, parameters of power users and network topology data of the power system;
the capacity calculation module is used for determining the optimal admittance capacity of the energy storage equipment according to the energy storage capacity verification model; the energy storage capacity verification model comprises constraint conditions and an objective function; the constraint conditions are set according to the thermal power generating unit parameters, the wind power generating unit parameters, the energy storage equipment parameters, the power user parameters and the network topology data; the objective function is a function established by taking the higher rated power and the larger rated capacity of the energy storage equipment as targets; and the optimal admittance capacity of the energy storage equipment is obtained according to the rated power and rated capacity of the energy storage equipment.
CN202310434266.6A 2023-04-21 2023-04-21 Network side energy storage optimal capacity verification method and system Pending CN116632883A (en)

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