Energy storage equipment working sequence optimization method and system based on terminal distribution network participation

Abstract

The present invention discloses a method and system for optimizing the working sequence of energy storage equipment based on the participation of terminal distribution network, which belongs to the field of power system dispatching technology, including: taking the maximum total revenue of energy storage equipment in the terminal distribution network as the goal, taking the sum of the revenue and cost of each period of energy storage equipment participating in power balance, peak regulation and frequency regulation as the objective function for optimizing the working sequence of energy storage equipment in each period; based on the objective function, optimizing the working sequence of energy storage equipment by setting mutually exclusive constraints. The present invention makes up for the vacancy of the working sequence optimization method for energy storage equipment participating in various regulation in different periods in the day-ahead optimization of terminal distribution network.

Description

Technical Field

[0001] The present invention relates to the technical field of power system dispatching, and in particular to a method and system for optimizing a working sequence of an energy storage device based on the participation of a terminal distribution network. Background Art

[0002] At present, aggregating the adjustable resources of the terminal distribution network to participate in the large power grid regulation is an effective measure to alleviate the contradiction of the shortage of flexible resources in the power grid. The load capacity and new energy generation capacity of the terminal distribution network are relatively small, and due to the high investment cost, the capacity of the energy storage equipment configured inside is also relatively limited. When energy storage equipment participates in multiple regulation at the same time, it is necessary to consider the issue of reserved output and capacity, which will result in the inability to fully utilize the limited capacity and give full play to the advantages of energy storage equipment in each regulation work.

[0003] There are many related studies on the participation of energy storage equipment in grid regulation. For example, based on the relationship between energy storage capacity and load characteristics, the energy storage capacity configuration method to reduce the peak load pressure of the grid is studied; with the goal of maximizing the benefits of energy storage in the auxiliary service market, the optimal planning and control strategy of energy storage equipment participating in frequency regulation is studied; a cost-benefit model is established based on the principle of cooperative game, and the capacity configuration method of energy storage participating in peak load regulation is studied through genetic algorithm; the calendar life model is used to estimate the service life of energy storage, and the energy storage capacity and control strategy for participating in frequency regulation are optimized with the maximum benefit over the entire life cycle; for real-time peak load working scenarios, dynamic planning is used to solve the optimization model, and life constraints are introduced to study energy storage charging and discharging strategies; for load-side energy storage, the control strategy for participating in peak load and frequency regulation coordination scenarios is analyzed and studied from an economic perspective. However, most of the above studies studied the capacity planning and control strategies of energy storage equipment from the perspective of the scenario in which energy storage equipment participates in a single regulation. A few studies also pre-specified the working time sequence of energy storage equipment in the scenario in which energy storage equipment participates in the coordinated control of peak and frequency regulation. They failed to arrange the type of regulation that the energy storage equipment participates in each time period according to the energy storage status and economic benefits, and thereby optimize the optimal working sequence of the energy storage equipment in each time period.

[0004] Therefore, for the scenario where the internal energy storage of the terminal distribution network participates in the regulation of the large power grid, a method is proposed to optimize the working sequence of energy storage equipment participating in the regulation through a constraint satisfaction problem (CSP) optimization model with mutually exclusive conditions. The optimal working sequence is found among various sequences that satisfy the constraints, which is of great significance for the terminal distribution network to give full play to the advantages of energy storage and coordinate other flexible resources to provide auxiliary services for the upper power grid. Summary of the invention

[0005] In order to solve the above problems, the purpose of the present invention is to provide a working sequence optimization technology for energy storage equipment based on the participation of terminal distribution networks, aiming to solve the problem that the capacity of energy storage equipment in terminal distribution networks is limited, and it participates in power balancing, peak shaving (peak shaving or valley filling), and frequency modulation of large power grids at the same time, resulting in poor energy storage utilization.

[0006] In order to achieve the above technical objectives, the present application provides a method for optimizing the working sequence of energy storage equipment based on the participation of terminal distribution network, comprising the following steps:

[0007] Taking the maximum total revenue of energy storage equipment in the terminal distribution network as the goal, the sum of the revenue and cost of energy storage equipment participating in power balancing, peak load regulation and frequency regulation in each period is used as the objective function for optimizing the operation sequence of energy storage equipment in each period.

[0008] Based on the objective function, the working sequence of the energy storage device is optimized by setting mutually exclusive constraints.

[0009] Preferably, in the process of obtaining mutually exclusive constraint conditions, energy storage charging and discharging power constraint, energy storage SOC overall constraint and regulation state constraint are used as the mutually exclusive constraint conditions.

[0010] Preferably, in the process of obtaining the energy storage charging and discharging power constraint and the energy storage SOC overall constraint, the energy storage charging and discharging power constraint is expressed as:

[0011]

[0012] Where: are the maximum charging and maximum discharging power respectively;

[0013] Overall constraints of energy storage SOC:

[0014]

[0015] 0.1<SOC(t)<0.9;

[0016] Where: The upper and lower limits of the energy storage device SOC are 0.9 and 0.1; η d and η c are discharge efficiency and charging efficiency respectively; E is the total capacity of the energy storage device.

[0017] Preferably, in the process of obtaining the control state constraint, the control state constraint is obtained with the goal that the energy storage must have the corresponding SOC condition to participate in the corresponding control, and is expressed as:

[0018]

[0019] Where: and The upper and lower limits of SOC required for energy storage equipment to participate in power balance regulation; The maximum SOC value of the energy storage device participating in valley filling; The minimum SOC value for the energy storage device to participate in peak shaving; and The upper and lower limits of SOC reserved for energy storage equipment to participate in frequency regulation.

[0020] Preferably, in the process of obtaining the revenue and cost of each time period when the energy storage device participates in power balancing, the revenue and cost of each time period when the energy storage device participates in power balancing is expressed as:

[0021]

[0022] In the formula, C B C is the charging and discharging electricity price when the energy storage device participates in power balancing; ESS B is the cost coefficient of energy storage equipment; t is a 1×T dimensional 0-1 matrix of the time series state of the energy storage device participating in power balance. t =1, B t =1, and the rest are 0, indicating that the energy storage device only participates in power balance regulation during period t; P B,t is the power of the energy storage device participating in power balancing during period t.

[0023] Preferably, in the process of obtaining the revenue and cost of each time period when the energy storage device participates in the peak load regulation of the power grid, the revenue and cost of each time period when the energy storage device participates in the peak load regulation of the power grid is expressed as:

[0024]

[0025] In the formula, C S The electricity price for energy storage equipment to participate in peak load regulation auxiliary services; C ESS S is the cost coefficient of energy storage equipment; t is a 1×T dimensional 0-1 matrix of the time sequence state of the energy storage device participating in peak load regulation. t =2 or 3, S t =1, and the rest are 0, indicating that the energy storage equipment only participates in valley filling or peak shaving during period t; P S,t is the power of the energy storage device when participating in peak load regulation during period t.

[0026] Preferably, in the process of obtaining the revenue and cost of each time period when the energy storage device participates in the grid frequency regulation, the revenue and cost of each time period when the energy storage device participates in the grid frequency regulation is expressed as:

[0027]

[0028] In the formula, C R The electricity price for energy storage equipment to participate in frequency regulation auxiliary services; C ESSR is the cost coefficient of energy storage equipment; t is a 1×T dimensional 0-1 matrix of the time sequence state of the energy storage device participating in frequency modulation. t =4, R t =1, and the rest of the elements are 0, indicating that the energy storage device only participates in frequency modulation during period t; P R,t The power value reserved for the frequency modulation of the energy storage device in period t.

[0029] Preferably, the upper and lower limits of SOC required for energy storage to participate in frequency regulation are obtained. In the process, the upper and lower limits for:

[0030]

[0031] Where: π ω is the probability of the scene ω appearing, ΔSOC R,ω is the SOC change value of the energy storage device participating in frequency modulation in scenario ω.

[0032] Preferably, when obtaining the power P reserved by the energy storage device for participating in frequency modulation R In the process, the power P reserved by the energy storage device for frequency regulation R It is expressed as:

[0033]

[0034] Where: is the maximum power of the energy storage device participating in frequency regulation in scenario ω.

[0035] The present invention also discloses a system for optimizing the working sequence of energy storage equipment based on the participation of a terminal distribution network, comprising:

[0036] An objective function construction module is used to maximize the total revenue of energy storage equipment in the terminal distribution network, and to use the sum of the revenue and cost of each period of the energy storage equipment participating in power balancing, peak load regulation and frequency regulation as the objective function for optimizing the operation sequence of the energy storage equipment in each period;

[0037] The control optimization module is used to optimize the working sequence of the energy storage device by setting mutually exclusive constraints based on the objective function.

[0038] The present invention discloses the following technical effects:

[0039] The present invention enables the terminal distribution network to consider that the energy storage only participates in power balance regulation, peak regulation (peak shaving or valley filling), and frequency regulation at most in each period when the internal energy storage capacity is limited, and optimizes the working sequence of energy storage equipment participating in various regulation at different periods in the day-ahead, and obtains the optimal working sequence of energy storage equipment in various sequences that meet the constraint conditions. The present invention fills the gap in the method for optimizing the working sequence of energy storage equipment participating in various regulation at different periods in the day-ahead optimization of the terminal distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1 It is a schematic diagram of the method flow of the present invention. DETAILED DESCRIPTION

[0042] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0043] like Figure 1 As shown, the present invention provides a method for optimizing the working sequence of energy storage devices in each time period of a terminal distribution network participating in grid regulation, and provides a method for optimizing the working timing of energy storage devices within the terminal distribution network, aiming to solve the problem that the capacity of energy storage devices in the terminal distribution network is limited, and the energy storage utilization rate is poor due to the simultaneous participation of the energy storage devices in the same time period in the large grid in power balance, peak shaving (peak shaving or valley filling), and frequency regulation.

[0044] Taking the maximum total benefit of energy storage equipment in the terminal distribution network as the goal, the CSP operation optimization model of the working sequence of energy storage equipment in each period with mutually exclusive conditions is established as follows:

[0045] (1) Overall objective function:

[0046] maxF=f B +fS +f R ;

[0047] Where: F is the total benefit of energy storage equipment; f B 、f S 、f R They are the sum of the benefits and costs of energy storage equipment in each period when it participates in power balancing, peak regulation (peak shaving or valley filling), and frequency regulation.

[0048] (2) The mutually exclusive constraints of the CSP operation optimization model for energy storage equipment are:

[0049] 1) The state variable set of the working sequence of the energy storage device in each period is: X(Z1, Z2, ..., Z T ), Z T This is the type of regulation that energy storage participates in during the T period. In a single period, it can only participate in one of the following regulation types: power balancing, valley filling, peak shaving, and frequency regulation.

[0050] 2) The range of energy storage device state variables is:

[0051]

[0052] Where: D i is the value range of the energy storage state variable; 0 means not participating in regulation; 1 means participating in power balance regulation; 2 means participating in valley filling in peak regulation; 3 means participating in peak shaving in peak regulation; 4 means participating in frequency regulation.

[0053] 3) Constraint set C

[0054] Energy storage charging and discharging power constraints:

[0055]

[0056] Where: are the maximum charge and discharge powers respectively.

[0057] Overall constraints of energy storage SOC:

[0058]

[0059] 0.1<SOC(t)<0.9;

[0060] Where: The upper and lower limits of the energy storage device SOC are 0.9 and 0.1; η d and η c are discharge efficiency and charging efficiency respectively; E is the total capacity of the energy storage device.

[0061] Energy storage must meet the corresponding SOC conditions to participate in the corresponding regulation. The regulation state constraints are:

[0062]

[0063] Where: and The upper and lower limits of SOC required for the energy storage device to participate in power balance regulation. When participating in power balance regulation, the energy storage device needs to reserve sufficient charge and discharge capacity, which is generally 0.4-0.6; The maximum SOC value of the energy storage device participating in valley filling. Sufficient charging capacity must be reserved for the energy storage device to participate in valley filling. It is generally 0.3. The minimum SOC value for the energy storage device to participate in peak shaving. Sufficient discharge capacity must be reserved for the energy storage device to participate in peak shaving. It is generally 0.7. and The upper and lower limits of SOC reserved for energy storage equipment to participate in frequency regulation can be calculated based on historical data.

[0064] (3) The calculation method of the benefit and cost of each period when the energy storage equipment participates in power balancing is:

[0065]

[0066] Where: C B C is the charging and discharging electricity price when the energy storage device participates in power balancing; ESS B is the cost coefficient of energy storage equipment; t is a 1×T dimensional 0-1 matrix of the time series state of the energy storage device participating in power balance. t =1, B t =1, and the rest are 0, indicating that the energy storage device only participates in power balance regulation during period t; P B,t is the power of the energy storage device participating in power balancing during period t, which can be obtained by optimizing the terminal distribution network a day ago.

[0067] (4) The calculation method of the benefit and cost of energy storage equipment in each period when it participates in the peak load regulation of the power grid is:

[0068]

[0069] Where: C S The electricity price for energy storage equipment to participate in peak load regulation auxiliary services; C ESS S is the cost coefficient of energy storage equipment; t is a 1×T dimensional 0-1 matrix of the time sequence state of the energy storage device participating in peak load regulation. t =2 or 3, S t =1, and the rest are 0, indicating that the energy storage equipment only participates in valley filling or peak shaving during period t; P S,t is the power of the energy storage device participating in peak load regulation during period t, which can be obtained by the day-ahead optimization process of the terminal distribution network.

[0070] (5) The calculation method of the revenue and cost of energy storage equipment in each period when it participates in grid frequency regulation is:

[0071]

[0072] Where: C R The electricity price for energy storage equipment to participate in frequency regulation auxiliary services; C ESS R is the cost coefficient of energy storage equipment; t is a 1×T dimensional 0-1 matrix of the time sequence state of the energy storage device participating in frequency modulation. t =4, R t =1, and the rest of the elements are 0, indicating that the energy storage device only participates in frequency modulation during period t; P R,t The power value reserved for the frequency regulation of the energy storage device in period t is evaluated from historical data.

[0073] (6) Reserved space required for energy storage equipment to participate in frequency regulation P R The calculation is obtained by using the scenario analysis method through historical data evaluation:

[0074] 1) Obtain the single scenario characteristics of energy storage equipment participating in frequency modulation through historical data calculation

[0075] The situation in which energy storage equipment participates in frequency modulation in one day in historical data is defined as a scenario, and the maximum power of energy storage equipment participating in frequency modulation for 96 periods in a scenario is calculated. And the energy storage SOC change ΔSOC in each period R :

[0076]

[0077] Where: Δt is the duration of a period of 15 minutes, P R,k It is the power sequence of energy storage participating in AGC frequency modulation in time period t (time scale 3 minutes).

[0078] This can characterize the characteristics of the scene.

[0079] 2) Generate a set of typical scenarios through historical data calculation

[0080] According to the number of days N of selected historical data, the corresponding scene set S can be generated, and the probability of a single scene occurring is When N is very large, in order to improve the calculation speed, the fast previous generation elimination technology based on probability distance is used to reduce the scene. The basic idea is as follows:

[0081] Step 1, calculate the geometric distance between each pair of scenes s and s′ in S;

[0082] Step 2, select the scene d with the smallest sum of probability distances to the remaining scenes;

[0083] Step 3: replace scene d with the scene r in S that is closest to the scene d set, add the probability of d to the probability of scene r, eliminate d, and form a new S′;

[0084] Step 4: Repeat steps 1 to 3 until the number of remaining scenes meets the calculation requirements, and obtain the typical scene set Ω{ξ1,ξ2,...,ξ n}, and the probability of each scene occurring π ω ,ω∈{1,2,...,n}.

[0085] Through the typical set scenario Ω and probability π ω It can characterize the randomness of energy storage equipment participating in frequency modulation.

[0086] 3) Calculate the energy storage equipment’s participation in frequency regulation the next day through typical scenarios P R ;

[0087] The upper and lower limits of SOC required for energy storage to participate in frequency regulation for:

[0088]

[0089] Where: π ω is the probability of the scene ω appearing, ΔSOC R,ω is the SOC change value of the energy storage device participating in frequency modulation in scenario ω.

[0090] The power P reserved for energy storage equipment to participate in frequency regulation R for:

[0091]

[0092] Where: is the maximum power of the energy storage device participating in frequency regulation in scenario ω.

[0093] The present invention enables the terminal distribution network to consider that the energy storage only participates in power balance regulation, peak regulation (peak shaving or valley filling), and frequency regulation at most in each period when the internal energy storage capacity is limited, and optimizes the working sequence of energy storage equipment participating in various regulation at different periods in the day-ahead, and obtains the optimal working sequence of energy storage equipment in various sequences that meet the constraint conditions. The present invention makes up for the lack of working sequence optimization method for energy storage equipment participating in various regulation at different periods in the day-ahead optimization of the terminal distribution network.

[0094] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0095] In the description of the present invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0096] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for optimizing the working sequence of energy storage equipment based on the participation of terminal distribution network, characterized in that: The following steps are involved: Taking the maximum total revenue of energy storage equipment in the terminal distribution network as the goal, the sum of the revenue and cost of energy storage equipment participating in power balancing, peak load regulation and frequency regulation in each period is used as the objective function for optimizing the operation sequence of energy storage equipment in each period. Based on the objective function, the working sequence of the energy storage device is optimized by setting mutually exclusive constraints; In the process of obtaining mutually exclusive constraint conditions, energy storage charging and discharging power constraint, energy storage SOC overall constraint and regulation state constraint are used as the mutually exclusive constraint conditions; In the process of obtaining the energy storage charging and discharging power constraint and the energy storage SOC overall constraint, the energy storage charging and discharging power constraint is expressed as: Where: are the maximum charging and maximum discharging power respectively; Overall constraints of energy storage SOC: 0.1<SOC(t)<0.9; Where: The upper and lower limits of the energy storage device SOC are 0.9 and 0.1; η d and η c are the discharge efficiency and the charging efficiency respectively; E is the total capacity of the energy storage device; In the process of obtaining the control state constraints, the goal is to obtain the control state constraints with the corresponding SOC conditions required for energy storage to participate in the corresponding control, which can be expressed as: Where: and The upper and lower limits of SOC required for energy storage equipment to participate in power balance regulation; The maximum SOC value of the energy storage device participating in valley filling; The minimum SOC value for the energy storage device to participate in peak shaving; and The upper and lower limits of SOC reserved for energy storage equipment to participate in frequency regulation, Z t is the type of regulation that the energy storage participates in during period t; In the process of obtaining the revenue and cost of each period when the energy storage device participates in power balancing, the revenue and cost of each period when the energy storage device participates in power balancing is expressed as: In the formula, C B C is the charging and discharging electricity price when the energy storage device participates in power balancing; ESS B is the cost coefficient of energy storage equipment; t is a 1×T dimensional 0-1 matrix of the time series state of the energy storage device participating in power balance. t =1, B t =1, S t =0, R t =0, indicating that the energy storage device only participates in power balance regulation during period t; P B,t is the power of the energy storage device participating in power balancing during period t; In the process of obtaining the revenue and cost of each period when the energy storage equipment participates in the peak load regulation of the power grid, the revenue and cost of each period when the energy storage equipment participates in the peak load regulation of the power grid is expressed as: In the formula, C S The electricity price for energy storage equipment to participate in peak load regulation auxiliary services; C ESS S is the cost coefficient of energy storage equipment; t is a 1×T dimensional 0-1 matrix of the time sequence state of the energy storage device participating in peak load regulation. t =2 or Z t =3, S t =1, B t =0, R t =0, indicating that the energy storage equipment only participates in valley filling or peak shaving during period t; P S,t is the power of the energy storage device when participating in peak load regulation during period t; In the process of obtaining the revenue and cost of each period when the energy storage equipment participates in the grid frequency regulation, the revenue and cost of each period when the energy storage equipment participates in the grid frequency regulation is expressed as: In the formula, C R The electricity price for energy storage equipment to participate in frequency regulation auxiliary services; C ESS R is the cost coefficient of energy storage equipment; t is a 1×T dimensional 0-1 matrix of the time sequence state of the energy storage device participating in frequency modulation. t =4, R t =1, S t =0, B t =0, indicating that the energy storage device only participates in frequency modulation during period t; P R,t The power value reserved for the frequency modulation of the energy storage device in period t.

2. The method for optimizing the working sequence of energy storage equipment based on the participation of the terminal distribution network according to claim 1 is characterized in that: The upper and lower limits of SOC required for energy storage to participate in frequency regulation are obtained In the process, the upper and lower limits for: Where: π ω is the probability of the scene ω appearing, ΔSOC R,ω is the SOC change value of the energy storage device participating in frequency modulation in scenario ω.

3. The method for optimizing the working sequence of energy storage equipment based on the participation of the terminal distribution network according to claim 2 is characterized in that: In the process of obtaining the power PR reserved by the energy storage device for participating in frequency regulation, the power P reserved by the energy storage device for participating in frequency regulation R It is expressed as: Where: is the maximum power of the energy storage device participating in frequency regulation in scenario ω.

4. A system for optimizing the working sequence of energy storage equipment based on the participation of a terminal distribution network, used to implement the method for optimizing the working sequence of energy storage equipment based on the participation of a terminal distribution network as claimed in claim 1, characterized in that: include: An objective function construction module is used to maximize the total revenue of energy storage equipment in the terminal distribution network, and to use the sum of the revenue and cost of each period of the energy storage equipment participating in power balancing, peak load regulation and frequency regulation as the objective function for optimizing the operation sequence of the energy storage equipment in each period; The control optimization module is used to optimize the working sequence of the energy storage device by setting mutually exclusive constraints based on the objective function.

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