Networking type energy storage planning method and system considering inertia response and primary frequency modulation

Abstract

The invention provides a network construction type energy storage planning method and system considering inertia response and primary frequency modulation, and the method comprises the steps: screening a typical new energy output scene based on a Monte Carlo method and a scene reduction method, and building an energy storage planning configuration model of a new energy base in the typical scene; the method comprises the following steps: excavating the power self-adaptive adjustment capability of network construction type energy storage, setting the power self-adaptive adjustment range of the network construction type energy storage, and constructing a mathematical model representing the power adjustment and inertia compensation characteristics of the network construction type energy storage; the method comprises the following steps: introducing frequency safety into an energy storage planning configuration model as a target function to form a double-layer model, carrying out iterative solution on the double-layer model by adopting a genetic algorithm, and deciding a network construction type energy storage optimal configuration scheme under joint linkage of economical efficiency and safety targets. The frequency of the new energy base can be safe and stable.

Description

Technical Field

[0001] The present invention belongs to the field of energy storage planning, and in particular relates to a grid-type energy storage planning method and system taking inertia response and primary frequency modulation into account. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Large-scale grid connection of new energy will lead to a lack of rotational inertia and voltage support in new energy bases, and the uncertainty of new energy will increase the difficulty of balancing electricity and power. If we can build an economic operation model for grid-type energy storage and distributed new energy, and establish a new energy base model with self-regulation capabilities, we can accurately describe the working and operating mechanism of the new energy base, thereby providing a theoretical basis for subsequent grid-type energy storage planning. Therefore, research on this type of modeling is imperative.

[0004] The internal parameters of a new energy base are determined in a short period of time, while the external environmental factors that affect new energy power generation, such as solar radiation, temperature and wind speed, are changing rapidly, resulting in intermittent, volatile and uncertain characteristics of new energy power generation. In addition, large-scale new energy grid connection will lead to problems such as lack of rotational inertia, poor frequency stability and wide-band oscillation in new energy bases. The volatility after large-scale new energy is connected to the new energy base has a huge negative impact on the safety and smooth operation of the base.

[0005] Traditional synchronous motors and synchronous condensers have the characteristics of providing voltage support and rotational inertia for new energy bases. Due to the lack of traditional synchronous generators and synchronous condensers, new energy bases cannot provide voltage support and rotational inertia for new energy bases. Research on grid-type energy storage can reduce the installed capacity of synchronous motors and synchronous condensers, give full play to the advantages of grid-type energy storage in voltage support, providing rotational inertia, and flexible charging and discharging, and ensure the safe and stable operation of new energy bases.

[0006] Most of the existing energy storage configuration methods do not fully consider the special operating characteristics of new energy bases without conventional power support, resulting in unreasonable energy storage configuration and failure to meet the system frequency stability requirements; at the same time, the influence of inertia time constant and primary frequency modulation coefficient on frequency is not considered during frequency response. By setting the optimal energy storage inertia response and primary frequency modulation parameters, the frequency support capability of grid-connected energy storage can be fully utilized. Summary of the invention

[0007] In order to solve the above problems, the present invention proposes a grid-type energy storage planning method and system taking into account inertia response and primary frequency modulation.

[0008] According to some embodiments, the present invention adopts the following technical solutions:

[0009] A grid-type energy storage planning method taking into account inertia response and primary frequency modulation comprises the following steps:

[0010] Based on the Monte Carlo method and scenario reduction method, typical renewable energy output scenarios are screened, and a storage planning and configuration model for renewable energy bases under typical scenarios is established;

[0011] Explore the power adaptive regulation capability of grid-type energy storage, set the power adaptive regulation range of grid-type energy storage, and construct a mathematical model to characterize the power regulation and inertia compensation characteristics of grid-type energy storage;

[0012] Frequency security is introduced as the objective function into the energy storage planning and configuration model to form a two-layer model. The genetic algorithm is used to solve the two-layer model, and the optimal configuration plan for grid-type energy storage is decided under the linkage of economic and safety goals.

[0013] As an optional implementation method, based on the Monte Carlo method and the scenario reduction method, the process of screening typical new energy output scenarios includes:

[0014] According to the fluctuation characteristics and seasonal features of wind and light, the Monte Carlo method is used to generate a set of renewable energy output scenarios exceeding the set quantity, and the K-means scenario clustering method is used to reduce the renewable energy output scenarios to representative scenarios less than the set quantity.

[0015] As an optional implementation method, the process of establishing a new energy base energy storage planning and configuration model under a typical scenario includes: the objective function of the new energy base energy storage planning and configuration model is to minimize the total cost, which includes the average daily energy storage investment cost, energy storage maintenance cost and the total operating cost of the new energy base.

[0016] As an optional implementation, the constraints of the energy storage planning and configuration model of the new energy base include DC transmission power range constraints, ramp power constraints, operation time constraints, power adjustment times constraints, power balance constraints, weak AC system support power constraints, new energy output constraints and energy storage operation constraints.

[0017] As an optional implementation method, the process of exploring the power adaptive regulation capability of grid-type energy storage includes: analyzing the relationship between the virtual inertia of grid-type energy storage and the frequency stability of the new energy base, taking the maximum frequency deviation, the maximum frequency change rate, and the quasi-steady-state frequency deviation as frequency safety indicators, and building a virtual inertia model of wind, light, and storage according to the operating characteristics of wind, light, and storage in the new energy base, and obtaining a frequency response model for inertia response and primary frequency regulation parameter optimization.

[0018] As a further step, in the inertia response stage, the grid-type energy storage and grid-type wind turbines achieve inertial response to alleviate frequency fluctuations, and then the active power can be adjusted through the grid-type control to complete a frequency regulation task.

[0019] As a further step, the frequency response model is:

[0020]

[0021] In the formula, Indicates the system inertia constant; ΔP e Indicates the system active unbalanced power; ΔP w and ΔP ess They represent the active power increment of the wind farm and the energy storage power station respectively; Δf(t) represents the frequency deviation; and D represents the damping coefficient of the system.

[0022] As a further step, the total system inertia of the new energy base is:

[0023]

[0024]

[0025] Among them, the total system inertia of the new energy base Provided by wind farms and grid-connected energy storage power stations; represents the virtual inertia time constant of the wind farm at time t, Represents the total inertia of the grid-type wind farm N Wi Represents the number of grid-type wind farms, P Wn,i and P n They represent the rated power of the i-th grid-connected wind farm and the rated power of the energy storage power station respectively; is the inertia time constant of the energy storage power station at time t.

[0026] As a further step, the minimum inertia requirement of the new energy base needs to meet:

[0027]

[0028] in, is the expected disturbance frequency at time t; R t,max is the maximum frequency change rate allowed by the system at time t, and f0 is the standard frequency of the system.

[0029] As an optional implementation method, the process of introducing frequency security as an objective function into the energy storage planning configuration model includes: taking the optimal multi-frequency safety index as the objective function, optimizing the inertia response and primary frequency regulation parameters of the grid-type energy storage, and the constraints of the objective function include inertia time constant constraints, primary frequency regulation coefficient constraints, and constraints on energy storage device capacity and power limit during transient processes.

[0030] A grid-type energy storage planning system taking into account inertia response and primary frequency modulation comprises:

[0031] The energy storage planning and configuration module is configured to screen typical renewable energy output scenarios based on the Monte Carlo method and scenario reduction method, and establish an energy storage planning and configuration model for renewable energy bases under typical scenarios;

[0032] A power regulation module is configured to explore the power adaptive regulation capability of the grid-type energy storage, set the power adaptive regulation range of the grid-type energy storage, and construct a mathematical model to characterize the power regulation and inertia compensation characteristics of the grid-type energy storage;

[0033] The two-layer optimization module is configured to introduce frequency security as an objective function into the energy storage planning and configuration model to form a two-layer model. The genetic algorithm is used to solve the two-layer model and decide on the optimal configuration plan for the grid-type energy storage under the linkage of economic and safety goals.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] The present invention proposes a method for optimizing the inertia response and primary frequency modulation parameters of a new energy base network energy storage system taking into account multiple frequency safety indicators. The method can set the optimal energy storage inertia response and primary frequency modulation parameters according to the expected power fluctuations, and give full play to the frequency support capability of the network energy storage system.

[0036] The present invention takes into account multiple frequency safety indicators. Based on the obtained grid-type energy storage capacity and power configuration, a grid-type energy storage planning for new energy bases is proposed that takes into account inertia response and primary frequency modulation parameter optimization, and achieves frequency stability of new energy bases, while effectively reducing the configuration required for new energy bases.

[0037] This paper uses genetic algorithms to propose a grid-type energy storage configuration planning method that comprehensively considers safety and economy for typical scenarios of new energy bases. This method provides a scientific decision-making basis for the configuration of grid-type energy storage in new energy bases, helps reduce the planning cost of new energy bases, and improves the operating efficiency and stability of new energy bases.

[0038] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0040] Figure 1 It is a schematic diagram of a typical DC transmission structure;

[0041] Figure 2 Frequency response process for new energy base;

[0042] Figure 3 It is the frequency response model of the new energy base;

[0043] Figure 4 Flowchart for solving the optimal configuration of energy storage and frequency response model for new energy bases. DETAILED DESCRIPTION

[0044] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0045] It should be noted that the following detailed descriptions are all illustrative and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0046] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0047] In the absence of conflict, the embodiments in this application and the features in the embodiments may be combined with each other.

[0048] Embodiment 1

[0049] First, some necessary explanations:

[0050] Grid-Forming Energy Storage refers to an energy storage system that can actively control the voltage and frequency of the power system. It is different from traditional grid-following energy storage. The grid-forming energy storage system can provide electric energy independently of the voltage and frequency changes of the power grid, thus playing a role similar to that of a traditional synchronous generator in the power system.

[0051] A new energy base usually refers to a concentrated geographical area dedicated to the development and utilization of various new energy resources, such as solar energy, wind energy, geothermal energy, tidal energy and other renewable energy sources. The purpose of these bases is to produce clean electricity on a large scale to support the diversification of energy supply and reduce the impact on the environment.

[0052] Inertial response refers to the ability of a system to maintain a short-term stable state when faced with a sudden power imbalance. This ability mainly comes from the inertia of the system, that is, the system's resistance to frequency changes.

[0053] A method for energy storage planning that takes into account inertia response and primary frequency regulation parameter optimization. First, based on the Monte Carlo method and scenario reduction method, typical renewable energy output scenarios are screened, and a new energy base model that takes into account the adaptive regulation capability of grid-type energy storage under typical scenarios is established; secondly, the power adaptive regulation capability of grid-type energy storage is explored, and the power adaptive regulation range of grid-type energy storage is set. Aiming at the frequency fluctuation problem caused by large-scale renewable energy access, a mathematical model that can accurately characterize the power regulation and inertia compensation characteristics of grid-type energy storage is constructed; finally, frequency safety is introduced as an objective function into the operating layer objective function, and a genetic algorithm is used to solve the model, so that the system can decide on the optimal configuration plan of grid-type energy storage under the linkage of economic and safety goals.

[0054] First, the energy storage planning and configuration process including grid-type energy storage is introduced, including:

[0055] By analyzing the fluctuation characteristics and seasonal characteristics of wind and light, the Monte Carlo method is used to generate a large number of renewable energy output scenario sets, and the K-means scenario clustering method is used to reduce the renewable energy output scenarios to a small number of representative scenarios.

[0056] Based on the frequency regulation characteristics and models of grid-connected energy storage, and targeting the uncertainty problem of renewable energy output, a mathematical model is established that can accurately characterize the operating characteristics of wind turbines, photovoltaics, and grid-connected energy storage.

[0057] Based on the output characteristics of various resources such as wind, light, and storage, and with the goal of tapping the interactive potential of various flexible resources such as wind, light, and storage, a new energy base model with a high degree of autonomy and self-regulation capabilities is established, thereby improving the reliability and stability of the base.

[0058] According to the seasonal fluctuation characteristics and resource endowment of different scenarios, the capacity matching plans of energy storage and other equipment in each scenario are studied, and a planning and configuration model for new energy bases including grid-type energy storage in typical scenarios is established.

[0059] The frequency stabilization process of the new energy base taking into account the inertia response and the optimization of the primary frequency modulation parameters includes:

[0060] The frequency response process of the new energy base is analyzed to obtain the connection between the base frequency response and the virtual inertia of the grid-type energy storage.

[0061] Set three frequency safety indicators: maximum frequency change rate, maximum frequency offset, and quasi-steady-state frequency deviation to verify effectiveness;

[0062] Generate virtual inertia constants for each wind farm based on wind and solar output scenarios, calculate virtual inertia, and provide inertia support for new energy bases;

[0063] Carry out large disturbances on the new energy base to simulate the power shortage caused by the fluctuation of new energy output, and observe the changes of the above indicators;

[0064] Determine whether the inertia provided by the grid-type energy storage meets the system requirements through indicator changes; and pass the lower-level results to the upper-level planning layer;

[0065] Use genetic algorithm to solve the problem.

[0066] The following is a more detailed description:

[0067] Constructing the objective function for optimal energy storage configuration

[0068] The goal of energy storage planning for new energy bases is to minimize the total cost, as shown in formula (1). This includes the average daily energy storage investment cost, as shown in formula (2), the energy storage maintenance cost, as shown in formula (3), and the total operating cost of the new energy base, as shown in formula (4).

[0069]

[0070] C o&m =C om P n (3)

[0071] C op =C punish +C reserve +C trans (4)

[0072]

[0073] Where: C total represents the total cost of energy storage; C inv represents the average daily investment cost of energy storage; C o&m represents the daily maintenance cost; π r represents the probability of a typical scene r appearing; C op,r represents the operating cost of the system in a typical scenario r; C punish C represents the penalty cost of abandoning wind and solar power at the base; reserve represents the load shedding standby cost; C transrepresents the AC system support power cost; C p and C cap Respectively represent the unit power and capacity investment coefficient of the energy storage system; P n and E n Respectively represent the rated power and rated capacity of the energy storage system; T cyc represents the operating life of the energy storage; i represents the investment discount factor calculated at an annual interest rate; C om represents the average daily maintenance cost per unit; c w and c v They represent the unit wind abandonment penalty coefficient and solar abandonment penalty coefficient respectively; c de represents the unit standby cost; c e It represents the unit electricity cost in Northwest China; and They represent the predicted output and the maximum available output of wind farm i at time t respectively; and They represent the predicted output and the maximum available output of PV power station i at time t respectively. represents the reserve power of wind farm i, where α represents the reserve rate of wind farm, It represents the supporting power provided by the weak AC system at time t.

[0074] DC transmission technology is one of the effective ways to transmit new energy over long distances. In order to meet the power transmission needs of new energy bases, this embodiment focuses on the DC operation mode when modeling. The typical DC transmission structure diagram is shown in the figure. Figure 1 shown.

[0075] DC power transmission range constraints:

[0076]

[0077] Where: P t DC represents the DC transmission power in the period t; P DC and They represent the upper and lower limits of DC transmission power respectively; d represents a typical day.

[0078] DC line ramp power constraints in adjacent time periods:

[0079]

[0080] Where: r down and r up They represent the downward and upward climbing capabilities of the DC line respectively; and They represent the state variables when the DC transmission power is in landslide and climbing respectively.

[0081] Formula (8) represents the conditions that the ramp state variable should satisfy in each time period, that is, the state of the DC transmission power in the same time period is constant, and the state of the DC transmission power in adjacent time periods must be adjusted.

[0082] DC constant power operation time constraints:

[0083] The DC constant power operation time constraint is a limit on the continuous operation time of related equipment in the DC transmission link, mainly to ensure that the equipment can maintain stable performance during long-term operation.

[0084]

[0085] Where: N T Indicates the minimum number of time periods allowed for power adjustment.

[0086] DC adjustment times constraint:

[0087] Since the state of DC transmission power cannot be changed frequently within the dispatch cycle, constraints are established on its adjustment times:

[0088]

[0089] Power balance constraints:

[0090] Power balance constraint is a prerequisite for energy storage configuration planning for new energy bases, ensuring that the power generation and transmission power of each part of the base remain balanced.

[0091]

[0092] Where: represents the actual output of the i-th wind farm at time t; represents the actual output of the ith photovoltaic power station at time t; N W and N V Respectively represent the number of wind farms and photovoltaic power stations; P t ess,dis and P t ess,ch They represent the energy storage charging power and discharging power during time period t respectively.

[0093] Weak AC system support power constraints:

[0094] Since the new energy base has no conventional energy support, the local power system strength is low, and the weak AC system support power constraint is a power constraint condition set to ensure the stable operation of the system.

[0095] P trans,min ≤P t trans ≤P trans,max (12)

[0096] Where: P trans,min and P trans,max They respectively represent the minimum and maximum values ​​of the supporting power provided by the weak AC system.

[0097] New energy output constraints:

[0098] The output constraint of new energy is mainly to reasonably limit the power of wind power generation and photovoltaic power generation in the new energy base, ensuring the optimization of resource allocation while ensuring stability. The maximum output of new energy and the predicted power satisfy equations (15) and (16). When the wind power output is greater than 20% of the rated power, it needs to participate in frequency regulation.

[0099]

[0100] Energy storage operation constraints:

[0101] Energy storage operation constraints mainly restrict the operation status of energy storage batteries, in order to maximize the role of grid-connected energy storage in new energy bases and ensure the stable operation of energy storage systems. Energy storage operation constraints mainly include energy storage discharge power constraints and charging power constraints (17)~(18); charging and discharging sign variable constraints (19), capacity changes of energy storage in each period (20) and capacity constraints (21)~(22).

[0102]

[0103] E0=0.2E n (twenty three)

[0104] Where: and They represent the energy storage discharge state variable and charging state variable respectively; represents the energy storage capacity corresponding to time period t; E min and E0 represent the minimum capacity and initial capacity allowed for energy storage in period t respectively; η ch and η dis They represent the energy storage charging efficiency and discharging efficiency respectively.

[0105] Frequency response process of new energy base based on inertia response and primary frequency modulation parameter optimization:

[0106] Unlike traditional power systems that rely on synchronous machines for frequency regulation, new energy bases that lack conventional power support use grid-based control technology to achieve frequency regulation. In the inertia response stage, grid-based energy storage and grid-based wind turbines can achieve inertia response similar to thermal power generators to alleviate frequency fluctuations, and then grid-based control can also be used to adjust active power and complete a frequency regulation task.

[0107] Figure 2Describes the frequency response process of the new energy base, from Figure 2 It can be seen that: t0~t dz is the inertia response stage, t1~t2 is the primary frequency modulation stage, t1~t dz is the overlapping area under the combined action of the two. For the inertia response curve, it rises to the maximum value at the moment of power shortage and reaches 0 when the system frequency decreases to the lowest point. After the frequency fluctuation exceeds the frequency modulation dead zone, a frequency modulation begins, and its value is positively correlated with the system frequency deviation. The frequency change of the new energy base can be described by formula (24):

[0108]

[0109] Where: Indicates the system inertia constant; ΔP e Indicates the system active unbalanced power; ΔP w and ΔP ess They represent the active power increment of the wind farm and the energy storage power station respectively; Δf(t) represents the frequency deviation; and D represents the damping coefficient of the system.

[0110] In order to intuitively reflect the improvement effect of inertia support on the frequency stability of the new energy base, the total system inertia of the new energy base is expressed as follows:

[0111]

[0112] Where: The total system inertia of the new energy base Provided by wind farms and grid-connected energy storage power stations; represents the virtual inertia time constant of the wind farm at time t, Represents the total inertia of the grid-type wind farm N Wi Represents the number of grid-type wind farms, P Wn,i and P n They represent the rated power of the i-th grid-connected wind farm and the rated power of the energy storage power station respectively; is the inertia time constant of the energy storage power station at time t.

[0113] Inertia requirements for new energy bases

[0114] The minimum inertia requirement of the new energy base must meet the following equation (27):

[0115]

[0116] Where: ΔP t ini is the expected disturbance frequency at time t; R t,max is the maximum frequency change rate allowed by the system at time t.

[0117] The frequency security of new energy bases is particularly important. Frequency security mainly refers to whether the dynamic change of frequency after disturbance meets the safety setting requirements of the equipment for the grid frequency. Generally, the system frequency response can be calculated by time domain simulation method, approximate solution method, etc., and then it can be judged whether the frequency change index meets the safety requirements. The frequency security indicators considered in this invention include:

[0118] Maximum frequency change rate:

[0119]

[0120] Where: f0 is the system standard frequency; ΔP t ini is the disturbance power received by the new energy base at time t; is the minimum inertia requirement of the new energy base at time t.

[0121] Maximum frequency deviation:

[0122] Δf t,dz =max(Δf t,n ),n=1...T / τ (29)

[0123] Where: Δf t,n is the frequency deviation of the nth step at time t.

[0124] Frequency Quasi-Steady-State Deviation

[0125]

[0126] Where: D is the damping coefficient of the new energy base, R t is the frequency change rate of the new energy base at time t.

[0127] This embodiment takes the optimal multi-frequency safety index as the objective function, optimizes the grid-type energy storage inertia response and the primary frequency modulation parameters, considers the grid-type control mode of the voltage source type VSG when simulating and calculating the frequency response, and also considers the frequency modulation dead zone and the limiting link, and establishes the frequency response model of the new energy base, such as Figure 2 shown.

[0128] The normalized optimal objective function of the multi-frequency safety index is constructed:

[0129]

[0130] Where: R max , Δf n,max , Δf ss,max They are the safety warning values ​​of the maximum frequency change rate, the maximum frequency offset, and the frequency quasi-steady-state deviation; a, b, and c are the weight coefficients of the three safety indicators.

[0131] Inertia time constant constraint:

[0132]

[0133] Where: Respectively represent the upper and lower limits of the inertia time constant.

[0134] Primary frequency modulation coefficient constraint

[0135]

[0136] Where: Respectively represent the upper and lower limits of the inertia time constant.

[0137] At the same time, the grid-type energy storage inertia and primary frequency regulation parameter settings are also constrained by the capacity and power limitations of the energy storage equipment during transient processes.

[0138] The primary frequency modulation power adjustment is shown in formula (34):

[0139]

[0140] The primary frequency regulation active reserve constraint is shown in (35):

[0141]

[0142] Where: and They represent the primary frequency regulation power and actual frequency regulation power corresponding to the nth step after the disturbance of the i-th grid-type wind farm in period t; Δf db Indicates the system frequency modulation dead zone; T i w and They represent the first-order inertia time constant and the primary frequency modulation coefficient of the primary frequency modulation stage of the i-th grid-type wind farm respectively; represents the reserve power of the i-th grid-connected wind farm in period t; P Wn,i Represents the rated power of the i-th grid-type wind farm.

[0143] Grid-type energy storage power station

[0144]

[0145] Where: represents the primary frequency modulation power of the grid-type energy storage corresponding to the nth step after the disturbance in period t; T e and They respectively represent the first-order inertia time constant and primary frequency modulation coefficient of the grid-connected energy storage power station.

[0146] The evaluation indexes of frequency stability mainly include the maximum frequency change rate, the maximum frequency offset and the frequency quasi-steady-state deviation. After discretizing the variables, the unbalanced power of the nth step after the disturbance in the t period is expressed, and then the frequency change rate and the corresponding frequency deviation of the nth step after the disturbance in the t period are obtained.

[0147]

[0148] Δf t,n =Δf t,n-1 +R t,n ·τ (39)

[0149] R t,max =max(R t,n ),n=1...T / τ (40)

[0150] Δf t,dz =max(Δf t,n ),n=1...T / τ (41)

[0151] Δf t,ss =Δf t,T / τ (42)

[0152]

[0153] Where: ΔP t,n represents the unbalanced power corresponding to the nth step in the time period t; N wi Indicates the number of grid-type wind farms; RoCoF t,n and Δf t,n They represent the frequency change rate and frequency deviation corresponding to the nth step in the time period t respectively; Δf max Indicates the maximum frequency deviation allowed by the system; Δf ss Indicates the quasi-steady-state frequency deviation.

[0154] The larger the inertia response and primary frequency regulation parameter settings of the grid-type energy storage, the more it can exert its frequency support capability. However, when the system is subjected to a large disturbance, it may cause the power or capacity safety limit of the energy storage device to exceed the limit during the transient process, affecting the health of the equipment and even causing safety problems. Therefore, it is necessary to consider the power and capacity constraints of the energy storage device during the transient process. Formula (43) represents the total frequency regulation power provided by the energy storage system, where the first term on the right side of the equal sign represents the primary frequency regulation power and the second term represents the inertia support power. Formula (44) represents the power and capacity limit constraints of the energy storage device.

[0155]

[0156] Embodiment 2

[0157] A grid-type energy storage planning method taking into account inertia response and primary frequency modulation, when executed, Figure 4 As shown, the main steps include:

[0158] Step 1: Use the Monte Carlo simulation method to generate typical output scenarios of new energy bases, including the historical output of wind power and photovoltaic power;

[0159] Step 2: Input system parameters, including economic parameters and new energy base control parameters. At this time, the iteration starts, the number of iterations is m=1, and the energy storage configuration result is generated. At the same time, the configuration result is transmitted to the operation layer.

[0160] Step 3: Model the virtual inertia of wind, solar and energy storage, and construct the virtual inertia constants of each wind farm and energy storage;

[0161] Step 4: Set up a short-term large disturbance of renewable energy to simulate the power shortage caused by the volatility of wind and solar power output of renewable energy bases;

[0162] Step 5: Use frequency constraints to restrict the new energy base during the simulation operation;

[0163] Step 6: Use the three frequency safety indicators of maximum frequency deviation, maximum frequency change rate, and quasi-steady-state frequency deviation to verify the data during the simulation operation;

[0164] Step 7: Check whether the new energy base meets the frequency safety index. If the new energy base fully meets the frequency safety index, execute step 8; if the new energy base does not fully meet the frequency safety index, then m=m+1, execute step 2;

[0165] Step 8: Output the energy storage planning configuration plan and base operation results.

[0166] Embodiment 3

[0167] A grid-type energy storage planning system taking into account inertia response and primary frequency modulation comprises:

[0168] The energy storage planning and configuration module is configured to screen typical renewable energy output scenarios based on the Monte Carlo method and scenario reduction method, and establish an energy storage planning and configuration model for renewable energy bases under typical scenarios;

[0169] A power regulation module is configured to explore the power adaptive regulation capability of the grid-type energy storage, set the power adaptive regulation range of the grid-type energy storage, and construct a mathematical model to characterize the power regulation and inertia compensation characteristics of the grid-type energy storage;

[0170] The two-layer optimization module is configured to introduce frequency security as an objective function into the energy storage planning and configuration model to form a two-layer model. The genetic algorithm is used to solve the two-layer model and decide on the optimal configuration plan for the grid-type energy storage under the linkage of economic and safety goals.

[0171] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made by those skilled in the art within the spirit and principle of the present invention without creative labor shall be included in the protection scope of the present invention.

Claims

1. A grid-type energy storage planning method taking into account inertia response and primary frequency modulation, characterized in that: The following steps are involved: Based on the Monte Carlo method and scenario reduction method, typical renewable energy output scenarios are screened, and a storage planning and configuration model for renewable energy bases under typical scenarios is established; Explore the power adaptive regulation capability of grid-type energy storage, set the power adaptive regulation range of grid-type energy storage, and construct a mathematical model to characterize the power regulation and inertia compensation characteristics of grid-type energy storage; Frequency security is introduced as the objective function into the energy storage planning and configuration model to form a two-layer model. The genetic algorithm is used to solve the two-layer model, and the optimal configuration plan for grid-type energy storage is decided under the linkage of economic and safety goals.

2. A grid-type energy storage planning method taking into account inertia response and primary frequency modulation as claimed in claim 1, characterized in that: Based on the Monte Carlo method and scenario reduction method, the process of screening typical renewable energy output scenarios includes: According to the fluctuation characteristics and seasonal features of wind and light, the Monte Carlo method is used to generate a set of renewable energy output scenarios exceeding the set quantity, and the K-means scenario clustering method is used to reduce the renewable energy output scenarios to representative scenarios less than the set quantity.

3. A grid-type energy storage planning method taking into account inertia response and primary frequency modulation as claimed in claim 1, characterized in that: The process of establishing a new energy base energy storage planning and configuration model under a typical scenario includes: the objective function of the new energy base energy storage planning and configuration model is to minimize the total cost, which includes the average daily energy storage investment cost, energy storage maintenance cost and the total operating cost of the new energy base.

4. A grid-type energy storage planning method taking into account inertia response and primary frequency modulation as claimed in claim 1, characterized in that: The constraints of the energy storage planning and configuration model for the new energy base include DC transmission power range constraints, ramp power constraints, operation time constraints, power adjustment times constraints, power balance constraints, weak AC system support power constraints, new energy output constraints, and energy storage operation constraints.

5. A grid-type energy storage planning method taking into account inertia response and primary frequency modulation as claimed in claim 1, characterized in that: The process of exploring the power adaptive regulation capability of grid-type energy storage includes: analyzing the relationship between the virtual inertia of grid-type energy storage and the frequency stability of the new energy base, taking the maximum frequency deviation, the maximum frequency change rate, and the quasi-steady-state frequency deviation as frequency safety indicators, and building a virtual inertia model of wind, light, and storage according to the operating characteristics of wind, light, and storage in the new energy base, and obtaining a frequency response model for inertia response and primary frequency regulation parameter optimization.

6. A grid-type energy storage planning method taking into account inertia response and primary frequency modulation as claimed in claim 5, characterized in that the frequency The response model is: In the formula, Indicates the system inertia constant; ΔP e Indicates the system active unbalanced power; ΔP w and ΔP ess They represent the active power increment of the wind farm and the energy storage power station respectively; Δf(t) represents the frequency deviation; and D represents the damping coefficient of the system.

7. A grid-type energy storage planning method taking into account inertia response and primary frequency modulation as claimed in claim 5, characterized in that: The total system inertia of the new energy base is: Among them, the total system inertia of the new energy base Provided by wind farms and grid-connected energy storage power stations; represents the virtual inertia time constant of the wind farm at time t, Represents the total inertia of the grid-type wind farm N Wi Represents the number of grid-type wind farms, P Wn,i and P n They represent the rated power of the i-th grid-connected wind farm and the rated power of the energy storage power station respectively; H t e is the inertia time constant of the energy storage power station at time t.

8. A grid-type energy storage planning method taking into account inertia response and primary frequency modulation as claimed in claim 5, characterized in that: The minimum inertia requirements of the new energy base must meet: Among them, ΔP t ini is the expected disturbance frequency at time t; R t,max is the maximum frequency change rate allowed by the system at time t, and f0 is the standard frequency of the system.

9. A grid-type energy storage planning method taking into account inertia response and primary frequency modulation as claimed in claim 1, characterized in that: The process of introducing frequency security as an objective function into the energy storage planning configuration model includes: taking the optimal multi-frequency security index as the objective function, optimizing the inertia response and primary frequency regulation parameters of the grid-type energy storage, and the constraints of the objective function include inertia time constant constraints, primary frequency regulation coefficient constraints, and constraints on energy storage equipment capacity and power limits during transient processes.

10. A grid-type energy storage planning system taking into account inertia response and primary frequency modulation, characterized in that: include: The energy storage planning and configuration module is configured to screen typical renewable energy output scenarios based on the Monte Carlo method and scenario reduction method, and establish an energy storage planning and configuration model for renewable energy bases under typical scenarios; A power regulation module is configured to explore the power adaptive regulation capability of the grid-type energy storage, set the power adaptive regulation range of the grid-type energy storage, and construct a mathematical model to characterize the power regulation and inertia compensation characteristics of the grid-type energy storage; The two-layer optimization module is configured to introduce frequency security as an objective function into the energy storage planning and configuration model to form a two-layer model. The genetic algorithm is used to iteratively solve the two-layer model, and the optimal configuration plan for grid-type energy storage is decided under the linkage of economic and safety goals.

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