Energy storage guarantee amplitude modulation risk assessment method and system based on power grid

Abstract

The invention discloses an energy storage guarantee amplitude modulation risk assessment method and system based on a power grid, and relates to the technical field of power grid risk assessment. The interception time range is determined by considering the adjacent order amplitude modulation interval condition and the response condition of the energy storage system, and a reliable basis is provided for subsequent risk index assessment. And carrying out comprehensive voltage change condition analysis to obtain a direct risk index which most intuitively describes the voltage amplitude modulation condition. The risk condition of the amplitude modulation behavior is evaluated in combination with a direct risk index and an indirect risk index, the indirect risk index represents other risk comprehensive conditions introduced by amplitude modulation, an overall risk index is generated in combination with the direct risk index and the indirect risk index, and the accuracy and reliability of energy storage guarantee amplitude modulation risk evaluation are improved. And safe and stable operation of the power grid is effectively ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid risk assessment, and particularly to a method and system for evaluating the risk of amplitude modulation support by energy storage based on a power grid. Background Art

[0002] With the increasing complexity of the power grid structure and the large-scale access of renewable energy, the voltage stability of the power grid faces many challenges. As an effective amplitude modulation means, energy storage technology can respond quickly when the power grid voltage fluctuates, absorb or release electric energy, so as to maintain voltage stability. However, the amplitude modulation behavior under energy storage support may also bring certain risks, such as over-modulation or under-modulation, waveform distortion, frequency fluctuation, etc. Therefore, it is particularly important to evaluate the risk of amplitude modulation behavior.

[0003] In the prior art, the risk of amplitude modulation is often evaluated only based on the voltage fluctuation of the power grid, without considering the risks related to other relevant data brought by voltage adjustment, such as the introduced harmonic components, waveform distortion, etc. The situation of voltage fluctuation and other relevant data is not taken into account, resulting in low accuracy and poor reliability of the risk assessment of energy storage support for amplitude modulation.

[0004] Therefore, how to improve the accuracy and reliability of the risk assessment of energy storage support for amplitude modulation is a technical problem to be solved at present. Summary of the Invention

[0005] The purpose of the present invention is to solve the problem of low accuracy and poor reliability of the risk assessment of energy storage support for amplitude modulation caused by not taking into account the situation of voltage fluctuation and other relevant data in the prior art, and to propose a method for evaluating the risk of amplitude modulation support by energy storage based on a power grid, which includes,

[0006] Obtain the charge and discharge records of the energy storage system of the power grid, detect whether there is an amplitude modulation behavior in the charge and discharge records, and obtain the action information of the amplitude modulation behavior, where the action information includes the amplitude modulation behavior time and the amplitude modulation reason;

[0007] Intercept the voltage fluctuation data and other relevant data before and after amplitude modulation through the amplitude modulation behavior time, and analyze the voltage fluctuation data before and after amplitude modulation to generate a direct risk index;

[0008] Generate an indirect risk index according to the amplitude modulation reason and other relevant data before and after amplitude modulation;

[0009] Combine the direct risk index and the indirect risk index to evaluate the risk situation of this amplitude modulation behavior, so as to help optimize and monitor the amplitude modulation behavior.

[0010] In some embodiments of the present application, intercepting the voltage fluctuation data and other relevant data before and after amplitude modulation through the amplitude modulation behavior time includes,

[0011] The time of the amplitude modulation behavior is the start time and the end time of the amplitude modulation behavior. The action information also includes the amplitude modulation range.

[0012] Calculate the differences between the start time and the end time of the previous amplitude modulation behavior and the start time of the current amplitude modulation behavior respectively, to obtain two time differences, and obtain the time difference of the current amplitude modulation behavior according to the two time differences.

[0013] Determine the duration of the current amplitude modulation behavior according to the start time and the end time of the current amplitude modulation behavior.

[0014] Comprehensively determine the first time length according to the amplitude modulation range, time difference and duration of the current amplitude modulation behavior.

[0015] Analyze the response ability of the energy storage system to the previous charge and discharge behaviors, and determine the second time length according to the response ability.

[0016] Determine the target time length according to the first time length and the second time length.

[0017] Display the voltage fluctuation data and other relevant data in the form of a time axis, and mark the start time and the end time of the current amplitude modulation behavior on the data time axis, and confirm the respective time allocation amounts before the start time and after the end time of the amplitude modulation behavior through the target time length.

[0018] Forward extend and backward extend the start time node and the end time node of the amplitude modulation behavior respectively by virtue of the time allocation amount to obtain new time nodes.

[0019] Intercept the data time axis according to the new time nodes to obtain the voltage fluctuation data and other relevant data before and after the amplitude modulation.

[0020] In some embodiments of the present application, analyzing the response ability of the energy storage system to the previous charge and discharge behaviors includes,

[0021] Classify the previous charge and discharge behaviors of the energy storage system into two categories: normal charge and discharge and amplitude modulation charge and discharge;

[0022] Statistically calculate the response time and power change rate of each normal charge and discharge and each amplitude modulation charge and discharge respectively, and calculate the average response time and average power conversion rate of normal charge and discharge and amplitude modulation charge and discharge respectively.

[0023] Define the response index of the energy storage system according to the average response time and average power conversion rate of normal charge and discharge and amplitude modulation charge and discharge respectively, and describe the response ability of the energy storage system through the response index.

[0024]

[0025] Wherein, Ri is the response index of the energy storage system, τ is the response conversion coefficient, α1 and α2 are the combined weights of the response times of normal charge and discharge and amplitude-modulated charge and discharge respectively, t1 and t2 are the average values of the response times of normal charge and discharge and amplitude-modulated charge and discharge respectively, β1 and β2 are the combined weights of the power change rates of normal charge and discharge and amplitude-modulated charge and discharge respectively, Q1 and Q2 are the average values of the power change rates of normal charge and discharge and amplitude-modulated charge and discharge respectively, and k is a preset constant.

[0026] In some embodiments of the present application, the voltage fluctuation data before and after amplitude modulation is analyzed to generate a direct risk index, including

[0027] The voltage fluctuation data is divided into three data segment types: the data segment before amplitude modulation, the data segment during amplitude modulation, and the data segment after amplitude modulation according to the start time and end time of the amplitude modulation behavior;

[0028] Voltage curves corresponding to each of the three data segment types, namely the data segment before amplitude modulation, the data segment during amplitude modulation, and the data segment after amplitude modulation, are constructed;

[0029] The direct risk index is generated by analyzing the voltage curves corresponding to each of the three data segment types, namely the data segment before amplitude modulation, the data segment during amplitude modulation, and the data segment after amplitude modulation.

[0030] In some embodiments of the present application, the direct risk index is generated by analyzing the voltage curves corresponding to each of the three data segment types, namely the data segment before amplitude modulation, the data segment during amplitude modulation, and the data segment after amplitude modulation, including

[0031] The normal voltage range is marked on the voltage curves of each of the three data segment types, namely the data segment before amplitude modulation, the data segment during amplitude modulation, and the data segment after amplitude modulation;

[0032] On the voltage curve of the data segment before amplitude modulation, the first voltage overlimit parameter, the voltage fluctuation amplitude reference value, and the voltage fluctuation frequency reference value are determined according to the normal voltage range on the voltage curve;

[0033] On the voltage curve of the data segment during amplitude modulation, the second voltage overlimit parameter is determined according to the normal voltage range on the voltage curve, and the first voltage fluctuation amplitude parameter and the first voltage fluctuation frequency parameter are determined by the voltage fluctuation amplitude reference value and the voltage fluctuation frequency reference value;

[0034] On the voltage curve of the data segment after amplitude modulation, the third voltage overlimit parameter is determined according to the normal voltage range on the voltage curve, and the second voltage fluctuation amplitude parameter and the second voltage fluctuation frequency parameter are determined by the voltage fluctuation amplitude reference value and the voltage fluctuation frequency reference value;

[0035] Generate a direct risk indicator by synthesizing the first voltage overlimit parameter, the second voltage overlimit parameter, the third voltage overlimit parameter, the first voltage fluctuation amplitude parameter, the first voltage fluctuation frequency parameter, the second voltage fluctuation amplitude parameter, and the second voltage fluctuation frequency parameter.

[0036] In some embodiments of the present application, generating a direct risk indicator by synthesizing the first voltage overlimit parameter, the second voltage overlimit parameter, the third voltage overlimit parameter, the first voltage fluctuation amplitude parameter, the first voltage fluctuation frequency parameter, the second voltage fluctuation amplitude parameter, and the second voltage fluctuation frequency parameter includes:

[0037] Compare the first voltage overlimit parameter, the second voltage overlimit parameter, and the third voltage overlimit parameter to obtain the voltage overlimit change with amplitude adjustment;

[0038] Compare the first voltage fluctuation amplitude parameter, the first voltage fluctuation frequency parameter, the second voltage fluctuation amplitude parameter, and the second voltage fluctuation frequency parameter to obtain the voltage fluctuation amplitude change and voltage fluctuation frequency change with amplitude adjustment;

[0039] Generate a direct risk indicator based on the voltage overlimit change with amplitude adjustment, the voltage fluctuation amplitude change, and the voltage fluctuation frequency change.

[0040] In some embodiments of the present application, generating an indirect risk indicator based on the amplitude adjustment reason and other relevant data before and after amplitude adjustment includes:

[0041] Classify other relevant data, assign influence weights to different types of data through the amplitude adjustment reason, and evaluate each indirect risk based on each type of data before and after amplitude adjustment, and integrate each indirect risk to obtain an indirect risk indicator.

[0042] In some embodiments of the present application, combining the direct risk indicator and the indirect risk indicator to evaluate the risk situation of this amplitude adjustment behavior includes:

[0043]

[0044] Wherein, Rm is the risk level of the amplitude adjustment behavior, γ1 and γ2 are the conversion coefficients of the direct risk indicator and the indirect risk indicator respectively, S1 and S2 are the direct risk indicator and the indirect risk indicator respectively, S 2，j is the risk degree of the jth indirect risk, max(S2,j) is the maximum value of the risk degree in S 2，j the maximum value of the risk degree, b1 and b2 are preset constants, and [] is the rounding symbol.

[0045] Correspondingly, the present application also provides an energy storage guarantee amplitude adjustment risk assessment system based on the power grid, including:

[0046] The first module is used to obtain the charge and discharge records of the energy storage system of the power grid, detect whether there is an amplitude modulation behavior in the charge and discharge records, and obtain the action information of the amplitude modulation behavior. The action information includes the amplitude modulation behavior time and the amplitude modulation reason;

[0047] The second module is used to intercept the voltage fluctuation data and other relevant data before and after the amplitude modulation according to the amplitude modulation behavior time, and analyze the voltage fluctuation data before and after the amplitude modulation to generate a direct risk index;

[0048] The third module is used to generate an indirect risk index according to the amplitude modulation reason and other relevant data before and after the amplitude modulation;

[0049] The fourth module is used to combine the direct risk index and the indirect risk index to evaluate the risk situation of this amplitude modulation behavior, so as to help optimize and monitor the amplitude modulation behavior.

[0050] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0051] 1. Intercept the voltage fluctuation data and other relevant data before and after the amplitude modulation according to the amplitude modulation behavior time, consider the adjacent order amplitude modulation interval situation and the response situation of the energy storage system to determine the intercepted time range, so as to ensure accurate capture of the data change situation before, after and during the amplitude modulation, and provide a reliable basis for the subsequent evaluation of the risk index.

[0052] 2. Analyze the voltage fluctuation data before and after the amplitude modulation to generate a direct risk index, divide the voltage data in different time periods, and conduct a comprehensive analysis of the voltage change situation to obtain a direct risk index that most intuitively describes the voltage amplitude modulation situation. Combine the direct risk index and the indirect risk index to evaluate the risk situation of this amplitude modulation behavior. The indirect risk index represents the comprehensive situation of other risks introduced by the amplitude modulation. Combine the direct risk index and the indirect risk index to generate an overall risk index, improve the accuracy and reliability of the energy storage amplitude modulation risk assessment, and effectively ensure the safe and stable operation of the power grid. Brief Description of the Drawings

[0053] Figure 1 It is a schematic flow chart of a method for evaluating the amplitude modulation risk of energy storage guarantee based on the power grid proposed by the present invention;

[0054] Figure 2 It is a schematic structural diagram of a system for evaluating the amplitude modulation risk of energy storage guarantee based on the power grid proposed by the present invention. Detailed Embodiment

[0055] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0056] Refer toFigure 1 , a risk assessment method for energy storage guarantee amplitude modulation based on the power grid, comprising the following steps:

[0057] Step S101: Obtain the charge and discharge records of the energy storage system of the power grid, detect whether there is an amplitude modulation behavior in the charge and discharge records, and obtain the action information of the amplitude modulation behavior. The action information includes the amplitude modulation behavior time and the amplitude modulation reason.

[0058] In this embodiment, the application of amplitude modulation (AM) in the power system mainly refers to adjusting the amplitude of the power grid voltage. The stability of the voltage amplitude is crucial for the normal operation of the power system, which affects the normal operation of power equipment, power quality, and the stability of the power grid. Obtain the charge and discharge records of the energy storage system from the energy storage management system (EMS) or energy storage monitoring system of the power grid. These systems usually provide API interfaces or database access permissions to allow obtaining real-time or historical charge and discharge data. The data should include information such as the charge and discharge start time, end time, charge and discharge power, and energy storage system status. The action information of the amplitude modulation behavior includes the amplitude modulation behavior time (start time and end time) and the amplitude modulation reason (such as excessive power grid voltage fluctuation, renewable energy generation fluctuation, etc.).

[0059] Step S102: Intercept the voltage fluctuation data and other relevant data before and after amplitude modulation according to the amplitude modulation behavior time, and analyze the voltage fluctuation data before and after amplitude modulation to generate a direct risk index.

[0060] In some embodiments of the present application, intercepting the voltage fluctuation data and other relevant data before and after amplitude modulation according to the amplitude modulation behavior time includes:

[0061] The amplitude modulation behavior time is the amplitude modulation behavior start time and the amplitude modulation behavior end time, and the action information also includes the amplitude modulation amplitude;

[0062] Calculate the differences between the amplitude modulation behavior start time and the amplitude modulation behavior end time of the previous amplitude modulation behavior and the amplitude modulation behavior start time of the current amplitude modulation behavior respectively to obtain two time differences, and obtain the time proximity difference of the current amplitude modulation behavior according to the two time differences;

[0063] Determine the duration of the current amplitude modulation behavior according to the amplitude modulation behavior start time and the amplitude modulation behavior end time of the current amplitude modulation behavior;

[0064] Determine the first time length by integrating the amplitude modulation amplitude, time proximity difference, and duration of the current amplitude modulation behavior;

[0065] Analyze the response ability of the energy storage system to past charge and discharge behaviors, and determine the second time length according to the response ability;

[0066] Determine the target time length according to the first time length and the second time length;

[0067] Display the voltage fluctuation data and other relevant data in the form of a time axis, mark the start time and end time of the amplitude modulation behavior of this amplitude modulation behavior on the data time axis, and confirm the respective time allocation amounts before the start time of the amplitude modulation behavior and after the end time of the amplitude modulation behavior through the target time length;

[0068] Forward extend and backward extend the start time node and end time node of the amplitude modulation behavior respectively by virtue of the time allocation amount to obtain new time nodes;

[0069] Intercept the data time axis according to the new time nodes to obtain the voltage fluctuation data and other relevant data before and after amplitude modulation.

[0070] In this embodiment, during the data interception process, determining the time range is a key step, which directly affects the accuracy and stability of subsequent data analysis. Regarding how to determine the data interception time range according to the amplitude modulation behavior to facilitate the subsequent stable capture of changes or anomalies in the data, the time is mainly determined from two aspects. One is the interval situation between adjacent amplitude modulation behaviors, and the other is the response situation of the energy storage system. Combine the two aspects to determine the optimal interception time length.

[0071] It can be understood that the data interception time here mainly refers to the specific time lengths before the start time of the amplitude modulation behavior and after the end time of the amplitude modulation behavior, because the data before and after amplitude modulation can also reflect the relevant content of amplitude modulation. The data before amplitude modulation reflects the basic situation or anomalies of amplitude modulation, and the data after amplitude modulation reflects the grid stability situation after amplitude modulation.

[0072] In this embodiment, the amplitude modulation amplitude, time difference, and duration will all affect the time setting. For example, if the interval time between amplitude modulation behaviors is short or the amplitude is large, a longer time range may be required to capture these changes and ensure the stability of the data. Allocate the target time length according to the respective time lengths before the start time of the amplitude modulation behavior and after the end time of the amplitude modulation behavior.

[0073] In some embodiments of the present application, analyze the response ability of the energy storage system to past charge and discharge behaviors, including,

[0074] Classify the past charge and discharge behaviors of the energy storage system into two categories: normal charge and discharge and amplitude modulation charge and discharge;

[0075] Statistically calculate the response time and power change rate of each normal charge and discharge and each amplitude modulation charge and discharge respectively, and calculate the average response time and average power change rate of normal charge and discharge and amplitude modulation charge and discharge respectively;

[0076] Define the response index of the energy storage system according to the average response time and the average power conversion rate of normal charge and discharge and amplitude - modulated charge and discharge respectively, and describe the response ability of the energy storage system through the response index;

[0077]

[0078] Among them, Ri is the response index of the energy storage system, τ is the response conversion coefficient, α1 and α2 are the combined weights of the response times of normal charge - discharge and amplitude - modulated charge - discharge respectively, t1 and t2 are the average response times of normal charge - discharge and amplitude - modulated charge - discharge respectively, β1 and β2 are the combined weights of the power change rates of normal charge - discharge and amplitude - modulated charge - discharge respectively, Q1 and Q2 are the average power change rates of normal charge - discharge and amplitude - modulated charge - discharge respectively, and k is a preset constant.

[0079] In this embodiment, if the energy storage system has a fast response speed, then it can respond to the fluctuations of the power grid in a short time. Therefore, the time range of data interception can be relatively short because the system can quickly capture the changes. Vice versa. The response time is a direct index to quantify the response ability of the energy storage system. It usually represents the time required from receiving the dispatching instruction or detecting the power grid change to the energy storage system starting to respond (such as starting to charge or discharge). The shorter the response time, the stronger the response ability of the energy storage system. The power change rate is also an important index to quantify the response ability of the energy storage system, which reflects the response ability of the energy storage system from the side. It represents the amount of power that the energy storage system can change per unit time. The larger the power change rate, the stronger the response ability of the energy storage system, indicating that it can change its output power in a shorter time.

[0080] In this embodiment, for the two types of normal charge - discharge and amplitude - modulated charge - discharge, during the normal charge - discharge process (normal charge - discharge), the response time of the energy storage system may be relatively long because it is mainly affected by factors such as system design, battery characteristics, and control strategies. These factors may not be optimized to pursue the fastest response time under normal operations. During the amplitude - modulated charge - discharge process (amplitude - modulated charge - discharge), the energy storage system needs to quickly respond to the demand changes of the power grid, so the response time is usually short. The system may adopt more advanced control strategies and faster response mechanisms to meet the immediate needs of the power grid.

[0081] It can be understood that when determining the time length of data interception related to amplitude modulation, it is necessary to consider the response speed of the system under different working conditions. If only the response of the amplitude - modulated charge - discharge behavior is considered, some important information in the normal charge - discharge process of the system may be ignored, such as the fluctuation range of the response time and the stability of the power change rate. These information are necessary for determining a reasonable data interception time length, so the response ability of the energy storage system is evaluated by combining the two types of charge - discharge behaviors.

[0082] In this embodiment, the English of the response indicator can be "response indicator", which is used to describe the indicator or metric for measuring or evaluating the response ability of systems, devices, processes, etc. In the combined weights of the response times of normal charge and discharge and amplitude-modulated charge and discharge, the weight of amplitude-modulated charge and discharge is relatively large, with amplitude-modulated charge and discharge being the main focus. It represents the correction of the sum of the self-power change rates to the sum of the response times, and k is used to balance and control the magnitude of the correction function.

[0083] In some embodiments of the present application, the voltage fluctuation data before and after amplitude modulation is analyzed to generate a direct risk indicator, including

[0084] The voltage fluctuation data is divided into three data segment types: the data segment before amplitude modulation, the data segment during amplitude modulation, and the data segment after amplitude modulation according to the start time and end time of the amplitude modulation behavior.

[0085] Voltage curves corresponding to each of the three data segment types, namely the data segment before amplitude modulation, the data segment during amplitude modulation, and the data segment after amplitude modulation, are constructed.

[0086] The direct risk indicator is generated by analyzing the voltage curves corresponding to each of the three data segment types, namely the data segment before amplitude modulation, the data segment during amplitude modulation, and the data segment after amplitude modulation.

[0087] In this embodiment, the voltage curve is the grid voltage curve that changes over time. For the three data segments of the data segment before amplitude modulation, the data segment during amplitude modulation, and the data segment after amplitude modulation, the data segment before amplitude modulation reflects the voltage stability of the grid before the amplitude modulation operation (usually the voltage is unstable and fluctuates). By analyzing this data segment, the voltage fluctuation characteristics of the grid under normal operating conditions can be understood, providing a benchmark for subsequent amplitude modulation operations and risk assessments. The data segment during amplitude modulation directly reflects the impact of the amplitude modulation operation on the grid voltage. By analyzing this data segment, the change trend, fluctuation amplitude, and frequency of the voltage during the amplitude modulation process can be observed, and the effectiveness of the amplitude modulation operation and its impact on the grid stability can be evaluated. The data segment after amplitude modulation reflects the voltage recovery of the grid after the amplitude modulation operation. By analyzing this data segment, the long-term impact of the amplitude modulation operation on the grid voltage and the stability performance of the grid after amplitude modulation can be understood.

[0088] In some embodiments of the present application, the direct risk indicator is generated by analyzing the voltage curves corresponding to each of the three data segment types, namely the data segment before amplitude modulation, the data segment during amplitude modulation, and the data segment after amplitude modulation, including

[0089] The normal voltage range is marked on the voltage curves of each of the three data segments of the data segment before amplitude modulation, the data segment during amplitude modulation, and the data segment after amplitude modulation.

[0090] On the voltage curve of the data segment before amplitude modulation, determine the first voltage overlimit parameter, the reference value of voltage fluctuation amplitude, and the reference value of voltage fluctuation frequency according to the normal voltage range on the voltage curve;

[0091] On the voltage curve of the data segment during amplitude modulation, determine the second voltage overlimit parameter according to the normal voltage range on the voltage curve, and determine the first voltage fluctuation amplitude parameter and the first voltage fluctuation frequency parameter through the reference value of voltage fluctuation amplitude and the reference value of voltage fluctuation frequency;

[0092] On the voltage curve of the data segment after amplitude modulation, determine the third voltage overlimit parameter according to the normal voltage range on the voltage curve, and determine the second voltage fluctuation amplitude parameter and the second voltage fluctuation frequency parameter through the reference value of voltage fluctuation amplitude and the reference value of voltage fluctuation frequency;

[0093] Generate a direct risk index by synthesizing the first voltage overlimit parameter, the second voltage overlimit parameter, the third voltage overlimit parameter, the first voltage fluctuation amplitude parameter, the first voltage fluctuation frequency parameter, the second voltage fluctuation amplitude parameter, and the second voltage fluctuation frequency parameter.

[0094] In this embodiment, the first voltage overlimit parameter, the second voltage overlimit parameter, and the third voltage overlimit parameter are all the number and duration of times that the voltage before amplitude modulation exceeds the normal range on their respective curves. The reference value of voltage fluctuation amplitude is the average amplitude of voltage fluctuation before amplitude modulation, which serves as the reference value. The reference value of voltage fluctuation frequency is the frequency of voltage fluctuation before amplitude modulation, which serves as the reference value. The first voltage fluctuation amplitude parameter, the first voltage fluctuation frequency parameter, the second voltage fluctuation amplitude parameter, and the second voltage fluctuation frequency parameter are all the time and number of times that the voltage fluctuation amplitude continuously exceeds the set threshold (reference value), or the time and number of times that the voltage fluctuation frequency exceeds the set threshold (reference value). Finally, compare the changes between the same parameters of the first voltage overlimit parameter, the second voltage overlimit parameter, the third voltage overlimit parameter, the first voltage fluctuation amplitude parameter, the first voltage fluctuation frequency parameter, the second voltage fluctuation amplitude parameter, and the second voltage fluctuation frequency parameter in the three time periods to generate a direct risk index.

[0095] In some embodiments of the present application, generating a direct risk index by synthesizing the first voltage overlimit parameter, the second voltage overlimit parameter, the third voltage overlimit parameter, the first voltage fluctuation amplitude parameter, the first voltage fluctuation frequency parameter, the second voltage fluctuation amplitude parameter, and the second voltage fluctuation frequency parameter includes,

[0096] Compare the first voltage overlimit parameter, the second voltage overlimit parameter, and the third voltage overlimit parameter to obtain the voltage overlimit change during amplitude modulation;

[0097] Compare the first voltage fluctuation amplitude parameter, the first voltage fluctuation frequency parameter, the second voltage fluctuation amplitude parameter, and the second voltage fluctuation frequency parameter to obtain the amplitude modulation voltage fluctuation amplitude change and voltage fluctuation frequency change;

[0098] Generate a direct risk index based on the amplitude modulation voltage overlimit change, voltage fluctuation amplitude change, and voltage fluctuation frequency change.

[0099] In this embodiment, the first voltage overlimit parameter, the second voltage overlimit parameter, and the third voltage overlimit parameter are all the time or number of times exceeding the normal range. After comparison, the amplitude modulation voltage overlimit change is obtained, which describes the voltage amplitude change situation. The first voltage fluctuation amplitude parameter (compared with the situation before amplitude modulation during the amplitude modulation process), the first voltage fluctuation frequency parameter, the second voltage fluctuation amplitude parameter (compared with the situation before amplitude modulation after amplitude modulation), and the second voltage fluctuation frequency parameter are the same. Compare the changes between voltage fluctuation amplitude parameters and the changes between voltage fluctuation frequency parameters to obtain the amplitude modulation voltage fluctuation amplitude change and voltage fluctuation frequency change, which describe the changes relative to before amplitude modulation during and after the amplitude modulation process. Integrate these change contents to generate a direct risk index, which describes the direct impact of the amplitude modulation process on the voltage and reflects the risk situation.

[0100] Step S103, generate an indirect risk index based on the amplitude modulation reason and other relevant data before and after amplitude modulation.

[0101] In this embodiment, other relevant data includes relevant data such as current, power factor, and power quality index.

[0102] In some embodiments of the present application, an indirect risk index is generated based on the amplitude modulation reason and other relevant data before and after amplitude modulation, including

[0103] Classify other relevant data, assign influence weights to different types of data through the amplitude modulation reason, and evaluate each indirect risk according to each type of data before and after amplitude modulation, and integrate each indirect risk to obtain an indirect risk index.

[0104] In this embodiment, indirect risks include harmonic current, waveform distortion, etc. The energy storage system may generate harmonic current during the charging and discharging process, causing harmonic pollution to the power grid. If the amplitude modulation operation is improper, it may exacerbate the harmonic risk. The energy storage system may change the current and voltage waveforms of the power grid during the charging and discharging process, resulting in waveform distortion. If the amplitude modulation operation is too frequent or the amplitude is too large, it may exacerbate the waveform distortion risk.

[0105] In this embodiment, the reasons for amplitude modulation include types such as renewable energy power generation fluctuations (such as the instability of wind power and solar power generation), grid load changes (such as the peak-valley changes of industrial load and residential load), equipment failures (such as transformer and line failures, etc.). Renewable energy power generation fluctuations may cause frequency deviation, so a relatively large weight is assigned to the frequency deviation, while other parameter weights are relatively small. Additionally, grid load changes may affect the power factor and current distribution, so relatively large weights are assigned to the power factor and current, and other parameter weights are relatively small. Combining these gives an indirect risk indicator.

[0106] Step S104: Combine the direct risk indicator and the indirect risk indicator to evaluate the risk situation of this amplitude modulation behavior, thereby helping to optimize and monitor the amplitude modulation behavior.

[0107] In this embodiment, the risk levels of the two types of indicators are comprehensively evaluated to facilitate decision-makers and operation and maintenance personnel to intuitively understand the risk status of the amplitude modulation behavior.

[0108] In some embodiments of the present application, combining the direct risk indicator and the indirect risk indicator to evaluate the risk situation of this amplitude modulation behavior includes,

[0109]

[0110] where R is the risk level of the amplitude modulation behavior, γ1 and γ2 are the conversion coefficients of the direct risk indicator and the indirect risk indicator respectively, S1 and S2 are the direct risk indicator and the indirect risk indicator respectively, S 2，j is the risk degree of the jth indirect risk, and max(S 2，j ) is the maximum value of the risk degree in S 2，j . b1 and b2 are preset constants, and [] is the rounding symbol.

[0111] In this embodiment, represents the correction of the sum of the direct risk indicator and the indirect risk indicator by the largest indirect risk. b1 and b2 are used to balance the correction function or the overall size of the risk degree.

[0112] Correspondingly, the present application also provides a risk assessment system for energy storage guarantee amplitude modulation based on the power grid, as Figure 2 shown, including,

[0113] The first module is used to obtain the charge and discharge records of the energy storage system of the power grid, detect whether there is an amplitude modulation behavior in the charge and discharge records, and obtain the action information of the amplitude modulation behavior. The action information includes the amplitude modulation behavior time and the reasons for amplitude modulation;

[0114] The second module is used to intercept the voltage fluctuation data and other relevant data before and after amplitude modulation according to the amplitude modulation behavior time, and analyze the voltage fluctuation data before and after amplitude modulation to generate a direct risk indicator;

[0115] A third module, configured to generate an indirect risk indicator based on the reasons for amplitude modulation and other relevant data before and after amplitude modulation;

[0116] A fourth module, configured to evaluate the risk situation of this amplitude modulation behavior by combining the direct risk indicator and the indirect risk indicator, so as to help optimize and monitor the amplitude modulation behavior.

[0117] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0118] 1. By using the amplitude modulation behavior time to intercept the voltage fluctuation data and other relevant data before and after amplitude modulation, considering the adjacent order amplitude modulation interval situation and the response situation of the energy storage system to determine the intercepted time range, so as to ensure accurate capture of the data change situation before, during and after amplitude modulation, and provide a reliable basis for the subsequent evaluation of risk indicators.

[0119] 2. Analyze the voltage fluctuation data before and after amplitude modulation to generate a direct risk indicator, divide the voltage data in different time periods, and conduct a comprehensive analysis of the voltage change situation to obtain a direct risk indicator that most intuitively describes the amplitude modulation situation of the voltage. Combine the direct risk indicator and the indirect risk indicator to evaluate the risk situation of this amplitude modulation behavior. The indirect risk indicator represents the comprehensive situation of other risks introduced by amplitude modulation. Combine the direct risk indicator and the indirect risk indicator to generate an overall risk indicator, improve the accuracy and reliability of the risk assessment of energy storage for amplitude modulation, and effectively ensure the safe and stable operation of the power grid.

[0120] Through the description of the above embodiments, those skilled in the art can clearly understand that the present invention can be implemented through hardware, or can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), including several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various implementation scenarios of the present invention.

[0121] Those skilled in the art can understand that the drawings are only schematic diagrams of a preferred implementation scenario, and the modules or processes in the drawings are not necessarily essential for implementing the present invention.

[0122] Those skilled in the art can understand that the modules in the system in the implementation scenario can be distributed in the system of the implementation scenario according to the description of the implementation scenario, or can be correspondingly changed and located in one or more systems different from this implementation scenario. The modules in the above implementation scenario can be combined into one module, or can be further split into multiple sub-modules.

[0123] As described above, it is only the preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, making equivalent substitutions or changes, shall be covered by the protection scope of the present invention.

Claims

1. A risk assessment method for energy storage guarantee amplitude modulation based on the power grid, characterized in that including, obtaining the charge and discharge records of the energy storage system of the power grid, detecting whether there is an amplitude modulation behavior in the charge and discharge records, and obtaining the action information of the amplitude modulation behavior, where the action information includes the amplitude modulation behavior time and the amplitude modulation reason; intercepting the voltage fluctuation data and other relevant data before and after the amplitude modulation through the amplitude modulation behavior time, and analyzing the voltage fluctuation data before and after the amplitude modulation to generate a direct risk index; generating an indirect risk index according to the amplitude modulation reason and other relevant data before and after the amplitude modulation; combining the direct risk index and the indirect risk index to evaluate the risk situation of this amplitude modulation behavior, so as to help optimize and monitor the amplitude modulation behavior.

2. The method for risk assessment of energy storage guarantee for amplitude modulation based on power grid according to claim 1, wherein intercepting the voltage fluctuation data and other relevant data before and after the amplitude modulation through the amplitude modulation behavior time, including, the amplitude modulation behavior time is the start time and end time of the amplitude modulation behavior, and the action information also includes the amplitude modulation range; calculating the differences between the start time and end time of the amplitude modulation behavior of the previous amplitude modulation behavior and the start time of the current amplitude modulation behavior respectively to obtain two time differences, and obtaining the time difference of the current amplitude modulation behavior according to the two time differences; determining the duration of the current amplitude modulation behavior according to the start time and end time of the current amplitude modulation behavior; determining the first time length by synthesizing the amplitude modulation range, time difference and duration of the current amplitude modulation behavior; analyzing the response ability of the energy storage system to past charge and discharge behaviors, and determining the second time length according to the response ability; determining the target time length according to the first time length and the second time length; displaying the voltage fluctuation data and other relevant data in the form of a time axis, marking the start time and end time of the amplitude modulation behavior of the current amplitude modulation behavior on the data time axis, and confirming the respective time allocation amounts before the start time of the amplitude modulation behavior and after the end time of the amplitude modulation behavior through the target time length; forward extending and backward extending the start time node and end time node of the amplitude modulation behavior respectively by virtue of the time allocation amount to obtain new time nodes; intercepting the data time axis according to the new time nodes to obtain the voltage fluctuation data and other relevant data before and after the amplitude modulation.

3. The method for evaluating the risk of regulating amplitude by energy storage based on the power grid according to claim 2, wherein analyzing the response ability of the energy storage system to past charge and discharge behaviors, including, classifying the past charge and discharge behaviors of the energy storage system into two categories: normal charge and discharge and amplitude modulation charge and discharge; statistically calculating the response time and power change rate of each normal charge and discharge and each amplitude modulation charge and discharge respectively, and calculating the average response time and average power conversion rate of normal charge and discharge and amplitude modulation charge and discharge respectively; defining a response index of the energy storage system according to the average response time and average power change rate of normal charge and discharge and amplitude modulation charge and discharge respectively, and describing the response ability of the energy storage system through the response index; Wherein, Ri is the response index of the energy storage system, τ is the response conversion coefficient, α1 and α2 are the combined weights of the response times of normal charge and discharge and amplitude-modulated charge and discharge respectively, t1 and t2 are the average values of the response times of normal charge and discharge and amplitude-modulated charge and discharge respectively, β1 and β2 are the combined weights of the power change rates of normal charge and discharge and amplitude-modulated charge and discharge respectively, Q1 and Q2 are the average values of the power change rates of normal charge and discharge and amplitude-modulated charge and discharge respectively, and k is a preset constant.

4. The energy storage guarantee amplitude modulation risk assessment method based on the power grid according to claim 2, wherein Analyze the voltage fluctuation data before and after amplitude modulation to generate direct risk indicators, including Classify the voltage fluctuation data into three data segment types: the data segment before amplitude modulation, the data segment during amplitude modulation, and the data segment after amplitude modulation according to the start time and end time of the amplitude modulation behavior; Construct the corresponding voltage curves for the three data segment types of the data segment before amplitude modulation, the data segment during amplitude modulation, and the data segment after amplitude modulation; Analyze the voltage curves corresponding to the three data segment types of the data segment before amplitude modulation, the data segment during amplitude modulation, and the data segment after amplitude modulation to generate direct risk indicators.

5. The method for evaluating the risk of amplitude modulation for energy storage guarantee based on the power grid according to claim 4, wherein, Analyze the voltage curves corresponding to the three data segment types of the data segment before amplitude modulation, the data segment during amplitude modulation, and the data segment after amplitude modulation to generate direct risk indicators, including Mark the normal voltage range on the voltage curves of the three data segment types of the data segment before amplitude modulation, the data segment during amplitude modulation, and the data segment after amplitude modulation; On the voltage curve of the data segment before amplitude modulation, determine the first voltage overlimit parameter, the voltage fluctuation amplitude reference value, and the voltage fluctuation frequency reference value according to the normal voltage range on the voltage curve; On the voltage curve of the data segment during amplitude modulation, determine the second voltage overlimit parameter according to the normal voltage range on the voltage curve, and determine the first voltage fluctuation amplitude parameter and the first voltage fluctuation frequency parameter through the voltage fluctuation amplitude reference value and the voltage fluctuation frequency reference value; On the voltage curve of the data segment after amplitude modulation, determine the third voltage overlimit parameter according to the normal voltage range on the voltage curve, and determine the second voltage fluctuation amplitude parameter and the second voltage fluctuation frequency parameter through the voltage fluctuation amplitude reference value and the voltage fluctuation frequency reference value; Generate direct risk indicators by synthesizing the first voltage overlimit parameter, the second voltage overlimit parameter, the third voltage overlimit parameter, the first voltage fluctuation amplitude parameter, the first voltage fluctuation frequency parameter, the second voltage fluctuation amplitude parameter, and the second voltage fluctuation frequency parameter.

6. The method for evaluating the risk of amplitude modulation for energy storage guarantee based on the power grid according to claim 5, wherein Generate direct risk indicators by synthesizing the first voltage overlimit parameter, the second voltage overlimit parameter, the third voltage overlimit parameter, the first voltage fluctuation amplitude parameter, the first voltage fluctuation frequency parameter, the second voltage fluctuation amplitude parameter, and the second voltage fluctuation frequency parameter, including Compare the first voltage overlimit parameter, the second voltage overlimit parameter, and the third voltage overlimit parameter to obtain the voltage overlimit change of the amplitude modulation; Compare the first voltage fluctuation amplitude parameter, the first voltage fluctuation frequency parameter, the second voltage fluctuation amplitude parameter, and the second voltage fluctuation frequency parameter to obtain the voltage fluctuation amplitude change and the voltage fluctuation frequency change of the amplitude modulation; Generate direct risk indicators according to the voltage overlimit change, the voltage fluctuation amplitude change, and the voltage fluctuation frequency change of the amplitude modulation.

7. The method for evaluating the risk of amplitude modulation guarantee for energy storage based on the power grid according to claim 1, wherein Generate an indirect risk indicator based on the reasons for amplitude modulation and other relevant data before and after amplitude modulation, including classify other relevant data, assign influence weights to different types of data based on the reasons for amplitude modulation, and evaluate each indirect risk according to each type of data before and after amplitude modulation, and integrate each indirect risk to obtain an indirect risk indicator.

8. The method for evaluating the risk of amplitude modulation guarantee for energy storage based on the power grid according to claim 4, wherein Combine the direct risk indicator and the indirect risk indicator to evaluate the risk situation of this amplitude modulation behavior including Among them, Rm is the risk level of the amplitude modulation behavior, γ1 and γ2 are the conversion coefficients of the direct risk index and the indirect risk index respectively, S1 and S2 are the direct risk index and the indirect risk index respectively, S 2，j is the risk degree of the j-th indirect risk, max(S 2，j ) is the maximum value of the risk degree in S 2，j , b1 and b2 are preset constants respectively, and [] is the rounding symbol.

9. A risk assessment system for energy storage guarantee amplitude modulation based on the power grid, characterized in that, including The first module is used to obtain the charge and discharge records of the energy storage system of the power grid, detect whether there is an amplitude modulation behavior in the charge and discharge records, and obtain the action information of the amplitude modulation behavior. The action information includes the amplitude modulation behavior time and the reasons for amplitude modulation; The second module is used to intercept the voltage fluctuation data and other relevant data before and after amplitude modulation through the amplitude modulation behavior time, and analyze the voltage fluctuation data before and after amplitude modulation to generate a direct risk indicator; The third module is used to generate an indirect risk indicator based on the reasons for amplitude modulation and other relevant data before and after amplitude modulation; The fourth module is used to combine the direct risk indicator and the indirect risk indicator to evaluate the risk situation of this amplitude modulation behavior, so as to help optimize and monitor the amplitude modulation behavior.

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