Method and system for evaluating frequency modulation capability of energy storage thermal power generating unit

Abstract

The invention relates to the technical field of electric energy storage control, in particular to an energy storage thermal power generating unit frequency modulation capability assessment method and system, and the method comprises the following steps: based on thermal power storage operation data, identifying node indexes and state records, extracting fluctuations and frequencies, assessing frequency response fitness, analyzing a regulation rate and a cooperation ratio, and screening risk units. And outputting the frequency modulation capability evaluation interval. According to the invention, through integration and identification of operation data of the energy storage thermal power generating unit, electric quantity fluctuation, an energy storage state and load change are monitored in real time, a response period of an energy storage unit is optimized, stability of a frequency modulation process is ensured, battery capacity, a temperature rise rate and a cycle frequency are comprehensively monitored, overload and efficiency reduction are avoided, stable scheduling of a power grid is guaranteed, and the power generation efficiency is improved. Through health risk identification and frequency modulation response space demarcation, cooperation of energy storage and thermal power generating units is realized, the regulation capability and long-term reliability of a power grid for dealing with fluctuating energy are enhanced, and the problem of response delay or efficiency in a traditional method is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of electric energy storage control, and particularly to a method and system for evaluating the frequency modulation ability of an energy storage thermal power unit. Background Art

[0002] The technical field of electric energy storage control includes various technologies related to the storage, scheduling, and management of electric energy in a power system. The core content of this field is to optimize the use efficiency of electric power through different energy storage devices to ensure the stability and reliability of the power grid. With the large-scale access of renewable energy, especially in the scheduling of energy sources with large fluctuations such as wind power and photovoltaic power, the electric energy storage control technology mainly covers aspects such as the storage, conversion, and scheduling of electric energy, involving the management methods of energy storage devices, the optimization schemes of energy storage technologies, and the coordination with traditional generating units (such as thermal power units, wind turbines, etc.). Through scientific and reasonable control methods, problems such as power grid load fluctuations and low energy utilization efficiency can be effectively solved, and the power regulation ability and flexibility can be improved.

[0003] Among them, the method for evaluating the frequency modulation ability of an energy storage thermal power unit refers to a technical method for evaluating the energy storage ability of a thermal power unit during the frequency modulation process. Aiming at the participation ability of a thermal power unit in power grid frequency modulation, especially the evaluation of the frequency modulation ability after the combination of energy storage technology and a thermal power unit, this method monitors and schedules the energy storage device of the thermal power unit, combines the operating state of the thermal power unit, evaluates its response ability and energy storage efficiency during the frequency regulation process, analyzes the coordinated operation of the thermal power unit and the energy storage in detail, evaluates its performance under different frequency regulation conditions, and proposes to optimize the relationship between energy storage and frequency modulation.

[0004] In the practical application of the existing electric energy storage control technology, there are problems of insufficiently rapid and accurate response to power grid frequency modulation. Especially when dealing with the coordination of energy storage and traditional thermal power units, it is difficult to achieve efficient response cooperation. For example, during the frequency modulation process of a thermal power unit, the use of the energy storage device is based on a preset load change pattern. However, due to the instantaneous and highly variable actual power grid load fluctuations, the traditional method cannot adjust the charge and discharge strategy of the energy storage system in a timely manner, resulting in a lag in frequency modulation response or inaccurate frequency regulation. The existing technology lacks real-time monitoring and diagnosis of the health state of the energy storage, and fails to effectively identify the potential risks of the energy storage unit during continuous operation, which easily leads to overcharge, overdischarge, or excessive loss of the energy storage system, affecting its long-term service life and efficiency. These problems make the traditional method face challenges of insufficient flexibility and delayed emergency response when dealing with the large-scale access of renewable energy, thus affecting power stability and regulation ability. Summary of the Invention

[0005] In order to solve the problem that the existing power energy storage control technology has a slow and inaccurate response to power grid frequency modulation in practical applications, especially when dealing with the coordination of energy storage and traditional thermal power units, it is difficult to achieve efficient response cooperation. For example, during the frequency modulation process of thermal power units, the use of energy storage devices is based on a preset load change pattern. However, due to the instantaneous and highly variable fluctuations of the actual power grid load, traditional methods cannot timely adjust the charge and discharge strategies of the energy storage system, resulting in a lag in frequency modulation response or inaccurate frequency regulation. The existing technology lacks real-time monitoring and diagnosis of the health status of energy storage, fails to effectively identify potential risks during the continuous operation of energy storage units, and is prone to overcharge, overdischarge, or excessive loss of the energy storage system, affecting its long-term service life and efficiency. This problem makes traditional methods face challenges of insufficient flexibility and delayed emergency response when dealing with the access of large-scale renewable energy, thus affecting power stability and regulation ability. The embodiments of the present invention provide a method and system for evaluating the frequency modulation ability of an energy storage thermal power unit. The technical solution is as follows: On the one hand, a method for evaluating the frequency modulation ability of an energy storage thermal power unit is provided, and the method includes: S1: Based on the operation data of the energy storage thermal power unit, including the power grid frequency value, the energy storage power value, the current charge and discharge state of the energy storage, and the change value of the thermal power load, call the edge node interface to merge and sort the operation data, identify the indicators of the corresponding nodes, and obtain multi-source state acquisition records; S2: According to the multi-source state acquisition records, screen the power fluctuation value of the energy storage unit and the adjustment frequency quantity of the edge control node, judge the power supply capacity coverage degree within the corresponding frequency response period, and obtain the energy storage frequency modulation matching metric value; S3: Call the energy storage frequency modulation matching metric value, compare it with the adjustment rate value of the thermal power load interface, identify the load coverage difference range within the same response period, judge the response matching degree, and obtain the frequency modulation resource coordination ratio; S4: According to the frequency modulation resource coordination ratio, extract the battery capacity change rate, the temperature rise rate, and the cycle frequency, compare the three values with thresholds, screen the low-adaptation state marked units, and output the health risk identification items.

[0006] As a further solution of the present invention, the multi-source state acquisition records include the power grid frequency, the energy storage power, the energy storage charge and discharge state, and the change of the thermal power load. The energy storage frequency modulation matching metric value includes the power fluctuation amplitude, the adjustment frequency, and the power supply capacity coverage degree. The frequency modulation resource coordination ratio includes the load coverage difference, the response matching degree, and the frequency modulation resource coordination ratio. The health risk identification items include the battery capacity change, the temperature rise rate, the cycle frequency, and their low-adaptation marks.

[0007] As a further solution of the present invention, the steps of the multi-source state acquisition records are specifically as follows: S101: Based on the operation data of the energy storage thermal power unit, the grid frequency value, the energy storage power value, the current charging and discharging state and the thermal power load change value are extracted, and the timestamp is processed uniformly. The corresponding data parameters are matched through the edge node interface node identification to generate a node parameter attribution value set; S102: calling the node parameter attribution value set, identifying and indexing the grid frequency and energy storage capacity, classifying them in combination with the charging and discharging status, dividing the intervals according to the thermal power load change, and constructing a classified state parameter sequence; S103: According to the classified state parameter sequence, the load interval is matched with the charge and discharge state, the parameter combination in the interval is extracted and the frequency is counted, the frequency threshold is used for screening, the unstable combination is eliminated, the state set with a repetition rate exceeding the set standard is retained, and the multi-source state acquisition record is obtained.

[0008] As a further solution of the present invention, the step of matching the energy storage frequency regulation metric value is specifically as follows: S201: Filtering the power change value of the energy storage unit and the number of adjustment actions of the corresponding edge control node according to the multi-source status collection record, summarizing them by time period, and generating energy storage fluctuation and adjustment statistics; S202: calling the energy storage fluctuation and regulation statistics, dividing the time period according to the frequency response cycle, determining the coverage of the power supply upper limit corresponding to the node regulation frequency by the power fluctuation value in each cycle, and obtaining the response cycle power supply coverage ratio; S203: Based on the response cycle power supply coverage ratio, the cycle coverage ratio and the cycle duration are processed into a unified dimension, the cycle difference value between the coverage ratio and the power supply coverage reference value is calculated, the cycle difference value is averaged, and an energy storage frequency regulation matching metric value is established; The period difference between the coverage ratio and the power supply coverage reference value is calculated using the formula: ; in, Represents the periodic difference between the coverage ratio and the power supply coverage reference value, represents the coverage ratio of the i-th period, represents the duration of the i-th cycle, represents the power supply coverage reference value of the i-th cycle, Represents the total number of cycles.

[0009] As a further solution of the present invention, the step of frequency modulation resource coordination ratio is specifically: S301: calling the energy storage frequency regulation matching metric value, unifying the cycle number matching section data according to the response cycle and regulation rate value in the thermal power load interface, calculating the difference between the energy storage frequency regulation value and the thermal power regulation rate value in each cycle, and summarizing the extreme values ​​in the cycle to obtain the load response difference interval; S302: Based on the load response difference interval, determine whether the energy storage frequency modulation value within each cycle section is within the response coincidence benchmark range set within the thermal power regulation rate change interval, and count the ratio between the number of coincidences and the total number of cycles to obtain the frequency modulation resource coordination ratio.

[0010] As a further solution of the present invention, the frequency modulation resource coordination ratio adopts the formula: ; wherein, represents the frequency modulation resource coordination ratio, represents the frequency change amount within the k-th cycle, represents the energy storage frequency modulation value within the k-th cycle, represents the maximum frequency change amount, represents the empirical adjustment coefficient, represents the total number of cycles.

[0011] As a further solution of the present invention, the steps of the health risk identification items are specifically as follows: S401: According to the frequency modulation resource coordination ratio, extract the battery capacity change value and time series of the energy storage unit, calculate the difference rate between adjacent time periods and perform normalization processing to generate an energy storage capacity change rate value set; S402: Invoke the energy storage capacity change rate value set, extract the temperature series and the number of charge and discharge times within the cycle of the corresponding unit, calculate the temperature change amplitude and the average frequency, and generate the temperature rise and cycle rate; S403: Based on the temperature rise and cycle rate, respectively compare the battery capacity change rate, temperature rise rate, and cycle frequency with the set performance thresholds, screen out the units where all three indicators are lower than the threshold lower limit, and attach an abnormal status mark to obtain the health risk identification items.

[0012] As a further solution of the present invention, the method further includes step S5: S5: Invoke the health risk identification items, delimit the effective frequency modulation response space of the energy storage and thermal power in the current cycle according to the weight distribution situation within the continuous frequency modulation cycles, and output an overview of the frequency modulation ability evaluation interval; The overview of the frequency modulation ability evaluation interval includes the energy storage frequency modulation response space, the thermal power frequency modulation response space, and the effective interval of the frequency modulation ability.

[0013] As a further solution of the present invention, the steps of the overview of the frequency modulation ability evaluation interval are specifically as follows: S501: Invoke the health risk identification items, extract the response amplitude and duration of the energy storage and thermal power of the marked units within the continuous frequency modulation cycles, perform weighted processing according to the frequency, and generate a cycle response weight group; S502: According to the periodic response weight group, normalize the weighted data of energy storage and thermal power, screen the continuous output segments, and obtain the effective response intervals; S503: Based on the effective response intervals, conduct combined analysis on the section boundaries of energy storage and thermal power, divide the grade sections according to the periodic index, extract the upper and lower response limits within each section, and obtain an overview of the frequency regulation capacity evaluation intervals.

[0014] A frequency regulation capacity evaluation system for energy storage and thermal power units, the system includes: The data merging module classifies nodes for the grid frequency, energy storage power, energy storage charge and discharge status, and thermal power load change values based on the operation data of energy storage and thermal power units, divides the frequency fluctuations within the same period into intervals, integrates the data by time period, and generates frequency modulation input correlation records; The response analysis module extracts the periodic energy storage power fluctuations and the control node adjustment frequencies based on the frequency modulation input correlation records, calculates the ratio of the adjustment amplitude to the frequency change rate, classifies them in combination with the frequency distribution weights, identifies the participation of the energy storage unit in frequency regulation, and establishes an energy storage frequency response portrait; The load comparison module extracts the thermal power adjustment rate data based on the energy storage frequency response portrait, calculates the difference with the energy storage unit response intensity value, extracts the difference sections and determines the compensation trend according to the difference distribution, and outputs a load action coordination relationship diagram; The status identification module calls the energy storage unit capacity change rate, temperature rise rate, and cycle frequency based on the load action coordination relationship diagram, determines whether they exceed the limits, marks the over-limit units, and obtains an abnormal adaptation unit index table according to the coincidence frequency screening results of the marked units and the difference sections; The capacity evaluation module extracts the action time periods and output levels during continuous frequency modulation periods based on the abnormal adaptation unit index table, conducts section matching in combination with the thermal power response curve, analyzes the overlap of the output trajectories of the two types of resources, identifies the joint coverage intervals of the dual regulation capabilities, and generates a frequency modulation resource collaborative capacity zoning map.

[0015] The beneficial effects brought by the technical solutions provided in the embodiments of the present invention at least include: By integrating and identifying the operation data of energy storage thermal power units, the adaptability and response efficiency of power grid frequency modulation can be comprehensively improved. Through real-time monitoring of key data such as power fluctuations, energy storage status, and load changes, and precise analysis of the adaptability measurement values of frequency response, the capabilities and contributions of energy storage systems under different frequency modulation conditions can be measured more accurately, the response cycle of energy storage units can be optimized, and their stability during the power grid frequency modulation process can be ensured. Through comprehensive monitoring of battery capacity, temperature rise rate, and cycle frequency, the health status can be identified in a timely manner, avoiding load overload or efficiency decline of energy storage devices, thereby ensuring the stable dispatching of the entire power grid. Based on the identification of health risks and the delineation of the frequency modulation response space, the optimal coordination of energy storage and thermal power units can be achieved, the frequency modulation capacity can be enhanced, and thus the emergency regulation capacity of the power grid in the face of fluctuating energy sources and the reliability of long-term operation can be improved. The processing logic not only improves the energy storage efficiency but also enhances the flexibility of frequency modulation resources through multi-dimensional real-time monitoring, avoiding problems such as response lag or efficiency decline in traditional methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a schematic diagram of the working process of the present invention; Figure 2 is a detailed flowchart of S1 of the present invention; Figure 3 is a detailed flowchart of S2 of the present invention; Figure 4 is a detailed flowchart of S3 of the present invention; Figure 5 is a detailed flowchart of S4 of the present invention; Figure 6 is a detailed flowchart of S5 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] The following describes the technical solutions in the present invention with reference to the accompanying drawings.

[0018] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to represent examples, illustrations, or explanations. Any embodiment or design solution described as "example" in the present invention should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly speaking, the use of the word "example" is intended to present concepts in a specific manner. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one of the two can be selected.

[0019] In the embodiments of the present invention, the terms "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, their intended meanings are the same. The terms "of", "corresponding", and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, their intended meanings are the same.

[0020] In the embodiments of the present invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference between them is not emphasized, their intended meanings are the same.

[0021] To make the technical problems, technical solutions, and advantages to be solved by the present invention clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments.

[0022] Please refer to Figure 1 , embodiments of the present invention provide a method for evaluating the frequency regulation ability of an energy storage thermal power unit. The processing flow of this method may include the following steps: S1: Based on the operation data of the energy storage thermal power unit, including grid frequency value, energy storage power value, current charge and discharge state of the energy storage, and thermal power load change value, call the edge node interface to merge and organize the operation data, identify the indicators of the corresponding nodes, and obtain multi-source state acquisition records; S2: According to the multi-source state acquisition records, screen the power fluctuation value of the energy storage unit and the adjustment frequency of the edge control node, judge the power supply capacity coverage degree within the corresponding frequency response period, and obtain the energy storage frequency regulation matching metric value; S3: Call the energy storage frequency regulation matching metric value, compare it with the adjustment rate value of the thermal power load interface, identify the load coverage difference range within the same response period, judge the response matching degree, and obtain the frequency regulation resource coordination ratio; S4: According to the frequency regulation resource coordination ratio, extract the battery capacity change rate, temperature rise rate, and cycle frequency, compare the three values with thresholds, screen the low-adaptation state marked units, and output the health risk identification items; S5: Call the health risk identification items, and delimit the effective frequency regulation response space of the energy storage and thermal power in the current period according to the weight distribution in the continuous frequency regulation period, and output an overview of the frequency regulation ability evaluation interval.

[0023] The multi-source status acquisition records include grid frequency, energy storage power, energy storage charge and discharge status, and thermal power load changes. The energy storage frequency modulation matching metrics include the amplitude of power fluctuation, regulation frequency, and power supply capacity coverage. The frequency modulation resource coordination ratio includes the load coverage difference, response matching degree, and frequency modulation resource coordination ratio. The health risk identification items include battery capacity change, temperature rise rate, cycle frequency, and their low adaptation marks. The overview of the frequency modulation ability evaluation interval includes the energy storage frequency modulation response space, thermal power frequency modulation response space, and effective interval of frequency modulation ability.

[0024] Specifically, as Figure 2 shown, the steps of multi-source status acquisition records are specifically as follows: S101: Based on the operation data of the energy storage thermal power unit, extract the grid frequency value, energy storage power value, current charge and discharge status, and thermal power load change value, uniformly process them according to the time stamp, match the node identification through the edge node interface to identify the corresponding data parameters, and generate the node parameter attribution value set; When extracting the grid frequency, energy storage power, charge and discharge status, and thermal power load change value, first extract the parameters from the operation data of the energy storage thermal power unit. The data extraction process needs to be uniformly processed through the time stamp to ensure the accuracy and consistency of the data. The grid frequency is a key parameter for power stability and is obtained through real-time monitoring equipment. The energy storage power value reflects the current storage capacity of the battery. The charge and discharge status is calibrated according to the working state of the battery (charging or discharging). The thermal power load change value refers to the change in the output power of the thermal power unit and is recorded in real time through the load monitoring device. Through the integration of data, it can provide the necessary basis for subsequent data analysis and model construction. The data interface and edge node are used to integrate the data. The node interface matching function can ensure that the data is accurately allocated according to different sensors and devices. Through real-time acquisition and transmission, the node parameter attribution value set is generated to prepare the data for subsequent analysis and processing.

[0025] S102: Call the node parameter attribution value set, identify and index the grid frequency and energy storage power, classify them in combination with the charge and discharge status, divide the intervals according to the thermal power load change, and construct the classified status parameter sequence; Identify relevant data on grid frequency and energy storage power. The grid frequency value is obtained from real-time power monitoring. By analyzing the frequency data, the stability of the grid can be judged and combined with the energy storage power data. The energy storage power value can reflect the change in the charging or discharging state of the battery. By classifying these two parameters, for example, when the grid frequency fluctuates greatly, the energy storage power will show rapid charge and discharge changes, which can be used as an important classification basis. By analyzing the charge and discharge state, the working state of the battery can be further subdivided. Classification can be further distinguished according to different intervals of thermal power load changes. The division of the thermal power load change interval needs to be set according to historical data. Through comprehensive analysis of the classification, a classified state parameter sequence can be obtained, providing data support for subsequent state prediction.

[0026] S103: According to the classified state parameter sequence, correspond the load interval with the charge and discharge state, extract the parameter combinations within the interval and count the frequency, use the frequency threshold for screening, eliminate unstable combinations, retain the state set with a repetition rate exceeding the set standard, and obtain multi-source state acquisition records; Correspond the load interval with the charge and discharge state. The division of the load interval is carried out by analyzing the thermal power load data. According to the distribution of historical load changes, the load interval is divided into multiple levels or intervals. The division of the interval needs to be set according to the actual fluctuation range of the grid load and combined with the charge and discharge capacity of the battery. For example, when the set load fluctuation is within the interval of ±5%, it is a stable state of the grid, while when the fluctuation exceeds ±10%, it is an unstable state of the grid. At this time, the change in the energy storage power will directly affect the stability of the grid. Combine the parameter combinations within the interval and conduct statistics. Through frequency statistics, find out the frequencies of the state combinations appearing in different intervals. When screening, set a frequency threshold. If the frequency of a certain parameter combination is lower than the set threshold, it is regarded as an unstable combination and eliminated. The setting of the threshold should be adjusted according to the actual data. The purpose of setting the threshold is to eliminate extreme abnormal situations and retain the state combinations that appear more frequently in actual applications. Through this method of frequency threshold screening, the stable states that have a greater impact on the grid frequency and energy storage power can be accurately identified, and multi-source state acquisition records can be obtained.

[0027] Specifically, as Figure 3 shown, the steps of the energy storage frequency modulation matching metric are specifically as follows: S201: According to the multi-source state acquisition records, screen the change value of the energy storage unit's power and the number of adjustment actions of the affiliated edge control node, summarize by time period, and generate the energy storage fluctuation and adjustment statistical value; Extract the power change value of the energy storage unit from the multi-source status acquisition records. The power change value can be obtained from the monitoring data of the energy storage, which is the amount of power change during battery charging or discharging. Each time the battery charges or discharges, the value of the increase or decrease in power is recorded. Extract the number of adjustment actions of the control node from the same record. The number of adjustment actions refers to the number of adjustment operations performed by the control node to maintain stability, including actions such as charging, discharging, and adjusting current. The number of actions reflects the frequency of the adjustment process. When summarizing the data, it is necessary to summarize by time period. For example, the data can be segmented by hour or day, and the change range of the energy storage unit's power and the number of adjustment actions within each time period are statistically calculated. The data can be summarized using the weighted average or simple summation method. For example, for a power change of +100 kWh within a certain hour and 5 adjustment action times, after summarizing by time period, the energy storage fluctuation and adjustment statistical value is obtained.

[0028] S202: Invoke the energy storage fluctuation and adjustment statistical value, divide the time period according to the frequency response period, judge the coverage of the power fluctuation value within each period on the corresponding power supply upper limit of the node adjustment frequency, and obtain the power supply coverage ratio of the response period; Divide the time period according to the frequency response period. The frequency response period is set according to the load change law of the power grid. For example, set every 30 minutes as a response period to analyze the load fluctuation of the power grid during this period, and judge the coverage of the power fluctuation value on the power supply upper limit through the relationship between the power fluctuation value and the node adjustment frequency within this period. First, calculate the power fluctuation value within each period. The power fluctuation value can be obtained by statistically calculating the maximum change amount of power within the statistical period. For example, if the power changes from 50 kWh to 30 kWh within a certain period, the power fluctuation is 20 kWh. Correspondingly, calculate the adjustment frequency of the node within this period. If the number of adjustment actions within this period is 4 times, it can be considered that the adjustment frequency within this period is 4 times. Compare the data with the power supply upper limit. The power supply upper limit refers to the maximum power supply capacity that the power grid can provide within this response period, which is determined according to the maximum power supply capacity value of the power grid. For example, set the maximum power supply capacity to 200 kW, analyze the relationship between the power fluctuation value and the adjustment frequency within this period, and thus obtain the power supply coverage ratio of the response period.

[0029] S203: Based on the power supply coverage ratio of the response period, perform a unified dimension processing on the period coverage ratio and the period duration, calculate the period difference value between the coverage ratio and the power supply coverage reference value, extract the mean value of the period difference value, and establish the energy storage frequency modulation matching metric value; The period difference value between the coverage ratio and the power supply coverage reference value adopts the formula: ; Among them, represents the period difference value between the coverage ratio and the power supply coverage reference value, represents the coverage ratio of the i-th cycle, represents the duration of the i-th cycle, represents the power supply coverage reference value of the i-th cycle, represents the total number of cycles; (Cycle difference value) This parameter represents the cycle difference value, which is used to reflect the difference between the power supply coverage of each cycle and the reference value. It is obtained by calculating the difference of each cycle and taking the average value; (Coverage ratio of the i-th cycle) This parameter is the coverage ratio of the i-th cycle, which represents the ratio of the actual power supply coverage ability to the expected power supply coverage ability within this cycle. This parameter is obtained from actual monitoring data. By the power grid management system, the ratio of actual power supply and demand within each cycle is obtained. For example, within a certain cycle, the actual power supply of the power grid is 800kW, and the expected power supply of this cycle is 1000kW, then the coverage ratio of this cycle is: ; (Duration of the i-th cycle) This parameter represents the duration of the i-th cycle, which is recorded in real time by the dispatching system according to the operation plan of the power grid. For example, assume the duration of a certain cycle is 5 hours, and it is recorded as: ; (Power supply coverage reference value of the i-th cycle) This parameter is a preset power supply coverage reference value, which is used to compare with the actual power supply coverage ratio. This reference value is set according to historical data or power grid management standards. For example, the set power supply coverage reference value is 0.85, that is: ; Suppose there are 3 cycles, , according to the actual monitoring data, the following information can be obtained: The 1st cycle: , hours, ; The 2nd cycle: , hours, ; The 3rd cycle: , hours, ; Substitute into the formula to calculate the difference value of each cycle: For the 1st cycle: ; For the 2nd cycle: ; For the 3rd cycle: ; Calculate the average value of the cycle difference value: ; The result shows that the cycle difference value is 0.6828, which reflects the average difference degree between the power supply coverage ratio and the power supply coverage reference value within all cycles; Supplement and improve the acquisition process of each parameter and the process of dimension unification: (Coverage ratio of the i-th cycle): The coverage ratio is determined by the ratio between the actual power supply capacity and the expected power supply capacity of the power grid, collected in real time through the power monitoring system, and quantified by comparing the power demand and power supply monitored in each cycle; (Duration of the i-th cycle): The duration is recorded through the power grid dispatching system, and the duration of each cycle is accurately obtained through timestamps, with the unit of hour; (Power supply coverage reference value of the i-th cycle): The reference value is determined by power grid management standards, historical data analysis or optimization calculation, and adjusted according to the demand changes in different regions and time periods. The reference value needs to be combined with historical operation data and dynamically adjusted to meet the requirements of power grid operation; All parameters in the formula need to maintain a unified unit. Especially for the calculation of the coverage ratio and the duration, the coverage ratio is a dimensionless quantity, the duration unit is hour, the reference value is a dimensionless quantity, and the result of the cycle difference value is a dimensionless quantity.

[0030] Specifically, as Figure 4 shown, the steps of the frequency modulation resource coordination ratio are specifically as follows: S301: Invoke the energy storage frequency modulation matching metric value, unify the cycle number matching section data according to the response cycle and regulation rate value in the thermal power load interface, calculate the difference between the energy storage frequency modulation value and the thermal power regulation rate value in each cycle, and summarize the extreme values within the cycle to obtain the load response difference interval; First, number the response cycles and match the corresponding section data. Within each cycle, calculate the difference between the energy storage frequency modulation value and the thermal power regulation rate value. By comparing the frequency modulation value and the regulation rate value cycle by cycle, obtain the difference between the two. At this time, it is necessary to clarify the range of the frequency modulation value and the regulation rate value. For example, the frequency modulation value represents the rate of energy regulation, with the unit of kilowatt (kW), and the regulation rate value refers to the change speed of the regulation ability, with the unit of kilowatt per hour (kW / h). The difference is calculated through simple subtraction. For example, at a certain time period, the energy storage frequency modulation value is 100 kW, while the thermal power regulation rate value is 80 kW / h, then the difference is 20 kW / h. Summarize the extreme values of each cycle to obtain the maximum difference or the minimum difference within the cycle, thereby obtaining the load response difference interval. Through the difference calculation and extreme value extraction cycle by cycle, this can provide a basis for the next judgment of the coincidence reference range, accurately extract the difference data between the energy storage frequency modulation and the thermal power load response, and thus provide accurate basic data support for the subsequent collaborative frequency modulation resource analysis.

[0031] S302: Based on the load response difference interval, determine whether the energy storage frequency modulation value within each cycle section is within the response coincidence reference range set within the thermal power regulation rate change interval, and count the ratio between the number of coincidences and the total number of cycles to obtain the frequency modulation resource coordination ratio; The frequency modulation resource coordination ratio adopts the formula: ; Wherein, represents the frequency modulation resource coordination ratio, represents the frequency change amount within the k-th cycle, represents the energy storage frequency modulation value within the k-th cycle, represents the maximum frequency change amount, represents the empirical adjustment coefficient, represents the total number of cycles; : The frequency modulation resource coordination ratio represents the coincidence degree between the energy storage frequency modulation value and the frequency change within each cycle segment, and its unit is percentage; : The frequency change amount within the k-th cycle, with the unit of Hz. This parameter is obtained in real time through a frequency monitoring device and is obtained by comparing the maximum frequency value and the minimum frequency value within the cycle at the end of each cycle; : The energy storage frequency modulation value within the k-th cycle, with the unit of MW. This value reflects the power change of the energy storage within this cycle and is calculated through the energy storage dispatching system based on the charge and discharge amount of the energy storage device and the frequency modulation response; : Maximum frequency change, in Hz. This value is the maximum of the frequency changes in all cycles and is calculated by the frequency monitoring device based on the historical data of the entire cycle. : Adjustment coefficient, dimensionless. This coefficient is an empirical value set according to the grid load response characteristics, set between 0.2 and 0.5. In some cases, this coefficient will be dynamically adjusted according to the load fluctuation frequency range of the system. : Total number of cycles. This value is the total number of cycles in the data acquisition process and is determined by the data cycle length within the collected time period. Parameter acquisition process and dimension unification: (Frequency change): Calculated in real time through the power grid monitoring system. The frequency change value in each cycle is obtained by comparing the frequency sensor with the dispatching system. The determination of the monitored frequency value and the sampling period requires unified dimensions, accurate to two decimal places in Hz. (Energy storage frequency regulation value): This value is calculated in real time through the control system of the energy storage power station and automatically recorded. The frequency regulation value needs to be unified under the dimensions of power output (MW) and power change (MW). This value is calculated by the frequency regulation command collected in real time by the energy storage and the actual power change. (Maximum frequency change): Obtained by calculating the historical cycle data. Select the maximum frequency change value within a time period. For example, within a certain cycle, the frequency fluctuates from 49.8 Hz to 50.2 Hz, then the maximum frequency change is 0.4 Hz. (Adjustment coefficient): Obtained by experimenting on the grid regulation characteristics or analyzing historical data. The adjustment coefficient fluctuates with the fluctuation range of the load response and is generally set according to the grid stability and system response speed. Suppose there are the following monitoring data: Total number of cycles: ; Frequency change: Hz, Hz, Hz, Hz, Hz; Energy storage frequency regulation value: MW, MW, MW, MW, MW; Maximum frequency change: Hz; Adjustment coefficient: ; Substitute into the formula: ; Calculate each term: For the 1st cycle: ; For the 2nd cycle: ; For the 3rd cycle: ; For the 4th cycle: ; For the 5th cycle: ; Sum up all the results: ; This result indicates that the coordinated frequency modulation resource ratio is 28.45%, that is, within 5 cycles, the coincidence degree between energy storage frequency modulation and frequency change is 28.45%, reflecting the effectiveness of frequency change on the response of the energy storage frequency modulation system.

[0032] Specifically, as Figure 5 shown, the steps of the health risk identification items are specifically as follows: S401: According to the coordinated frequency modulation resource ratio, extract the battery capacity change value and time series of the energy storage unit, calculate the difference rate between adjacent time periods and perform normalization processing to generate a set of energy storage capacity change rate values; Extract the battery capacity change value and time series of the energy storage unit. The extraction process involves obtaining the historical data of the battery capacity from the energy storage management. The data is the total battery capacity recorded at regular intervals (such as every hour or daily), which reflects the charge and discharge conditions of the battery over a period of time. Calculate the difference rate of the battery capacity between adjacent time periods. The calculation method of the difference rate is to subtract the capacity of the previous time period from the capacity of the current time period, and then divide by the capacity of the previous time period to obtain a percentage representing the capacity change. This percentage can indicate the capacity loss or increase of the battery during that time period. Next, perform normalization processing. Normalization is to convert the difference rate value to a standard range, which is between 0 and 1, so that data at different times can be fairly compared. Finally, generate a set of energy storage capacity change rate values, which provides a standardized battery performance index for subsequent analysis.

[0033] S402: Call the set of energy storage capacity change rate values, extract the temperature series and the number of charge and discharge times within the cycle of the corresponding unit, calculate the temperature change amplitude and the average frequency, and generate the temperature rise and cycle rate; Extract the temperature sequence of the corresponding unit and the number of charge and discharge cycles within a period. The temperature sequence is obtained by real-time recording through the temperature sensors in the energy storage, while the number of charge and discharge cycles is the number of charging and discharging activities recorded by the battery management within each period. Calculate the temperature change amplitude, which involves the difference between the highest and lowest temperature values recorded within the period. This temperature difference can reflect the thermal stability of the battery during operation. Calculate the average values of the temperature change and the number of charge and discharge cycles. The calculation of the average value can provide an overall assessment of the temperature rise and the battery usage frequency within each period, thereby generating the temperature rise and the cycle rate. These two indicators help to understand the thermal management efficiency and usage intensity of the battery during actual operation.

[0034] S403: Based on the temperature rise and the cycle rate, compare the battery capacity change rate, the temperature rise rate, and the cycle frequency with the set performance thresholds respectively. Screen out the units where all three indicators are lower than the lower limit of the threshold, and attach an abnormal status mark to obtain the health risk identification items. After analyzing the temperature rise and the cycle rate, compare the battery capacity change rate, the temperature rise rate, and the cycle frequency with the set performance thresholds. The thresholds are preset based on the battery performance requirements and safety standards. The comparison helps to identify which battery units have performance lower than the expected level. The screening process involves checking whether all three indicators are simultaneously lower than the lower limit of their corresponding thresholds. If all the indicators of a unit are lower than the threshold, it indicates that the unit has health or performance problems, and the unit will be attached with an abnormal status mark. This mark helps with subsequent maintenance decisions. Through this process, obtain the health risk identification items. The identification items are a kind of early warning for the future operation risks of the battery units.

[0035] Specifically, as Figure 6 shown, the steps of the overview of the frequency modulation ability evaluation interval are specifically as follows: S501: Call the health risk identification items, extract the response amplitude and duration of the energy storage and thermal power of the marked units within the continuous frequency modulation period, and perform weighted processing according to the frequency to generate the cycle response weight group. Extract marker unit data from the health risk identification items. This involves obtaining data from energy storage units where potential problems have been identified, including the response amplitude and duration within consecutive frequency modulation cycles. The response amplitude is represented by the amount of electrical energy response of the energy storage unit to a frequency regulation request within a specific cycle, and the duration refers to the length of time the energy storage unit can maintain a stable output of electrical energy in the demand response state. The data needs to be weighted according to the frequency of occurrence. The purpose of the weighting process is to more accurately reflect the importance of frequent and critical responses. The weights are calculated based on the number of responses and the effective duration within the cycle. Through this weighting method, data with a single large-amplitude response but a low frequency can be effectively balanced with frequent but smaller-amplitude responses, ultimately generating a cycle response weight group that comprehensively reflects the response performance of the energy storage unit. This weight group helps operators understand which units perform better in frequent frequency modulation activities.

[0036] S502: According to the cycle response weight group, perform normalization processing on the weighted data of energy storage and thermal power, screen the continuous output segments, and obtain the effective response interval. Perform normalization processing on the data of energy storage and thermal power. Normalization processing eliminates the scale differences between different data sets by converting the data to the same ratio or range, making the data of energy storage and thermal power units from different sources or different technologies comparable. The normalized data can more fairly reflect the performance of each unit. Subsequently, screen the continuous output segments. The continuous output segments refer to those time periods that always maintain a stable output within consecutive frequency modulation cycles. The screening is determined by setting thresholds. For example, set the time period with a continuous output not lower than a certain set value as the effective response interval, which reflects the stability and response ability in the face of continuous demand.

[0037] S503: Based on the effective response interval, perform combined analysis on the section boundaries of energy storage and thermal power, divide the grade segments according to the cycle index, extract the upper and lower response limits within each segment, and obtain an overview of the frequency modulation ability evaluation interval. Based on the effective response interval, perform combined analysis on the section boundaries of energy storage and thermal power. The analysis involves comparing and classifying the performance of different energy storage and thermal power units within the cycle. By dividing the grade segments according to the cycle index, the performance of the units can be evaluated and classified. The division of the grade segments is based on multiple dimensions such as the rapidity, persistence, and stability of the response. The upper and lower response limits within each segment are the high and low standards of the unit performance in the grade. The limits are set based on the statistical data of the performance and the expected operating standards, thereby obtaining an overview of the frequency modulation ability evaluation interval. This overview provides operators with a clear view to identify the status and role of each unit in the overall frequency modulation strategy and its potential upgrade or optimization requirements.

[0038] Energy storage and thermal power unit frequency modulation ability evaluation system, the system includes: Based on the operation data of the energy storage thermal power unit, the data merging module classifies nodes for grid frequency, energy storage power, energy storage charge and discharge state, and the change value of thermal power load, divides the frequency fluctuations within the same period into intervals, integrates the data by time period, and generates a frequency modulation input correlation record; Based on the frequency modulation input correlation record, the response analysis module extracts the energy storage power fluctuation and the control node adjustment frequency within the period, calculates the ratio of the adjustment amplitude to the frequency change rate, classifies them in combination with the frequency distribution weight, identifies the participation of the energy storage unit in frequency modulation, and establishes an energy storage frequency response portrait; Based on the energy storage frequency response portrait, the load comparison module extracts the thermal power adjustment rate data, calculates the difference with the energy storage unit response intensity value, extracts the difference section, determines the compensation trend according to the difference distribution, and outputs a load effect coordination relationship diagram; Based on the load effect coordination relationship diagram, the state identification module calls the energy storage unit capacity change rate, temperature rise rate and cycle frequency, determines whether they exceed the limit values, marks the over-limit units, and obtains an abnormal adaptation unit index table according to the coincidence frequency screening result of the marked units and the difference section; Based on the abnormal adaptation unit index table, the capacity evaluation module extracts the action time period and output level within the continuous frequency modulation period, performs section matching in combination with the thermal power response curve, analyzes the overlap of the output trajectories of the two types of resources, identifies the joint coverage interval of the dual regulation capacity, and generates a frequency modulation resource coordination capacity zoning map.

[0039] The above is only the specific implementation manner 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 can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for evaluating the frequency regulation capability of a thermal power unit with energy storage, characterized in that: The following steps are involved: S1: Based on the operation data of the energy storage thermal power unit, including the grid frequency value, energy storage power value, current energy storage charge and discharge status, and thermal power load change value, the edge node interface is called to merge and organize the operation data, identify the indicators of the corresponding nodes, and obtain multi-source status collection records; S2: According to the multi-source status collection record, the power fluctuation value of the energy storage unit and the adjustment frequency of the edge control node are screened, the power supply capacity coverage within the corresponding frequency response period is determined, and the energy storage frequency regulation matching measurement value is obtained; S3: calling the energy storage frequency regulation matching metric value, comparing it with the regulation rate value of the thermal power load interface, identifying the load coverage difference range within the same response cycle, determining the response matching degree, and obtaining the frequency regulation resource coordination ratio; S4: According to the frequency modulation resource coordination ratio, the battery capacity change rate, the temperature rise rate and the cycle frequency are extracted, the thresholds of the three values ​​are compared, the low adaptation state marking unit is filtered, and the health risk identification item is output.

2. The method for evaluating the frequency regulation capability of an energy storage thermal power unit according to claim 1, characterized in that: The multi-source status collection record includes grid frequency, energy storage power, energy storage charging and discharging status, and thermal power load changes. The energy storage frequency regulation matching measurement value includes power fluctuation amplitude, adjustment frequency, and power supply capacity coverage. The frequency regulation resource coordination ratio includes load coverage difference, response matching degree, and frequency regulation resource coordination ratio. The health risk identification items include battery capacity changes, temperature rise rate, cycle frequency, and its low adaptation mark.

3. The method for evaluating the frequency regulation capability of an energy storage thermal power unit according to claim 1, characterized in that: The steps of multi-source status collection and recording are specifically as follows: S101: Based on the operation data of the energy storage thermal power unit, the grid frequency value, the energy storage power value, the current charging and discharging state and the thermal power load change value are extracted, and the timestamp is processed uniformly. The corresponding data parameters are matched through the edge node interface node identification to generate a node parameter attribution value set; S102: calling the node parameter attribution value set, identifying and indexing the grid frequency and energy storage capacity, classifying them in combination with the charging and discharging status, dividing the intervals according to the thermal power load change, and constructing a classified state parameter sequence; S103: According to the classified state parameter sequence, the load interval is matched with the charge and discharge state, the parameter combination in the interval is extracted and the frequency is counted, the frequency threshold is used for screening, the unstable combination is eliminated, the state set with a repetition rate exceeding the set standard is retained, and the multi-source state acquisition record is obtained.

4. The method for evaluating the frequency regulation capability of an energy storage thermal power unit according to claim 3, characterized in that: The steps of energy storage frequency modulation matching metric value are specifically as follows: S201: Filtering the power change value of the energy storage unit and the number of adjustment actions of the corresponding edge control node according to the multi-source status collection record, summarizing them by time period, and generating energy storage fluctuation and adjustment statistics; S202: calling the energy storage fluctuation and regulation statistics, dividing the time period according to the frequency response cycle, determining the coverage of the power supply upper limit corresponding to the node regulation frequency by the power fluctuation value in each cycle, and obtaining the response cycle power supply coverage ratio; S203: Based on the response cycle power supply coverage ratio, the cycle coverage ratio and the cycle duration are uniformly dimensioned, the cycle difference value between the coverage ratio and the power supply coverage reference value is calculated, the cycle difference value is averaged, and the energy storage frequency regulation matching metric value is established.

5. The method for evaluating the frequency regulation capability of an energy storage thermal power unit according to claim 4, characterized in that: The period difference between the coverage ratio and the power supply coverage reference value is calculated using the formula: ； in, Represents the periodic difference between the coverage ratio and the power supply coverage reference value, represents the coverage ratio of the i-th period, represents the duration of the i-th cycle, represents the power supply coverage reference value of the i-th cycle, Represents the total number of cycles.

6. The method for evaluating the frequency regulation capability of an energy storage thermal power unit according to claim 4, characterized in that: The steps of frequency modulation resource coordination ratio are specifically as follows: S301: calling the energy storage frequency regulation matching metric value, unifying the cycle number matching section data according to the response cycle and regulation rate value in the thermal power load interface, calculating the difference between the energy storage frequency regulation value and the thermal power regulation rate value in each cycle, and summarizing the extreme values ​​in the cycle to obtain the load response difference interval; S302: Based on the load response difference interval, determine whether the energy storage frequency regulation value in each cycle segment is within the response overlap reference range set in the thermal power regulation rate change interval, count the ratio between the number of overlaps and the total number of cycles, and obtain the frequency regulation resource coordination ratio; The frequency modulation resource coordination ratio adopts the formula: ； in, represents the frequency modulation resource coordination ratio, represents the frequency change in the kth cycle, represents the energy storage frequency modulation value in the kth cycle, Represents the maximum frequency change, represents the experience adjustment coefficient, Represents the total number of cycles.

7. The method for evaluating the frequency regulation capability of an energy storage thermal power unit according to claim 6, characterized in that: The steps of health risk identification are as follows: S401: extracting the battery capacity change value and time series of the energy storage unit according to the frequency modulation resource coordination ratio, calculating the difference rate between adjacent time periods and performing normalization processing, and generating an energy storage capacity change rate value set; S402: calling the energy storage capacity change rate value set, extracting the temperature sequence of the corresponding unit and the number of charge and discharge times in the cycle, calculating the temperature change amplitude and the average frequency, and generating the temperature rise and cycle rate; S403: Based on the temperature rise and cycle rate, the battery capacity change rate, temperature rise rate and cycle frequency are compared with the set performance thresholds respectively, and the cells with all three indicators lower than the lower threshold are screened, and abnormal status marks are added to obtain health risk identification items.

8. The method for evaluating the frequency regulation capability of an energy storage thermal power unit according to claim 1, characterized in that: The method further comprises step S5: S5: calling the health risk identification item, delineating the effective frequency regulation response space of energy storage and thermal power in the current cycle according to the weight distribution in the continuous frequency regulation cycle, and outputting an overview of the frequency regulation capability assessment interval; The frequency regulation capability evaluation interval overview includes energy storage frequency regulation response space, thermal power frequency regulation response space, and frequency regulation capability effective interval.

9. The method for evaluating the frequency regulation capability of an energy storage thermal power unit according to claim 8, characterized in that: The steps of the frequency modulation capability evaluation interval overview are as follows: S501: calling the health risk identification item, extracting the response amplitude and duration of the energy storage and thermal power of the marked unit in the continuous frequency modulation cycle, weighting them according to the frequency, and generating a cycle response weight group; S502: normalizing the weighted data of energy storage and thermal power according to the periodic response weight group, screening the continuous output section, and obtaining the effective response interval; S503: Based on the effective response interval, a combined analysis is performed on the section boundaries of energy storage and thermal power, the level segments are divided according to the cycle index, the upper and lower response limits within each segment are extracted, and an overview of the frequency regulation capability evaluation interval is obtained.

10. The frequency regulation capability evaluation system of energy storage thermal power units is characterized by: The system is used to implement the method for evaluating the frequency regulation capability of an energy storage thermal power unit according to any one of claims 1 to 9, and the system comprises: The data merging module classifies nodes of grid frequency, energy storage capacity, energy storage charging and discharging status, and thermal power load change values ​​based on the operating data of energy storage thermal power units, divides frequency fluctuations within the same period into intervals, integrates data by time period, and generates frequency modulation input association records; The response analysis module extracts the periodic energy storage power fluctuation and the control node adjustment frequency based on the frequency modulation input association record, calculates the ratio of the adjustment amplitude to the frequency change rate, classifies according to the frequency distribution weight, identifies the energy storage unit frequency modulation participation, and establishes an energy storage frequency response portrait; The load comparison module extracts the thermal power regulation rate data based on the energy storage frequency response portrait, calculates the difference with the energy storage unit response intensity value, extracts the difference section and determines the compensation trend according to the difference distribution, and outputs the load action coordination relationship diagram; The state recognition module calls the capacity change rate, temperature rise rate and cycle frequency of the energy storage unit based on the load action coordination relationship diagram to determine whether the limit is exceeded, and marks the over-limit unit, and obtains the abnormal adaptation unit index table according to the overlap frequency of the marked unit and the difference section; Based on the abnormal adaptation unit index table, the capacity assessment module extracts the action period and output level within the continuous frequency regulation cycle, performs segment matching in combination with the thermal power response curve, analyzes the overlap of the output trajectories of the two types of resources, identifies the joint coverage interval of the dual regulation capabilities, and generates a frequency regulation resource coordination capability zoning map.

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