A control method for an energy storage device for power system load balancing

Abstract

The present invention discloses a control method for an energy storage device for load balancing in a power system, which relates to the field of automatic control of power systems and includes: obtaining the total load, constructing a control platform, based on the total load, through dynamic time period division, forming fluctuation types, screening the fluctuating load, based on the total load, the fluctuating load and the fluctuating load, calculating the fluctuating load weight, the maximum load power line and the warning load power line, obtaining the total generated power in the power system, and calculating the fluctuating generated power, obtaining the total storage amount, dividing the power storage system into usage storage, alarm storage and stable storage, forming a joint regulation platform, and constructing a dynamic alarm regulation system for the control platform. The advantages of the present invention are as follows: By means of dynamic time period division, fluctuating load calculation, classified regulation of energy storage devices, etc., the real-time monitoring and dynamic regulation of the load of the power system are realized, thereby improving the stability of the power system and the utilization rate of energy storage devices.

Description

Technical Field

[0001] The present invention relates to the field of automatic control of power systems, and specifically to a control method for energy storage devices for load balancing in power systems. Background Art

[0002] With the continuous development of power systems, the volatility of power loads has become increasingly significant. Especially during peak and off-peak periods, there are large differences in power loads in power systems. Traditional power system load balancing methods mainly rely on the regulation of generators, but this method has problems such as slow response speed and low regulation accuracy. To cope with the fluctuations of power loads, energy storage devices have gradually been introduced into power systems to balance load fluctuations. However, existing energy storage device control methods still have problems such as untimely regulation and low utilization rate of energy storage devices when dealing with complex load fluctuations. Therefore, there is an urgent need for a control method that can monitor power load fluctuations in real time and dynamically regulate energy storage devices to improve the stability of power systems and the utilization rate of energy storage devices. Summary of the Invention

[0003] To solve the above technical problems, a control method for energy storage devices for load balancing in power systems is provided. This technical solution solves the problems of untimely regulation and low utilization rate of energy storage devices when dealing with complex load fluctuations as mentioned in the above background art.

[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0005] A control method for energy storage devices for load balancing in power systems, based on sensors at power detection points, obtains the power data of the load in the power system, denoted as the total load, and constructs a control platform;

[0006] Based on the total load, through dynamic time period division, multiple fluctuation types are formed, and the load data with the same fluctuation type is selected as the fluctuating load, and the division process and fluctuation types are fed back to the control platform;

[0007] Based on the total load and the fluctuating load, calculate the proportion of each fluctuating load in the total load power, denoted as the fluctuating load weight;

[0008] Based on the fluctuating load, calculate the maximum load power line and the warning load power line;

[0009] Obtain the power data generated by the power sources in the power system, denoted as the total generated power;

[0010] Based on the total generated power, according to the node load power weight, calculate the generated power data within each fluctuation type, denoted as the fluctuating generated power;

[0011] Subtract the fluctuating power output from the maximum load power for the corresponding time period to obtain the difference between the fluctuating power output and the maximum load power, denoted as the total storage capacity;

[0012] Based on the fluctuating power output, the power storage system is divided into usage storage, alarm storage, and stable storage. The usage storage, alarm storage, and stable storage form a joint regulation platform;

[0013] Associate the joint regulation platform with the control platform and combine it with dynamic time period division to form a control platform dynamic alarm regulation system.

[0014] Preferably, the formation of multiple fluctuation types through dynamic time period division based on the total load specifically includes:

[0015] Taking each hour as a node, divide a day into multiple local time periods, and count the power consumption within the local time periods to obtain the local load power;

[0016] Based on the local load power, calculate the average value of the local load power, denoted as the standard load power;

[0017] Arrange the data of the local load power in ascending order, select the first 10 data and the last 10 data in the row arrangement, denoted as influencing factors;

[0018] Delete the influencing factors in the arrangement to form fluctuating row data;

[0019] Based on multiple sets of fluctuating row data, calculate the average value of the fluctuating row data to obtain the low fluctuation threshold;

[0020] Add the low fluctuation threshold to the standard load power to obtain the medium load power;

[0021] Multiply the medium load power by the proportion of the influencing factors in the total data to obtain the medium fluctuation threshold;

[0022] Based on the local load power data, subtract the local load power between adjacent local time periods to obtain multiple power differences;

[0023] Mark the adjacent local time periods with a power difference less than the low fluctuation threshold as the low fluctuation time group, and mark the local time period with a larger local load power within the low fluctuation time group as the low fluctuation type;

[0024] Mark the adjacent local time periods with a power difference between the low fluctuation threshold and the medium fluctuation threshold as the medium fluctuation time group, and mark the local time period with a larger local load power within the medium fluctuation time group as the medium fluctuation type;

[0025] Mark the adjacent local time periods with a power difference higher than the medium fluctuation threshold as the high fluctuation time group, and mark the local time period with a larger local load power within the high fluctuation time group as the high fluctuation type.

[0026] Preferably, setting the load data with the same screening fluctuation type as the fluctuating load specifically includes:

[0027] Summarize the local load power data of the local time period with the low fluctuation type to form a low fluctuation load, and perform single-time timing monitoring by the control platform;

[0028] Summarize the local load power data of the local time period with the medium fluctuation type to form a medium fluctuation load, and perform multiple-time timing monitoring by the control platform;

[0029] Summarize the local load power data of the local time period with the high fluctuation type to form a high fluctuation load, and implement monitoring by the control platform.

[0030] Preferably, calculating the maximum load power line and the warning load power line based on the fluctuating load specifically includes:

[0031] Based on all the data within the fluctuating load, screen the maximum value of the local load power within the fluctuation type, and record it as the maximum load power;

[0032] Connect the maximum load powers of each fluctuation type to form a maximum load power line;

[0033] Based on multiple influencing factors, calculate the average value of the influencing factors to obtain an influencing average value;

[0034] Calculate the proportion of the maximum load power in the total load power, and record it as the maximum load weight;

[0035] Multiply the maximum load weight by the influencing average value to obtain an influencing fluctuation parameter;

[0036] Multiply the maximum load power by the influencing fluctuation parameter to obtain the warning load power;

[0037] Connect the warning load powers of each fluctuation type to form a warning load power line.

[0038] Preferably, using storage, alarm storage, and stable storage to form a joint regulation mechanism specifically includes:

[0039] Set current transformers and voltage transformers in the use storage, alarm storage, and stable storage, and connect the current transformers and voltage transformers to the control platform;

[0040] Based on the current transformers, monitor the internal power parameters of the use storage, alarm storage, and stable storage, and feedback the monitoring results to the control platform;

[0041] Based on the detection results of the current transformers, the control platform controls the power generation and load of the use storage, alarm storage, and stable storage.

[0042] Preferably, based on the detection results of the current transformers, the control platform performs deployment control on the power generation and load of the usage storage, alarm storage, and stable storage, which specifically includes:

[0043] When the power stored in the usage storage is lower than the maximum load power line, the control platform will activate the alarm storage, causing the alarm storage to enter the discharge state and sharing the overall power load synchronously with the usage storage;

[0044] Through the control platform database, obtain the fluctuating load of the previous month, denoted as the preparatory data, and perform fitting on multiple preparatory data with respect to time to form a preparatory curve. The abscissa of the preparatory curve is time;

[0045] Combine the preparatory data and its corresponding time into coordinate points, where the abscissa of the coordinate points is time;

[0046] Take the average value of the preparatory data in the coordinate points above the preparatory curve, denoted as the preset upper limit;

[0047] Take the average value of the preparatory data in the coordinate points below the preparatory curve, denoted as the preset lower limit;

[0048] When the power of the alarm storage reaches the preset upper limit, the control platform will activate the stable storage, causing the power inside the alarm storage to flow to the inside of the stable storage, so that the power of the alarm storage drops below the preset upper limit;

[0049] When the power of the alarm storage is insufficient for the preset lower limit, the control platform will activate the stable storage, causing the power inside the stable storage to flow to the inside of the alarm storage, so that the power inside the alarm storage reaches above the preset lower limit.

[0050] Preferably, associating the joint regulation platform with the control platform and combining dynamic time period division to form a control platform dynamic alarm regulation system specifically includes:

[0051] Based on the current transformers and voltage transformers set in the usage storage, alarm storage, and stable storage, obtain the actual power data in the usage storage, alarm storage, and stable storage, and feedback the actual power data to the inside of the control platform;

[0052] Connect the sensors at the power detection points to the inside of the control platform, obtain the real-time load data in the power system, and incorporate the real-time load data into the total load to achieve real-time update of the total load;

[0053] The control platform can, according to the real-time updated total load, based on the division rules, update the low fluctuation threshold and medium fluctuation threshold in real time, complete the update of calculating the fluctuating load, calculating the maximum load power line, and calculating the warning load power line, and feedback the update results to the inside of the control platform;

[0054] Let the key sites in the power system be nodes, and the nodes share the load data in the control platform through a communication network;

[0055] Embed a server at the node, connect the server to the power detection device, and conduct unified control by the control platform;

[0056] The control platform regularly obtains summary data from the edge nodes, obtains the actual total load, the actual fluctuation type, the actual maximum load power line, and the actual warning load power line, and feeds them back into the control platform. The actual maximum load power line is a curve of the actual maximum load power fitted with respect to time, and the actual warning load power line is a curve of the actual warning load power fitted with respect to time;

[0057] Based on the calculated maximum load power line, the calculated warning load power line, the actual maximum load power line, and the actual warning load power line, judge whether the power output is in a normal state. If it is in a normal state, no output is made. If it is not in a normal state, it is fed back to the dynamic alarm regulation system of the control platform, and the dynamic alarm regulation system monitors the power in real time.

[0058] Preferably, the dynamic alarm regulation system's real-time monitoring of power specifically includes:

[0059] Input the calculated maximum load power line and the actual maximum load power line into the control platform, calculate the average value of the ordinates of the points corresponding to the same time in the calculated maximum load power line and the actual maximum load power line, and denote it as the maximum average value;

[0060] Fit the maximum average value with respect to time to form a maximum power line. The abscissa of the maximum power line is time, and the ordinate is the maximum load power;

[0061] Input the calculated warning load power line and the actual warning load power line into the control platform, calculate the average value of the ordinates of the points corresponding to the same time in the calculated warning load power line and the actual warning load power line, and denote it as the warning average value;

[0062] Fit the warning average value with respect to time to form a warning power line. The abscissa of the warning power line is time, and the ordinate is the warning load power;

[0063] Take the time corresponding to the real-time load power as the characteristic time, take the ordinate corresponding to the characteristic time in the warning power line as the first ordinate, and take the ordinate corresponding to the characteristic time in the maximum power line as the second ordinate;

[0064] If the real-time load power is greater than the first vertical coordinate but does not exceed the second vertical coordinate, the control platform will generate a secondary alarm, notify the operator to check the power usage at the detection point, and feedback the inspection result to the control platform. If the real-time load power is greater than the second vertical coordinate, the control platform will generate a primary alarm, automatically activate the alarm storage, make the alarm storage cooperate with the usage storage for the load, and perform analysis and prediction based on the inspection results feedback in the secondary alarm.

[0065] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0066] The present invention proposes a control method for an energy storage device for power system load balancing. By taking each hour as a node, dividing a day into multiple local time periods, and dynamically calculating the low-fluctuation threshold and medium-fluctuation threshold based on the average value and fluctuation row data of the local load power, it can more accurately identify low-fluctuation, medium-fluctuation, and high-fluctuation types. According to the weight analysis of different types, dynamically adjusting the power output of the energy storage device according to the fluctuation load weight can more reasonably allocate the power output of the energy storage device and optimize the usage efficiency of the energy storage device. When the fluctuation load weight is relatively high, the system will preferentially use the alarm storage and stable storage to share the power load, ensuring the stable operation of the power system, effectively solving the problem of low usage efficiency of the energy storage device in traditional methods, and improving the usage efficiency of the energy storage device and the overall performance of the power system.

[0067] The present invention proposes a control method for an energy storage device for power system load balancing. By constructing a joint control platform, uniformly managing the usage storage, alarm storage, and stable storage, and combining dynamic time period division, a control platform dynamic alarm regulation system is formed. It can real-time obtain the load data in the power system and the power parameters of the energy storage device, and automatically adjust the power output of the energy storage device according to the real-time updated total load and fluctuation type. When the real-time load power exceeds the warning load power line, the system will automatically generate an alarm and activate the alarm storage, ensuring the stable operation of the power system, forming a real-time monitoring and automatic adjustment mechanism, and effectively solving the problem of untimely power load regulation in traditional methods, improving the stability and reliability of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 It is a flow diagram of the present invention;

[0069] Figure 2 It is a flow diagram of forming multiple fluctuation types based on the total load through dynamic time period division in the present invention;

[0070] Figure 3 It is a flow diagram of screening the load data with the same fluctuation type and setting it as the fluctuation load in the present invention;

[0071] Figure 4 Schematic diagram of the process for calculating the maximum load power line and the warning load power line based on the fluctuating load in the present invention;

[0072] Figure 5 Schematic diagram of the process for forming a combined regulation mechanism using storage, alarm storage, and stable storage in the present invention;

[0073] Figure 6 Schematic diagram of the process for the control platform to allocate and control the power generation and load of storage, alarm storage, and stable storage based on the detection results of the current transformer in the present invention;

[0074] Figure 7 Schematic diagram of the process for associating the combined regulation platform with the control platform and forming a dynamic alarm regulation system for the control platform in combination with dynamic time period division in the present invention;

[0075] Figure 8 Schematic diagram of the process for the dynamic alarm regulation system to monitor the power in real time in the present invention. Detailed implementation manners

[0076] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments in the following description are only examples, and those skilled in the art can think of other obvious variations.

[0077] Refer to Figure 1 As shown, a control method for an energy storage device for power system load balancing, based on sensors at power detection points, obtains the power data of the load in the power system, denoted as the total load, and constructs a control platform;

[0078] Based on the total load, through dynamic time period division, multiple fluctuation types are formed, the load data with the same fluctuation type is selected as the fluctuating load, and the division process and the fluctuation type are fed back to the control platform;

[0079] Based on the total load and the fluctuating load, calculate the proportion of each fluctuating load in the total load power, denoted as the fluctuating load weight;

[0080] Based on the fluctuating load, calculate the maximum load power line and the warning load power line;

[0081] Obtain the power data generated by the power sources in the power system, denoted as the total generated power;

[0082] Based on the total generated power, according to the node load power weight, calculate the generated power data within each fluctuation type, denoted as the fluctuating generated power;

[0083] Take the difference between the fluctuating generated power and the maximum load power in the corresponding time period to obtain the difference between the fluctuating generated power and the maximum load power, denoted as the total storage amount;

[0084] Based on the fluctuating output power, the power storage system is divided into usage storage, alarm storage, and stable storage. The usage storage, alarm storage, and stable storage form a joint regulation platform;

[0085] The joint regulation platform is associated with the control platform and, combined with dynamic time period division, forms a control platform dynamic alarm regulation system.

[0086] A distributed intelligent sensor array is adopted to collect the load power data of each monitoring point in the power system in real time. After the data is preprocessed by the edge computing node, it is transmitted to the control platform to form a total load data set. The control platform integrates a real-time database, a visualization interface, and an intelligent decision-making module to extract the fluctuation characteristics of the total load data on multiple time scales, divides the load curve into multiple fluctuation types, and the division results of each fluctuation type are fed back to the control platform in real time to form a dynamic load characteristic map. Combining the historical data ratio, peak-valley characteristics, and equipment operation characteristics of the loads of each fluctuation type, a fluctuation load weight matrix is calculated.

[0087] The total output power data is obtained in real time, and combined with the node load weights, the output power of each fluctuation type is dynamically allocated to form a fluctuating output power matrix. Through the predictive control algorithm, the accurate matching of the power generation output and the load fluctuation is realized, and a three-level energy storage system of usage storage, alarm storage, and stable storage is established, and real-time collaborative control is achieved through the bus of the control platform.

[0088] The load fluctuation characteristics, energy storage status, and power generation output are three-dimensionally visualized within the control platform. When it is detected that the load fluctuation in a certain time period exceeds the warning power line, the system automatically triggers the warning mechanism by calling the stable storage, usage storage, and alarm storage.

[0089] Refer to Figure 2 As shown, the formation of multiple fluctuation types based on the total load through dynamic time period division specifically includes:

[0090] Taking each hour as a node, a day is divided into multiple local time periods, and the power consumption within the local time periods is statistically calculated to obtain the local load power;

[0091] Based on the local load power, the average value of the local load power is calculated and denoted as the standard load power;

[0092] Arrange the data of the local load power in ascending order, select the first 10 data and the last 10 data in the row arrangement, and denote them as influencing factors;

[0093] Delete the influencing factors in the arrangement to form the fluctuating row and column data;

[0094] Based on multiple fluctuating row-column data, calculate the average value of the fluctuating row-column data to obtain a low-fluctuation threshold;

[0095] Add the low-fluctuation threshold to the standard load power to obtain the medium load power;

[0096] Multiply the medium load power by the proportion of the influencing factor in the total data to obtain the medium-fluctuation threshold;

[0097] Based on the local load power data, calculate the difference between the local load powers in adjacent local time periods to obtain multiple power differences;

[0098] Mark the adjacent local time periods with power differences less than the low-fluctuation threshold as the low-fluctuation time group, and mark the local time period with a larger local load power within the low-fluctuation time group as the low-fluctuation type;

[0099] Mark the adjacent local time periods with power differences between the low-fluctuation threshold and the medium-fluctuation threshold as the medium-fluctuation time group, and mark the local time period with a larger local load power within the medium-fluctuation time group as the medium-fluctuation type;

[0100] Mark the adjacent local time periods with power differences higher than the medium-fluctuation threshold as the high-fluctuation time group, and mark the local time period with a larger local load power within the high-fluctuation time group as the high-fluctuation type.

[0101] Adopt the sliding window technology. Taking 1 hour as the basic time unit, divide the 24 hours of the whole day into 24 local time periods. Each time period corresponds to an independent load data acquisition unit. The edge computing node collects and stores the electricity consumption power data within this time period in real time. Conduct statistical analysis on the load data of each local time period, calculate the average power value of this time period as the standard load power, then arrange the load data of each time period in ascending order, extract the first 10% and the last 10% of the data points as influencing factors, and then calculate their average value as the low-fluctuation threshold. The medium load power is obtained by superimposing the standard load power and the low-fluctuation threshold. The medium-fluctuation threshold is corrected according to the proportion of the influencing factor. Thus, the power difference between adjacent time periods can be calculated, and classification is carried out through the double-threshold discrimination method. And the system automatically updates the reference values and fluctuation thresholds of each time period every hour, dynamically corrects the threshold parameters, and ensures that the classification model can adapt to the seasonal changes and real-time fluctuations of the load characteristics.

[0102] Refer to Figure 3 As shown, setting the load data with the same screened fluctuation type as the fluctuating load specifically includes:

[0103] Summarize the local load power data of the local time periods of the low-fluctuation type to form the low-fluctuation load, and conduct single-time regular monitoring by the control platform;

[0104] Summarize the local load power data of the local time period of the medium fluctuation type to form a medium fluctuation load, and conduct multiple regular monitoring by the control platform;

[0105] Summarize the local load power data of the local time period of the high fluctuation type to form a high fluctuation load, and implement monitoring by the control platform.

[0106] The control platform implements a three-level monitoring mechanism through the task scheduling system. When in the low fluctuation load time period, conduct multiple regular monitoring. When in the medium fluctuation load, when multiple regular monitoring can be started, synchronously activate the pre-configured demand-side response strategy to conduct multiple regular monitoring. Finally, when in the high fluctuation load, trigger the pre-charging instruction of the energy storage system to conduct real-time monitoring.

[0107] Refer to Figure 4 As shown, calculating the maximum load power line and the warning load power line based on the fluctuating load specifically includes:

[0108] Based on all the data within the fluctuating load, screen the maximum value of the local load power within the fluctuation type, and record it as the maximum load power;

[0109] Connect the maximum load powers of each fluctuation type to form the maximum load power line;

[0110] Based on multiple influencing factors, calculate the average value of the influencing factors to obtain the average influencing value;

[0111] Calculate the proportion of the maximum load power in the total load power, and record it as the maximum load weight;

[0112] Multiply the maximum load weight by the average influencing value to obtain the influencing fluctuation parameter;

[0113] Multiply the maximum load power by the influencing fluctuation parameter to obtain the warning load power;

[0114] Connect the warning load powers of each fluctuation type to form the warning load power line.

[0115] Real-time scan each fluctuating load data set, extract the maximum value of the local load power of each fluctuation type, and use the cubic spline interpolation algorithm to smooth the discrete extreme points to generate a continuous maximum load power line,

[0116] And establish an influencing factor database based on historical data, calculate the average influencing value, so as to calculate the influencing fluctuation parameter according to the maximum load weight, and thus obtain the warning load power line. Among them, the influencing fluctuation parameter is obtained by multiplying the maximum load weight by the average value of the influencing factors, which reflects the coupling relationship between the load fluctuation characteristics and the external influencing factors. The warning load power is determined by the product of the extreme load and the influencing fluctuation parameter, and this value comprehensively considers the load extreme value and the amplification effect of potential influencing factors.

[0117] Superimpose the maximum load power line and the warning load power line on the 3D visualization interface of the control platform. When the real-time load curve touches the warning line, the system automatically triggers a secondary warning; when it breaks through the maximum line, a primary emergency response is initiated.

[0118] Refer to Figure 5 As shown, the specific implementation of the combined regulation mechanism formed by usage storage, alarm storage, and stable storage includes:

[0119] Install current transformers and voltage transformers in usage storage, alarm storage, and stable storage, and connect the current transformers and voltage transformers to the control platform.

[0120] Based on the current transformers, monitor the internal power parameters of usage storage, alarm storage, and stable storage, and feedback the monitoring results to the control platform.

[0121] Based on the detection results of the current transformers, the control platform allocates and controls the power generation and load of usage storage, alarm storage, and stable storage.

[0122] Install high-precision current transformers and voltage transformers in the three major energy storage units of usage storage, alarm storage, and stable storage respectively, so that the transformers are connected to the edge computing nodes of the control platform through industrial Ethernet to form a distributed monitoring network, and real-time collect parameters such as voltage, current, and power factor of the energy storage system, and transmit the parameters to the inside of the control platform. The control platform dynamically adjusts the energy storage operation mode according to the real-time monitoring data, so that usage storage, alarm storage, and stable storage can cooperate with each other, circulate, and ensure stable power transmission.

[0123] Refer to Figure 6 As shown, the specific implementation of the control platform's allocation and control of the power generation and load of usage storage, alarm storage, and stable storage based on the detection results of the current transformers includes:

[0124] When the power stored in the usage storage is lower than the maximum load power line, the control platform will activate the alarm storage, making the alarm storage enter the discharge state and sharing the overall power load synchronously with the usage storage.

[0125] Through the control platform database, obtain the fluctuating load of the previous month, record it as the preparatory data, and fit multiple preparatory data with respect to time to form a preparatory curve. The abscissa of the preparatory curve is time.

[0126] Combine the preparatory data and its corresponding time into coordinate points, and the abscissa of the coordinate points is time.

[0127] Take the average value of the preparatory data in the coordinate points above the preparatory curve, and record it as the preset upper limit.

[0128] Take the average of the preliminary data in the coordinate points below the preliminary curve and denote it as the preset lower limit;

[0129] When the alarm storage power reaches the preset upper limit, the control platform will activate stable storage, causing the power inside the alarm storage to flow into the stable storage, reducing the alarm storage power below the preset upper limit;

[0130] When the alarm storage power is insufficient for the preset lower limit, the control platform will activate stable storage, causing the power inside the stable storage to flow into the alarm storage, bringing the power inside the alarm storage above the preset lower limit.

[0131] The control platform monitors the state of charge of the used storage in real time through a current transformer. When the real-time monitoring data is lower than the capacity threshold corresponding to the maximum load power line, it triggers the pre-start instruction of the alarm storage, forms a parallel power supply with the used storage, jointly bears the high-fluctuation load, and can independently obtain historical data. Combining with historical data, it provides a reasonable regulation boundary for the current energy storage state, thus providing a data basis for setting alarm conditions for the alarm system.

[0132] Refer to Figure 7 As shown, the association of the joint regulation platform with the control platform and the combination with dynamic time period division to form a control platform dynamic alarm regulation system specifically includes:

[0133] Based on the current transformers and voltage transformers set in the used storage, alarm storage, and stable storage, obtain the actual power data in the used storage, alarm storage, and stable storage, and feedback the actual power data to the inside of the control platform;

[0134] Connect the sensors at the power detection points to the inside of the control platform, obtain the real-time load data in the power system, and incorporate the real-time load data into the total load to achieve real-time update of the total load;

[0135] The control platform can, according to the real-time updated total load, based on the division rules, real-time update the low-fluctuation threshold and medium-fluctuation threshold, complete the update of calculating the fluctuating load, calculating the maximum load power line, and calculating the warning load power line, and feedback the update results to the inside of the control platform;

[0136] Set the key stations in the power system as nodes, and the nodes share the load data inside the control platform through a communication network;

[0137] Install an embedded server at the node, connect the server to the power detection equipment, and conduct unified control by the control platform;

[0138] The control platform regularly obtains summary data from the edge nodes, obtains the actual total load, actual fluctuation type, actual maximum load power line, and actual warning load power line, and feeds them back into the control platform. The actual maximum load power line is a curve fitted by the actual maximum load power with respect to time, and the actual warning load power line is a curve fitted by the actual warning load power with respect to time;

[0139] Based on the calculated maximum load power line, calculated warning load power line, actual maximum load power line, and actual warning load power line, judge whether the power output is in a normal state. If it is in a normal state, no output is made. If it is not in a normal state, it is fed back to the dynamic alarm control system of the control platform, and the dynamic alarm control system monitors the power in real time.

[0140] First, the control platform obtains the load data in the power system and the power parameters of the energy storage device in real time, combines the dynamic time period division rule, updates the low fluctuation threshold and medium fluctuation threshold in real time, and completes the calculation and update of the fluctuating load, maximum load power line, and warning load power line. These update results are fed back into the control platform to form the calculated maximum load power line and the calculated warning load power line. At the same time, the control platform regularly obtains summary data from the edge nodes, obtains the actual total load, actual fluctuation type, actual maximum load power line, and actual warning load power line, and feeds these data back into the control platform. The actual maximum load power line and the actual warning load power line are curves fitted by the actual maximum load power and the actual warning load power with respect to time respectively. Next, the control platform judges the power output state based on the calculated maximum load power line, calculated warning load power line, actual maximum load power line, and actual warning load power line. The specific judgment method is as follows: Take the time corresponding to the real-time load power as the characteristic time, take the ordinate corresponding to the characteristic time in the warning power line as the first ordinate, and take the ordinate corresponding to the characteristic time in the maximum power line as the second ordinate. If the real-time load power is less than or equal to the first ordinate, it is judged that the power output is in a normal state, and the control platform does not make an output; if the real-time load power is greater than the first ordinate but does not exceed the second ordinate, the control platform will generate a secondary alarm, notify the operator to check the power usage situation at the detection point, and feed back the inspection result to the control platform; if the real-time load power is greater than the second ordinate, the control platform will generate a primary alarm, automatically turn on the alarm storage, make the alarm storage cooperate with the usage storage for load, and perform analysis and prediction based on the inspection result feedback in the secondary alarm. Through this judgment method, the control platform can monitor the load state of the power system in real time to ensure the stability and reliability of the power output.

[0141] Refer to Figure 8 As shown, the real-time monitoring of power by the dynamic alarm control system specifically includes:

[0142] Input and calculate the maximum load power line and the actual maximum load power line in the control platform. Calculate the average value of the ordinates of the points corresponding to the same time in the maximum load power line and the actual maximum load power line, and denote it as the maximum average value;

[0143] Fit the maximum average value with respect to time to form the maximum power line. The abscissa of the maximum power line is time, and the ordinate is the maximum load power;

[0144] Input and calculate the warning load power line and the actual warning load power line in the control platform. Calculate the average value of the ordinates of the points corresponding to the same time in the warning load power line and the actual warning load power line, and denote it as the warning average value;

[0145] Fit the warning average value with respect to time to form the warning power line. The abscissa of the warning power line is time, and the ordinate is the warning load power;

[0146] Take the time corresponding to the real-time load power as the characteristic time, take the ordinate corresponding to the characteristic time in the warning power line as the first ordinate, and take the ordinate corresponding to the characteristic time in the maximum power line as the second ordinate;

[0147] If the real-time load power is greater than the first ordinate but does not exceed the second ordinate, the control platform will generate a secondary alarm, notify the operator to check the power usage situation of the detection point, and feedback the inspection result to the control platform. If the real-time load power is greater than the second ordinate, the control platform will generate a primary alarm, automatically turn on the alarm storage, make the alarm storage cooperate with the usage storage for the load, and perform analysis and prediction according to the inspection result feedback in the secondary alarm.

[0148] Within the control platform, the dynamic alarm regulation system calculates the maximum load power line and the actual maximum load power line through input, and calculates the average value of the vertical coordinates at the same time point of the two, which is denoted as the maximum average value. Subsequently, the control platform fits the maximum average value with respect to time to form the maximum power line, where the abscissa of this line is time and the ordinate is the maximum load power. In the same way, the control platform inputs and calculates the warning load power line and the actual warning load power line, calculates the average value of the vertical coordinates at the same time point of the two, which is denoted as the warning average value, and fits the warning average value with respect to time to form the warning power line, whose abscissa is time and the ordinate is the warning load power. Next, the control platform takes the time corresponding to the real-time load power as the characteristic time, takes the vertical coordinate corresponding to the characteristic time in the warning power line as the first vertical coordinate, and takes the vertical coordinate corresponding to the characteristic time in the maximum power line as the second vertical coordinate. In this way, the control platform can judge the load status of the power system in real time. If the real-time load power is greater than the first vertical coordinate but does not exceed the second vertical coordinate, the control platform will generate a secondary alarm, notify the operator to check the power usage at the detection point, and feedback the inspection result to the control platform for further analysis of the operation status of the power system. If the real-time load power is greater than the second vertical coordinate, the control platform will generate a primary alarm, automatically activate the alarm storage, and make the alarm storage cooperate with the usage storage to share the load pressure of the power system to ensure the stable operation of the system. At the same time, the control platform will conduct in-depth analysis and prediction based on the inspection results in the secondary alarm, and optimize the load distribution of the power system and the regulation strategy of the energy storage device. Through this real-time monitoring and dynamic adjustment mechanism, the control platform can effectively respond to the load fluctuations in the power system, ensure the stability and reliability of the power output, and at the same time improve the utilization efficiency of the energy storage device.

[0149] In summary, the advantages of the present invention are as follows: By means of dynamic time period division, fluctuating load calculation, classified regulation of energy storage devices, etc., the real-time monitoring and dynamic regulation of the load of the power system are realized, thereby improving the stability of the power system and the utilization rate of the energy storage device.

[0150] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification is only the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for controlling energy storage equipment for load balancing of a power system, characterized in that: include: Based on the sensors at the power detection points, the power data of the load in the power system is obtained, recorded as the total load, and a control platform is built; Based on the total load, multiple fluctuation types are formed through dynamic time period division, and the load data with the same fluctuation type are selected as the fluctuating load, and the division process and fluctuation type are fed back to the control platform; Based on the total load and fluctuating load, calculate the proportion of each fluctuating load in the total load power, which is recorded as the fluctuating load weight; Based on the fluctuating load, calculate the maximum load power line and the warning load power line; Obtain the power data generated by the power supply in the power system, recorded as the total generated power; Based on the total output power, according to the node load power weight, the output power data within each fluctuation type is calculated and recorded as the fluctuating output power; The difference between the fluctuating power and the maximum load power in the corresponding time period is calculated to obtain the difference between the fluctuating power and the maximum load power, which is recorded as the total storage amount; Based on the fluctuating power output, the power storage system is divided into usage storage, alarm storage and stable storage, which form a joint control platform; Link the joint control platform to the control platform and combine it with dynamic time period division to form a dynamic alarm control system for the control platform; Setting current transformers and voltage transformers in the use storage, alarm storage and stable storage, and connecting the current transformers and voltage transformers to the control platform; Based on current transformers, the internal power parameters of the usage storage, alarm storage and stable storage are monitored, and the monitoring results are fed back to the control platform; Based on the detection results of the current transformer, the control platform controls the generation and load of the use storage, alarm storage and stable storage power; The method of associating the joint control platform with the control platform and combining the dynamic time period division to form a dynamic alarm control system for the control platform specifically includes: Based on the current transformers and voltage transformers set in the usage storage, alarm storage and stable storage, the actual power data in the usage storage, alarm storage and stable storage are obtained, and the actual power data is fed back to the control platform; Connect the sensors at the power detection points to the control platform to obtain real-time load data in the power system, and incorporate the real-time load data into the total load to achieve real-time update of the total load; The control platform can update the low fluctuation threshold and the medium fluctuation threshold in real time according to the real-time updated total load and the division rules, complete the calculation of the fluctuating load, the calculation of the maximum load power line and the calculation of the warning load power line, and feed back the update results to the control platform; The key sites in the power system are assumed to be nodes, and the nodes share the load data in the control platform through the communication network; Install an embedded server at the node, connect the server to the power detection equipment, and control it uniformly through the control platform; The control platform periodically obtains summary data from edge nodes to obtain the actual total load, actual fluctuation type, actual maximum load power line and actual warning load power line, and feeds them back to the control platform. The actual maximum load power line is a curve of the actual maximum load power fitting over time, and the actual warning load power line is a curve of the actual warning load power fitting over time. Based on the calculated maximum load power line, the calculated warning load power line, the actual maximum load power line and the actual warning load power line, it is determined whether the power output is in a normal state. If it is in a normal state, no output is made. If it is not in a normal state, it is fed back to the dynamic alarm control system of the control platform. The dynamic alarm control system monitors the power in real time.

2. A method for controlling energy storage equipment for load balancing of a power system according to claim 1, characterized in that: The multiple fluctuation types formed based on the total load and divided by dynamic time periods specifically include: Taking each hour as a node, a day is divided into multiple local time periods, and the power consumption in the local time period is counted to obtain the local load power; Based on the local load power, the average value of the local load power is calculated and recorded as the standard load power; Arrange the data of local load power from small to large, select the first 10 data and the last 10 data of the row arrangement, and record them as influencing factors; Delete the influencing factors in the arrangement to form fluctuating row and column data; Based on multiple fluctuation row and column data, the average value of the fluctuation row and column data is calculated to obtain a low fluctuation threshold value; Add the low fluctuation threshold to the standard load power to get the medium load power; Multiply the medium load power by the proportion of the influencing factor in the total data to obtain the medium fluctuation threshold; Based on the local load power data, the local load powers in adjacent local time periods are subtracted to obtain multiple power differences; The adjacent local time periods with power difference less than the low fluctuation threshold are recorded as low fluctuation time groups, and the local time periods with larger local load power in the low fluctuation time groups are recorded as low fluctuation types; The adjacent local time periods with power difference between the low fluctuation threshold and the medium fluctuation threshold are recorded as the medium fluctuation time group, and the local time period with large local load power in the medium fluctuation time group is recorded as the medium fluctuation type; Adjacent local time periods with power differences higher than the medium fluctuation threshold are recorded as high fluctuation time groups, and local time periods with larger local load power within the high fluctuation time groups are recorded as high fluctuation types.

3. A method for controlling energy storage equipment for load balancing of a power system according to claim 2, characterized in that: The step of screening load data with the same fluctuation type and setting them as fluctuating loads specifically includes: The local load power data of the local time period of the low-fluctuation type is aggregated to form a low-fluctuation load, which is monitored by the control platform at a single time. The local load power data of the local time period of the medium fluctuation type is aggregated to form a medium fluctuation load, which is monitored multiple times by the control platform at regular intervals; The local load power data of the local time period of the high fluctuation type is aggregated to form a high fluctuation load, which is monitored by the control platform.

4. The energy storage device control method for load balancing of a power system according to claim 3, characterized in that: The calculation of the maximum load power line and the warning load power line based on the fluctuating load specifically includes: Based on all the data in the fluctuating load, the maximum value of the local load power in the fluctuation type is selected and recorded as the maximum load power; Connect the maximum load powers of each fluctuation type to form a maximum load power line; Based on multiple influencing factors, the average values ​​of the influencing factors are calculated to obtain the influencing average value; Calculate the ratio of the maximum load power to the total load power, which is recorded as the maximum load weight; Multiply the maximum load weight by the influence average value to obtain the influence fluctuation parameter; Multiply the maximum load power by the influencing fluctuation parameter to obtain the warning load power; Connect the warning load powers of each fluctuation type to form a warning load power line.

5. The energy storage device control method for load balancing of a power system according to claim 4, characterized in that: The control platform controls the generation and load of power for use storage, alarm storage and stable storage based on the detection results of the current transformer, specifically including: When the stored power in the usage storage is lower than the maximum load power line, the control platform will turn on the alarm storage, so that the alarm storage enters the discharge state and shares the overall power load synchronously with the usage storage; The fluctuating load of the previous month is obtained through the control platform database and recorded as the preliminary data, and multiple preliminary data are fitted with respect to time to form a preliminary curve, and the horizontal axis of the preliminary curve is time; Combine the prepared data and its corresponding time into a coordinate point, where the horizontal coordinate of the coordinate point is time; Take the average of the preliminary data at the coordinate points above the preliminary curve and record it as the preset upper limit; Take the average of the preliminary data at the coordinate points below the preliminary curve and record it as the preset lower limit; When the alarm storage power reaches the preset upper limit, the control platform will open the stable storage, so that the power inside the alarm storage flows to the stable storage, so that the alarm storage power drops below the preset upper limit; When the alarm storage power is less than the preset lower limit, the control platform will turn on the stable storage, allowing the power inside the stable storage to flow to the alarm storage, so that the power inside the alarm storage reaches above the preset lower limit.

6. The energy storage device control method for load balancing of a power system according to claim 5, characterized in that: The dynamic alarm control system performs real-time monitoring of power, specifically including: Input the calculated maximum load power line and the actual maximum load power line into the control platform, calculate the average value of the ordinates of the points corresponding to the same time in the maximum load power line and the actual maximum load power line, and record it as the maximum average value; The maximum average value is fitted with respect to time to form a maximum power line, where the horizontal coordinate of the maximum power line is time and the vertical coordinate is the maximum load power; Input the calculated warning load power line and the actual warning load power line into the control platform, calculate the average value of the ordinates of the points corresponding to the same time in the warning load power line and the actual warning load power line, and record it as the warning average value; The warning average value is fitted with respect to time to form a warning power line, the horizontal axis of the warning power line is time, and the vertical axis is the warning load power; The time corresponding to the real-time load power is used as the characteristic time, the ordinate corresponding to the characteristic time in the warning power line is used as the first ordinate, and the ordinate corresponding to the characteristic time in the maximum power line is used as the second ordinate; If the real-time load power is greater than the first vertical coordinate but not more than the second vertical coordinate, the control platform will generate a secondary alarm, notify the operator to check the power usage of the detection point, and feedback the inspection results to the control platform. If the real-time load power is greater than the second vertical coordinate, the control platform will generate a first-level alarm, automatically open the alarm storage, so that the alarm storage and the use of storage coordinate the load, and perform analysis and prediction based on the inspection results fed back in the second-level alarm.

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