Voltage support control method and system of energy storage system in microgrid

Abstract

The invention relates to the technical field of energy storage systems, in particular to a voltage support control method and system of an energy storage system in a micro-grid. According to the method, the problem of excessive voltage fluctuation or untimely adjustment possibly caused by single power adjustment is effectively avoided by combining dynamic adjustment of active power and reactive power, and the control parameters of the energy storage system can be optimized in real time by generating the local power control curve and the voltage transient distribution map of the energy storage system, so that the energy storage system can be optimized in real time. The method ensures that the system provides optimal voltage support under different load working conditions, ensures the stability of the power grid voltage, realizes the optimization of energy distribution of the energy storage system by dynamically adjusting the output quantities of active power and reactive power, avoids energy waste or shortage, and improves the stability of the system by generating a voltage support control model. According to the invention, the voltage stability supporting function of the energy storage system is realized, and the stability of the voltage and the high efficiency of the system can be continuously maintained in the long-term operation process of the micro-grid.

Description

Technical Field

[0001] This invention relates to the field of energy storage system technology, and in particular to a voltage support control method and system for an energy storage system in a microgrid. Background Technology

[0002] A microgrid is a small, localized power network, typically composed of multiple distributed energy sources and loads, capable of operating in connected or isolated modes. Voltage support control in a microgrid refers to regulating and stabilizing the voltage level of the microgrid through energy storage devices. Since the power sources within a microgrid may fluctuate, voltage support is crucial. The goal of voltage support control is to maintain the voltage of the microgrid within a specified safe range, preventing voltage from being too low or too high.

[0003] Current technologies for voltage support control of energy storage systems in microgrids primarily maintain grid voltage stability by adjusting the reactive power output of the energy storage system. When the voltage is too low, the energy storage system provides reactive power to boost the voltage; conversely, it absorbs reactive power to lower the voltage, ensuring the grid operates within a safe voltage range. However, the adjustment of reactive power by energy storage systems is often limited by the system itself. The charging state, power output capability, and electrical characteristics of the energy storage system all influence each other, potentially leading to insufficient energy allocation to meet the active load demands during reactive power adjustment. Summary of the Invention

[0004] The main objective of this invention is to provide a voltage support control method for energy storage systems in microgrids, aiming to solve the technical problems in the prior art.

[0005] This invention proposes a voltage support control method for an energy storage system in a microgrid, comprising:

[0006] Acquire the basic operating parameters, real-time dynamic status parameters, real-time load change data and initial control parameters of the energy storage system of the microgrid, and determine the initial active power and initial reactive power of the energy storage system based on the basic operating parameters and initial control parameters;

[0007] The initial active power output and initial reactive power output of the corresponding energy storage system are obtained based on the initial active power and initial reactive power.

[0008] The power regulation deviation value is obtained based on the real-time dynamic status parameters and real-time load change data;

[0009] The initial active power output and initial reactive power output of the energy storage system are dynamically adjusted according to the power regulation deviation value, and multiple voltage fluctuation amplitudes and power response delay times of the microgrid under different load conditions are obtained in real time during the adjustment process.

[0010] The local power control curve of the energy storage system is generated based on multiple voltage fluctuation amplitudes and power response delay times, and the bus voltage transient data at multiple consecutive moments are obtained based on the local power control curve.

[0011] A voltage transient distribution map is obtained based on multiple bus voltage transient data, and optimized control parameters are obtained based on the voltage transient distribution map;

[0012] The power-voltage correlation dataset is obtained based on the local power control curve, and a voltage support control model is generated based on the power-voltage correlation dataset and optimized control parameters, so that the energy storage system can achieve voltage stability support for the microgrid according to the voltage support control model.

[0013] Preferably, the step of determining the initial active power and initial reactive power of the energy storage system based on the basic operating parameters and initial control parameters includes:

[0014] Acquire basic operating parameters and initial control parameters, wherein the basic operating parameters include the bus rated voltage, load rated power and line impedance value, and the initial control parameters include the initial duty cycle, initial current loop gain and initial voltage loop gain of the energy storage DC / DC converter;

[0015] The voltage loss coefficient is obtained based on the rated bus voltage and line impedance value, and the rated voltage loss value is obtained based on the voltage loss coefficient and the rated load power.

[0016] The allowable voltage deviation range is obtained based on the rated voltage loss value and the rated bus voltage, and the voltage control threshold range is determined based on the allowable voltage deviation range.

[0017] The voltage regulation sensitivity is obtained based on the initial duty cycle and the initial voltage loop gain, and the reactive power regulation range is obtained based on the voltage regulation sensitivity and the voltage control threshold range.

[0018] The current carrying capacity is obtained based on the initial current loop gain and the rated load power, and the active power adjustment range is obtained based on the current carrying capacity and the reactive power adjustment range.

[0019] The median value of the active power adjustment range is selected as the initial active power, and the median value of the reactive power adjustment range is selected as the initial reactive power.

[0020] Preferably, the step of obtaining the power regulation deviation value based on the real-time dynamic state parameters and real-time load change data includes:

[0021] Acquire real-time dynamic status parameters and real-time load change data, wherein the real-time dynamic status parameters include real-time bus voltage, real-time bus current and real-time output power of energy storage system, and the real-time load change data includes load active power fluctuation value and load reactive power fluctuation value;

[0022] The voltage deviation is obtained based on the real-time bus voltage and the rated bus voltage, and the voltage deviation contribution value is obtained based on the voltage deviation and the preset voltage weighting coefficient.

[0023] The line power loss is obtained based on the real-time bus current and line impedance value, and the loss deviation contribution value is obtained based on the line power loss and the preset loss weighting coefficient.

[0024] The active load fluctuation ratio is obtained based on the active power fluctuation value and the rated power of the load, and the active power fluctuation contribution value is obtained based on the active load fluctuation ratio and the preset active power weighting coefficient.

[0025] The reactive load fluctuation ratio is obtained based on the load reactive power fluctuation value and the load rated power, and the reactive power fluctuation contribution value is obtained based on the reactive load fluctuation ratio and the preset reactive power weighting coefficient.

[0026] The power regulation deviation value is obtained by weighting and summing the voltage deviation contribution value, loss deviation contribution value, active power fluctuation contribution value, and reactive power fluctuation contribution value.

[0027] Preferably, the step of dynamically adjusting the initial active power output and initial reactive power output of the energy storage system based on the power regulation deviation value includes:

[0028] Analyze the relationship between the power regulation deviation value and the preset deviation threshold range;

[0029] If the power regulation deviation is within the preset deviation threshold range, the initial active power output and the initial reactive power output will remain unchanged.

[0030] If the power adjustment deviation is greater than the upper limit of the preset deviation threshold range, the total adjustment increment is obtained based on the difference between the power adjustment deviation and the upper limit.

[0031] The active power adjustment increment and reactive power adjustment increment are obtained according to the total adjustment increment, and the active power output and reactive power output are adjusted accordingly based on the active power adjustment increment and reactive power adjustment increment.

[0032] If the power regulation deviation is less than the lower limit of the preset deviation threshold range, the total regulation reduction is obtained based on the difference between the lower limit and the power regulation deviation.

[0033] The active power reduction and reactive power reduction are obtained based on the total reduction, and the active power output and reactive power output are adjusted accordingly based on the active power reduction and reactive power reduction.

[0034] Preferably, the step of generating the local power control curve of the energy storage system based on multiple voltage fluctuation amplitudes and power response delay times includes:

[0035] The control sampling frequency and initial operating characteristics of the energy storage system are obtained, wherein the initial operating characteristics include initial active power output, initial reactive power output, initial bus voltage, and initial response delay;

[0036] The time step is obtained according to the control sampling frequency, and the corresponding real-time update response delay is obtained according to the time step, the initial response delay, and the power response delay time.

[0037] The real-time updated active power output is obtained based on each of the real-time update response delay, initial active power output, voltage fluctuation amplitude, and time step; the real-time updated reactive power output is obtained based on each of the real-time update response delay, initial reactive power output, voltage fluctuation amplitude, and time step.

[0038] With time as the X-axis, active power output as the Y-axis, and reactive power output as the Z-axis, a three-dimensional coordinate axis of time-active power-reactive power is established, and the initial active power output, initial reactive power output, and initial response delay are plotted on the three-dimensional coordinate axis of time-active power-reactive power as the starting point.

[0039] Plot the real-time updated active power output, real-time updated reactive power output, and real-time updated response delay at each time step point on the time-active-reactive three-dimensional coordinate axis as connection points.

[0040] By sequentially connecting the starting point and multiple connection points with a smooth curve, a local power control curve is obtained.

[0041] Preferably, the step of obtaining a voltage transient distribution map based on multiple bus voltage transient data and obtaining optimized control parameters based on the voltage transient distribution map includes:

[0042] Each bus voltage transient data is divided into multiple data windows according to the time series, and multiple voltage sampling points are obtained according to each data window;

[0043] The voltage change rate and voltage duration of each voltage sampling point are obtained, and the standard deviation of the change rate and the average duration are obtained respectively according to the multiple voltage change rates and voltage durations;

[0044] The voltage transient correlation is obtained based on multiple voltage change rates and voltage durations, and a voltage stability evaluation matrix is ​​constructed based on the voltage transient correlation, the standard deviation of the change rate, and the average duration.

[0045] The eigenvalues ​​and eigenvectors are obtained from the voltage stability evaluation matrix, and the voltage stability coefficients are obtained from the eigenvalues ​​and eigenvectors.

[0046] Determine whether the voltage stability coefficient is greater than a preset stability threshold;

[0047] If the voltage stability coefficient is greater than the preset stability threshold, the voltage state of the corresponding data window is determined to be stable.

[0048] If the voltage stability coefficient is not greater than the preset stability threshold, the voltage state of the corresponding data window is determined to be unstable, and the corresponding voltage transient distribution map is obtained according to the distribution of multiple stable states and unstable states.

[0049] Based on the voltage transient distribution map, extract the power control parameters corresponding to each unstable state and the operating parameters of each stable state, and obtain the control parameter correction amount based on multiple power control parameters and operating parameters;

[0050] The initial control parameters are optimized and adjusted based on the control parameter correction amount to obtain the optimized control parameters.

[0051] Preferably, the step of obtaining the power-voltage correlation dataset based on the local power control curve, and generating a voltage support control model based on the power-voltage correlation dataset and optimized control parameters, includes:

[0052] Based on the local power control curve, obtain the active power control value and reactive power control value corresponding to multiple moments on the curve, and match the bus voltage transient data at the corresponding moment based on the multiple moments.

[0053] Effective power-voltage data pairs are formed by combining the active power control value, reactive power control value and corresponding bus voltage transient data at each moment, and a power-voltage correlation dataset is constructed based on multiple effective power-voltage data pairs.

[0054] The range of power parameter variation and the stability threshold of voltage parameter in the power-voltage correlation dataset are obtained, and the input dimension and output target of the preset regression analysis model are determined based on the range of variation, the stability threshold and the optimized control parameters.

[0055] A portion of the data from the power-voltage correlation dataset is used as training samples and input into a preset regression analysis model, and the weight coefficients of the model are adjusted according to the optimized control parameters.

[0056] The remaining data are verified using the adjusted preset regression analysis model to obtain the verification results. The model parameters are then optimized based on the verification results until the model error meets the preset requirements, thus obtaining the voltage support control model.

[0057] This application also provides a voltage support control system for an energy storage system in a microgrid, including:

[0058] The determination module is used to acquire the basic operating parameters, real-time dynamic status parameters, real-time load change data and initial control parameters of the microgrid, and determine the initial active power and initial reactive power of the energy storage system based on the basic operating parameters and initial control parameters.

[0059] The first acquisition module is used to acquire the initial active power output and initial reactive power output of the corresponding energy storage system based on the initial active power and initial reactive power.

[0060] The second acquisition module is used to acquire the power regulation deviation value based on the real-time dynamic status parameters and real-time load change data;

[0061] The adjustment module is used to dynamically adjust the initial active power output and initial reactive power output of the energy storage system according to the power adjustment deviation value, and to acquire in real time multiple voltage fluctuation amplitudes and power response delay times of the microgrid under different load conditions during the adjustment process.

[0062] The first generation module is used to generate a local power control curve of the energy storage system based on multiple voltage fluctuation amplitudes and power response delay times, and to obtain bus voltage transient data at multiple consecutive moments based on the local power control curve.

[0063] The third acquisition module is used to acquire a voltage transient distribution map based on multiple bus voltage transient data, and to acquire optimized control parameters based on the voltage transient distribution map;

[0064] The second generation module is used to obtain a power-voltage correlation dataset based on the local power control curve, and generate a voltage support control model based on the power-voltage correlation dataset and optimized control parameters, so that the energy storage system can achieve voltage stability support of the microgrid according to the voltage support control model.

[0065] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the voltage support control method of the energy storage system in the microgrid described above.

[0066] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the voltage support control method of the energy storage system in a microgrid described above.

[0067] The beneficial effects of this invention are as follows: By acquiring the dynamic state parameters and load change data of the microgrid in real time, this invention can quickly identify and respond to abnormal voltage fluctuations during grid operation. By combining the dynamic adjustment of active and reactive power, it effectively avoids the problems of excessive voltage fluctuations or untimely adjustment that may be caused by single power regulation. By generating the local power control curve and voltage transient distribution map of the energy storage system, the control parameters of the energy storage system can be optimized in real time, ensuring that the system provides optimal voltage support under different load conditions. While ensuring grid voltage stability, the energy distribution of the energy storage system is optimized by dynamically adjusting the output of active and reactive power, avoiding energy waste or shortage. This enables the energy storage system to not only efficiently support the voltage stability of the microgrid, but also achieve efficient energy utilization and system capacity management while meeting the active load demand. By generating a voltage support control model, the voltage stability support function of the energy storage system is realized, which can continuously maintain voltage stability and system efficiency during the long-term operation of the microgrid. Through accurate power-voltage correlation datasets, it can ensure that the energy storage system can make the most reasonable adjustment according to voltage changes at any time, thereby effectively preventing voltage collapse or excessive fluctuations. Attached Figure Description

[0068] Figure 1 This is a schematic diagram of a method flow according to an embodiment of the present invention.

[0069] Figure 2 This is a schematic diagram of the system structure according to an embodiment of the present invention.

[0070] Figure 3 This is a schematic diagram of the internal structure of a computer device according to an embodiment of this application.

[0071] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0072] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0073] like Figure 1 As shown, this application provides a voltage support control method for an energy storage system in a microgrid, comprising:

[0074] S1. Obtain the basic operating parameters, real-time dynamic status parameters, real-time load change data and initial control parameters of the microgrid, and determine the initial active power and initial reactive power of the energy storage system based on the basic operating parameters and initial control parameters.

[0075] S2. Obtain the initial active power output and initial reactive power output of the corresponding energy storage system based on the initial active power and initial reactive power.

[0076] S3. Obtain the power regulation deviation value based on real-time dynamic status parameters and real-time load change data;

[0077] S4. Dynamically adjust the initial active power output and initial reactive power output of the energy storage system according to the power regulation deviation value, and obtain multiple voltage fluctuation amplitudes and power response delay times of the microgrid under different load conditions in real time during the adjustment process.

[0078] S5. Generate the local power control curve of the energy storage system based on multiple voltage fluctuation amplitudes and power response delay times, and obtain the bus voltage transient data at multiple consecutive moments based on the local power control curve.

[0079] S6. Obtain the voltage transient distribution map based on multiple bus voltage transient data, and obtain the optimized control parameters based on the voltage transient distribution map;

[0080] S7. Obtain the power-voltage correlation dataset based on the local power control curve, and generate a voltage support control model based on the power-voltage correlation dataset and optimized control parameters, so that the energy storage system can achieve voltage stability support for the microgrid according to the voltage support control model.

[0081] As described in steps S1-S7 above, the ratio of active power regulation increment to reactive power regulation increment is determined based on the ratio of bus real-time voltage to bus rated voltage, and the ratio of active power regulation reduction to reactive power regulation reduction is determined based on the ratio of energy storage system output real-time power to load real-time power.

[0082] The steps for real-time acquisition of multiple voltage fluctuation amplitudes and power response delay times of a microgrid under different load conditions during adjustment include: real-time acquisition of the real-time voltage acquisition frequency of the microgrid under each load condition during adjustment, and setting a voltage sampling time interval based on the real-time voltage acquisition frequency; acquisition of multiple real-time voltage values ​​of the bus under each load condition based on the voltage sampling time interval, and acquisition of the corresponding average voltage value based on the multiple real-time voltage values; acquisition of the absolute value of the voltage difference based on each real-time voltage value and the average voltage value, and determination of the maximum value among the absolute values ​​as the voltage fluctuation amplitude under the corresponding load condition; acquisition of the issuance time of the power adjustment command of the energy storage system, and determination of the power response start time point based on the issuance time; acquisition of the time when the power output of the energy storage system reaches the target value of the adjustment command for each load condition, and determination of this time as the power response termination time point; acquisition of the time difference between the power response start time point and the power response termination time point, and determination of the time difference as the power response delay time under the corresponding load condition.

[0083] This invention, by dynamically acquiring and timely adjusting system parameters, ensures that the energy storage system can quickly identify abnormal behavior under different loads and operating conditions, avoiding excessive or insufficient power regulation caused by static parameter settings. This, in turn, ensures the timeliness and accuracy of voltage support. By converting initial active and reactive power into the actual output of the energy storage system, it can determine whether the system's basic voltage support requirements are met based on preset parameters and initial conditions. This ensures that the energy storage system can adapt to load and voltage fluctuations in real time. By calculating power regulation deviations using real-time dynamic status and load change data, the energy storage system can determine the current power matching degree and make subsequent power adjustments based on the deviation value. This invention provides real-time response to any voltage deviation changes in a microgrid, enabling precise regulation. Based on power regulation deviation, it dynamically adjusts the active and reactive power outputs of the energy storage system. This dynamic adjustment process allows for more detailed and flexible responses to changes in grid load and status, thus enabling rapid response to the actual needs of the system. By balancing active and reactive power, it can more effectively achieve voltage support and energy optimization. By generating local power control curves using multiple voltage fluctuation amplitudes and power response delay times, it can accurately depict the response characteristics of the energy storage system under different loads and operating conditions. This allows for real-time and accurate capture of the relationship between voltage fluctuations and the power output of the energy storage system, thereby enabling more precise responses to unexpected situations during system operation.

[0084] By generating voltage transient distribution maps from multiple bus voltage transient data, the fluctuation characteristics and trends of voltage under different load conditions can be accurately displayed, thus providing more reliable data support for system optimization control. The voltage transient distribution maps can reveal the full picture of microgrid voltage fluctuations in more detail, helping to more effectively identify abnormal electricity consumption behavior. By generating voltage support control models through power-voltage correlation datasets and optimized control parameters, the energy storage system can make precise adjustments according to the voltage support requirements under different operating conditions. It can not only respond to grid voltage fluctuations, but also adjust the output power of the energy storage system in real time, ensuring that the grid voltage always remains within a stable range.

[0085] In one embodiment, step S1, which determines the initial active power and initial reactive power of the energy storage system based on basic operating parameters and initial control parameters, includes:

[0086] S11. Obtain basic operating parameters and initial control parameters. The basic operating parameters include the rated voltage of the bus, the rated power of the load, and the line impedance value. The initial control parameters include the initial duty cycle, the initial current loop gain, and the initial voltage loop gain of the energy storage DC / DC converter.

[0087] S12. Obtain the voltage loss coefficient based on the ratio of the bus rated voltage to the line impedance value, and obtain the rated voltage loss value based on the product of the voltage loss coefficient and the rated load power.

[0088] S13. Obtain the allowable voltage deviation range based on the rated voltage loss value and the rated voltage of the bus, and determine the voltage control threshold range based on the allowable voltage deviation range;

[0089] S14. Obtain the voltage regulation sensitivity based on the initial duty cycle and initial voltage loop gain, and obtain the reactive power regulation range based on the voltage regulation sensitivity and voltage control threshold range.

[0090] S15. Obtain the current carrying capacity based on the initial current loop gain and the rated power of the load, and obtain the active power adjustment range based on the current carrying capacity and the reactive power adjustment range.

[0091] S16. Select the median value of the active power adjustment range as the initial active power, and select the median value of the reactive power adjustment range as the initial reactive power.

[0092] As described in steps S11-S16 above, the upper limit of the allowable voltage deviation range is calculated by adding the rated voltage loss value and the redundancy coefficient to the rated bus voltage, and the lower limit of the allowable voltage deviation range is calculated by subtracting the rated voltage loss value and the redundancy coefficient from the rated bus voltage. The formula for calculating the upper limit of the voltage control threshold range is as follows: ;in, This represents the upper limit of the voltage control threshold range. This indicates the lower limit of the allowable voltage deviation range. Indicates the rated voltage of the busbar. Indicates dead zone voltage. This represents the threshold coefficient; the formula for calculating the lower limit of the voltage control threshold range is: ;in, This represents the lower limit of the voltage control threshold range. This indicates the upper limit of the allowable voltage deviation range; the formula for calculating voltage regulation sensitivity is: ;in, Indicates voltage regulation sensitivity. Indicates the initial duty cycle. This represents the initial voltage loop gain. This represents the DC bus voltage of the energy storage system; the formula for calculating the lower limit of the reactive power regulation range is: ;in, This indicates the lower limit of the reactive power adjustment range. This represents the rated reactive power; the formula for calculating the upper limit of the reactive power adjustment range is: ;in, This represents the upper limit of the reactive power regulation range; the light load factor and overload factor are obtained through the load rated power and load rated current, the lower limit of current carrying capacity is obtained by multiplying the light load factor and the load rated current, the upper limit of current carrying capacity is obtained by multiplying the overload factor and the load rated current, and the apparent power range is obtained by multiplying the AC side voltage and the current carrying capacity. The formula for calculating the upper limit of the active power regulation range is: ;in, This indicates the upper limit of the active power adjustment range. This represents the upper limit of the apparent power range; the formula for calculating the lower limit of the active power adjustment range is: ;in, This indicates the lower limit of the active power adjustment range. Indicates the lower limit of the apparent power range;

[0093] This invention allows for a precise understanding of the system's operating environment and status through basic operating parameters, helping to ensure that the energy storage system's operation does not deviate from the expected design values. The voltage loss coefficient is closely related to the bus voltage and line impedance; obtaining the voltage loss coefficient can effectively predict voltage loss values, enabling the system to accurately assess voltage drops in the power grid under different load conditions. The calculation method based on the voltage loss coefficient can dynamically adjust the system's power output according to the actual operating conditions of the power grid, avoiding the incompatibility problems that may arise from using fixed parameters in traditional methods. Through accurate voltage loss prediction, the energy storage system can adjust its power output in advance, thereby ensuring grid voltage stability and avoiding the problems associated with traditional methods. The voltage control response lag phenomenon in this method can be addressed by obtaining the allowable voltage deviation range. The system can set a reasonable voltage fluctuation range, thereby better adapting to different load conditions and grid fluctuations. This avoids the rigid voltage control in traditional technology, which makes it unable to cope with complex load changes. By controlling the range of voltage deviation, the operating efficiency of the grid is optimized. While maintaining grid stability, excessive reactive power output is avoided, reducing the load on the energy storage system and thus improving the system's operating economy. The allowable voltage deviation range can improve the system's fault tolerance. Through the flexible voltage adjustment range, it can better cope with emergencies and improve the system's stability.

[0094] By combining the initial duty cycle and voltage loop gain to obtain voltage regulation sensitivity, the energy storage system can respond more quickly to voltage changes. This allows the system to not only effectively maintain voltage over a wide range but also rapidly adjust voltage within a short time, effectively improving grid stability and facilitating fine-grained voltage regulation. Refining the sensitivity parameters enables precise control of reactive power output, thus avoiding unreasonable power distribution caused by improper reactive power regulation and ensuring that active power demand is prioritized. Furthermore, by obtaining the current carrying capacity based on the current loop gain and rated load power, the maximum current range that the system can withstand can be clearly defined, thereby avoiding problems caused by excessive current. In the event of equipment damage or system instability, the current carrying capacity assessment ensures that the system can effectively cope with high load conditions, guaranteeing that the energy storage system can provide sufficient energy without overload under any load conditions. This ensures the stable operation of the power grid under high loads. By selecting the midpoint of the active and reactive power adjustment ranges as the initial power, the energy distribution of the energy storage system can be balanced between different power output demands, avoiding excessive adjustment of reactive power that leads to insufficient active power. By selecting the midpoint of the power adjustment range, the system can be in an optimized state from the beginning, reducing the frequency of extensive adjustments required by the energy storage system and lowering energy losses during the adjustment process.

[0095] In one embodiment, step S3, which obtains the power regulation deviation value based on real-time dynamic state parameters and real-time load change data, includes:

[0096] S31. Obtain real-time dynamic status parameters and real-time load change data. The real-time dynamic status parameters include real-time bus voltage, real-time bus current and real-time output power of the energy storage system. The real-time load change data includes load active power fluctuation value and load reactive power fluctuation value.

[0097] S32. Obtain the voltage deviation amount based on the absolute value of the difference between the real-time bus voltage and the rated bus voltage, and obtain the voltage deviation contribution value based on the product of the voltage deviation amount and the preset voltage weighting coefficient.

[0098] S33. Obtain the line power loss based on the real-time bus current and line impedance value, and obtain the loss deviation contribution value based on the product of the line power loss and the preset loss weighting coefficient.

[0099] S34. Obtain the active load fluctuation ratio based on the ratio of the load active power fluctuation value to the load rated power, and obtain the active power fluctuation contribution value based on the product of the active load fluctuation ratio and the preset active power weight coefficient.

[0100] S35. Obtain the reactive load fluctuation ratio based on the ratio of the reactive power fluctuation value to the rated power of the load, and obtain the reactive load fluctuation contribution value based on the product of the reactive load fluctuation ratio and the preset reactive weighting coefficient.

[0101] S36. The power regulation deviation value is obtained by weighted summing of the voltage deviation contribution value, loss deviation contribution value, active power fluctuation contribution value and reactive power fluctuation contribution value.

[0102] As described in steps S31-S36 above, this invention can provide basic data for subsequent power regulation by collecting real-time dynamic status parameters and real-time load change data, ensuring that the regulation strategy is based on the current real situation of the system. By calculating the voltage deviation through the difference between the real-time bus voltage and the rated voltage and combining it with the preset voltage weight coefficient, the contribution value of the voltage deviation to the power regulation is obtained, reflecting the impact of voltage fluctuations on the power output of the energy storage system. This can more accurately quantify the impact of voltage changes on the system, thereby achieving more efficient voltage regulation. By assigning weights to the contribution of voltage deviation, the system can more flexibly adjust the power according to the severity of the voltage deviation, thereby maintaining system stability when the voltage fluctuation is small and avoiding energy waste caused by over-regulation. Based on the bus current and the impedance value of the line, the power loss on the line is calculated and combined with the preset loss weight coefficient to obtain the contribution value of the loss deviation. By accurately calculating the line power loss and assigning a loss coefficient, the energy loss on the line can be accurately reflected, providing a more detailed basis for the regulation strategy. By considering the line loss in the power regulation, the additional loss caused by excessive current can be avoided and the energy allocation can be optimized, improving the overall transmission efficiency of the system.

[0103] This invention calculates the active load fluctuation ratio by the ratio of the active load fluctuation value to the rated load power, and determines the contribution value of active load fluctuation to power regulation based on a preset weighting coefficient. This helps identify the impact of load fluctuation on power demand. The refined active load fluctuation ratio analysis helps identify and respond to large load fluctuations, achieving more precise power regulation. By calculating the active load fluctuation contribution value, the power output of the energy storage system can be rationally allocated. When load fluctuations are large, timely adjustments can be made to meet active load demand, thereby avoiding energy waste and power shortages. The reactive load fluctuation ratio is calculated by the ratio of the reactive load fluctuation value to the rated load power, and the reactive load fluctuation contribution value is calculated based on the reactive power weighting coefficient. Reactive power fluctuation directly affects... Detailed reactive power fluctuation contribution analysis can more accurately identify the specific impact of reactive load fluctuations on voltage, thereby improving regulation precision. By adjusting the reactive power fluctuation contribution value, the system can dynamically adjust reactive power output to ensure grid voltage stability. By comprehensively considering the multiple impacts of voltage, losses, active power fluctuations, and reactive power fluctuations on power regulation, a comprehensive regulation deviation value is obtained, providing an accurate reference for the power regulation of energy storage systems. It can comprehensively evaluate the operating status of energy storage systems in microgrids, ensuring the coordination of power regulation among various links. Through weighted synthesis, the power output of energy storage systems can be precisely adjusted according to the actual impact of different factors, optimizing resource allocation and improving the overall system efficiency and stability.

[0104] In one embodiment, step S4, which dynamically adjusts the initial active power output and initial reactive power output of the energy storage system based on the power regulation deviation value, includes:

[0105] S41. Analyze the relationship between the power regulation deviation value and the preset deviation threshold range;

[0106] S42. If the power regulation deviation value is within the preset deviation threshold range, then the initial active power output and the initial reactive power output remain unchanged.

[0107] S43. If the power adjustment deviation value is greater than the upper limit of the preset deviation threshold range, the total adjustment increment is obtained based on the difference between the power adjustment deviation value and the upper limit value.

[0108] S44. Obtain the active power adjustment increment and reactive power adjustment increment based on the total adjustment increment, and adjust the active power output and reactive power output respectively according to the active power adjustment increment and reactive power adjustment increment.

[0109] S45. If the power adjustment deviation value is less than the lower limit of the preset deviation threshold range, the total adjustment reduction is obtained based on the difference between the lower limit value and the power adjustment deviation value.

[0110] S46. Obtain the active power reduction and reactive power reduction based on the total reduction, and adjust the active power output and reactive power output accordingly based on the active power reduction and reactive power reduction.

[0111] As described in steps S41-S46 above, this invention analyzes the relationship between the power regulation deviation value and the preset deviation threshold range, enabling early judgment of the system's power deviation and helping the system identify whether it has deviated from the normal operating range. If the power regulation deviation value is within the preset safe range, it means that the system's power distribution and grid voltage are already in a relatively ideal state, requiring no adjustment. Maintaining the initial active and reactive power output unchanged can effectively avoid system instability or resource waste caused by frequent adjustments. When the power regulation deviation value is greater than the preset upper limit value, it means that the system has experienced a significant power mismatch, which may lead to excessively low or unstable grid voltage. By calculating the difference between the power regulation deviation value and the upper limit value, a quantitative adjustment increment is achieved, ensuring that the system can adjust quickly and accurately to eliminate the unbalanced state. Compared with the fixed increment adjustment method in the prior art, the setting of dynamic increment can make more flexible adjustments based on the actual power regulation deviation, avoiding the risk of over-adjustment or under-adjustment, thereby significantly improving the grid's adjustment accuracy and response speed.

[0112] When a large power deviation is detected, precise power regulation can be achieved by allocating the total adjustment increment to active and reactive power. By adjusting the output of active and reactive power separately, the system can optimize the operation of the power grid without affecting other parameters. This invention can simultaneously and reasonably adjust active and reactive power, avoiding local over-regulation or insufficient regulation, and ensuring system stability. When the power regulation deviation is less than the lower limit, it indicates that the system's power demand is low. Over-regulation may lead to unnecessary energy loss. By calculating the adjustment reduction based on the difference between the deviation and the lower limit, the adjustment range can be intelligently reduced, avoiding unnecessary... This invention eliminates necessary energy waste while avoiding the risk of excessive energy input, reducing system energy consumption. It can dynamically adjust the reduction based on the actual deviation, ensuring the flexibility and accuracy of the adjustment process, thereby maximizing the system's operating efficiency. By precisely controlling active and reactive power, the system can avoid ineffective power output under low load conditions, improving the system's energy utilization rate, reducing excessive output and unnecessary power loss, and enhancing the long-term economic benefits of the energy storage system. The step-by-step adjustment of this invention can more finely control the output of active and reactive power, avoiding unnecessary resource waste and enhancing the system's adaptability to complex environmental changes.

[0113] In one embodiment, step S5, which generates a local power control curve for the energy storage system based on multiple voltage fluctuation amplitudes and power response delay times, includes:

[0114] S51. Obtain the control sampling frequency and initial operating characteristics of the energy storage system, wherein the initial operating characteristics include initial active power output, initial reactive power output, initial bus voltage and initial response delay;

[0115] S52. Obtain the time step based on the control sampling frequency, and obtain the corresponding real-time update response delay based on the time step, the initial response delay, and the response delay time of each power.

[0116] S51. Obtain the real-time updated active power output based on each real-time update response delay, initial active power output, voltage fluctuation amplitude, and time step; obtain the real-time updated reactive power output based on each real-time update response delay, initial reactive power output, voltage fluctuation amplitude, and time step.

[0117] S54. Establish a three-dimensional coordinate axis of time-active-reactive power with time as the X-axis, active power output as the Y-axis, and reactive power output as the Z-axis. Plot the initial active power output, initial reactive power output, and initial response delay on the three-dimensional coordinate axis of time-active-reactive power as the starting point.

[0118] S55. Plot the real-time updated active power output, real-time updated reactive power output, and real-time updated response delay at the time point corresponding to each time step as connection points on the time-active-reactive three-dimensional coordinate axis.

[0119] S56. Connect the starting point and multiple connection points sequentially through a smooth curve to obtain the local power control curve.

[0120] As described in steps S51-S56 above, the control sampling frequency determines the system's response speed to external changes, while the initial operating characteristics provide an accurate reference value for the starting point of the system state. By controlling the sampling frequency and the initial operating characteristics, the accuracy and real-time performance of subsequent operations are ensured, error accumulation is avoided, and the inaccuracy of energy distribution is reduced. By combining the control sampling frequency and the initial response delay, the calculation method for each power response delay is further refined, generating a real-time updated response delay. The time step, as the system's adjustment frequency, complements the control sampling frequency, ensuring that the system's response to voltage fluctuations is accurate and fast. By updating the response delay in real time, the energy storage system can respond more sensitively to changes in grid power, avoiding the lag caused by fixed delays in existing technologies. The real-time updated active and reactive power outputs are calculated by combining the initial active and reactive power outputs with the voltage fluctuation amplitude. By precisely controlling each power output, the system can achieve accurate response to voltage fluctuations. Through the dynamic adjustment process, the active and reactive power outputs become more adaptable to changes in grid conditions, effectively avoiding the mutual influence between active load demand and reactive power regulation during voltage control, and improving the stability and reliability of the system.

[0121] By constructing a three-dimensional coordinate system, the response and regulation process of the energy storage system becomes visualized, facilitating analysis and optimization. The three-dimensional coordinate axes can more accurately display the interrelationships between various variables. In practical applications, this model can more quickly identify abnormal behaviors in system operation, such as imbalances between active and reactive power outputs and the impact of response delays on the power grid. This enables precise optimization of the energy storage system's regulation strategy. By plotting real-time updated power output and response delays at each time point on the three-dimensional coordinate axes, a dynamic representation of the energy storage system's regulation process is provided. The time-step-based and real-time-updating approach dynamically reflects system changes, allowing the regulation strategy to be tailored to the voltage at each moment. The system can quickly adjust to fluctuations, especially under conditions of drastic voltage changes, better cope with grid fluctuations, avoid uncontrollable anomalies, and improve overall operating efficiency. By smoothly connecting the starting point and multiple connection points in sequence to obtain the local power control curve, it not only graphically displays the power adjustment process of the energy storage system, but also provides a smooth and continuous control strategy in practical applications. This can reduce the burden on the system caused by excessive fluctuations, while ensuring that each power output closely matches the actual needs of the grid. By connecting the curves smoothly, the energy storage system can avoid voltage instability caused by large fluctuations, which helps to achieve more precise voltage regulation and load balancing.

[0122] In one embodiment, step S5, which involves obtaining transient bus voltage data at multiple consecutive moments based on the local power control curve, includes:

[0123] S57. Obtain the power regulation time interval and multiple discrete power control nodes based on the local power control curve, and determine the total acquisition time of the bus voltage transient data based on the power regulation time interval.

[0124] S58. Obtain the voltage data sampling interval based on the total acquisition time and the number of discrete power control nodes, and set the voltage acquisition trigger time based on the sampling interval.

[0125] S59. Obtain the real-time instantaneous voltage value of the microgrid bus according to each voltage acquisition trigger time, and establish a time-voltage-power association table based on the real-time instantaneous voltage value and the power control node at the corresponding trigger time;

[0126] S510. Extract the real-time voltage instantaneous value corresponding to each consecutive time moment according to the time-voltage-power correlation table, and obtain the time series of voltage data based on the real-time voltage instantaneous values ​​of multiple consecutive time moments.

[0127] S511. Filter out the effective voltage data for each consecutive time step according to the time series, and determine the bus voltage transient data for the corresponding time step according to the effective voltage data.

[0128] S512: By iterating through all voltage acquisition trigger times, the transient data of the bus voltage at multiple consecutive times can be obtained.

[0129] As described in steps S57-S512 above, this invention obtains the power adjustment time interval and multiple discrete power control nodes through the local power control curve. This helps the system accurately define the specific time interval and adjustment node of the voltage adjustment moment, enhancing the accuracy and real-time performance of the system adjustment process and reducing unnecessary power fluctuations. The sampling interval of voltage data is determined by the total acquisition time and the number of power control nodes, thereby performing voltage acquisition at each trigger moment, ensuring the efficiency and accuracy of data acquisition. By setting a reasonable sampling interval, unnecessary computational burden caused by excessively frequent sampling is avoided, as well as data loss caused by excessively large sampling intervals. The sampling frequency can be flexibly adjusted according to specific power adjustment requirements and system load status, thereby better reflecting the fluctuation of bus voltage. By establishing a time-voltage-power correlation table by mapping the real-time voltage instantaneous value to the power control node, it helps to accurately track the change pattern of bus voltage under different power adjustment states, thereby helping to identify voltage anomalies that occur during system load or adjustment. This enables real-time capture of voltage data and its combination with power control status, avoiding the disadvantage of decoupling voltage changes from power changes in traditional technologies.

[0130] By extracting instantaneous voltage values ​​from the time-voltage-power correlation table and obtaining the time series of voltage data, the voltage data can be effectively processed in a time series manner, ensuring the continuity and timeliness of voltage changes. Through the real-time instantaneous voltage values ​​at continuous moments, the system can accurately depict the voltage change trend at different points in time, helping to quickly identify voltage anomalies. By filtering valid voltage data, the system ensures that the analysis of voltage changes is based only on real and valid data, rather than noise or invalid data, thereby significantly improving the accuracy of the data and avoiding voltage data distortion caused by interference or noise during the acquisition process. By traversing all voltage acquisition trigger times, more complete voltage fluctuation information can be provided, ensuring that the energy storage system can continuously track the voltage status of the microgrid and promptly detect abnormal fluctuations, greatly improving the real-time performance and accuracy of the voltage regulation process.

[0131] In one embodiment, step S6, which involves obtaining a voltage transient distribution map based on multiple bus voltage transient data and obtaining optimized control parameters based on the voltage transient distribution map, includes:

[0132] S61. Divide the transient data of each bus voltage into multiple data windows according to the time series, and obtain multiple voltage sampling points according to each data window;

[0133] S62. Obtain the voltage change rate and voltage duration for each voltage sampling point, and obtain the standard deviation of the change rate and the average duration for each voltage change rate and voltage duration.

[0134] S63. Obtain the voltage transient correlation degree based on multiple voltage change rates and voltage durations, and construct a voltage stability evaluation matrix based on the voltage transient correlation degree, standard deviation of the change rate, and average duration.

[0135] S64. Obtain eigenvalues ​​and eigenvectors from the voltage stability evaluation matrix, and obtain the voltage stability coefficients from the eigenvalues ​​and eigenvectors.

[0136] S65. Determine whether the voltage stability coefficient is greater than the preset stability threshold.

[0137] S66. If the voltage stability coefficient is greater than the preset stability threshold, the voltage state of the corresponding data window is determined to be stable.

[0138] S67. If the voltage stability coefficient is not greater than the preset stability threshold, the voltage state of the corresponding data window is determined to be unstable, and the corresponding voltage transient distribution spectrum is obtained based on the distribution of multiple stable and unstable states.

[0139] S68. Extract the power control parameters corresponding to each unstable state and the operating parameters of each stable state based on the voltage transient distribution spectrum, and obtain the control parameter correction amount based on multiple power control parameters and operating parameters;

[0140] S69. Optimize and adjust the initial control parameters according to the control parameter correction amount to obtain the optimized control parameters.

[0141] As described in steps S61-S69 above, this invention effectively segments and analyzes voltage change behavior by dividing the bus voltage transient data into multiple data windows according to the time series. This not only helps capture short-term fluctuations in voltage transients but also avoids redundancy in long-term data, improving the accuracy of data analysis. By calculating the voltage change rate and voltage duration at each voltage sampling point, the dynamic characteristics of voltage changes can be further extracted. By calculating the standard deviation of multiple voltage change rates and the average of voltage durations, the stability and periodicity of voltage fluctuations can be quantified. By obtaining the correlation of voltage transients and constructing a voltage stability evaluation matrix, the multidimensional characteristics of voltage fluctuations can be further analyzed. The correlation of voltage transients reflects... The intrinsic relationship between voltage change rate and voltage duration provides a multi-faceted quantitative basis for assessing the impact of voltage transients on power grid stability. By constructing a voltage stability assessment matrix, not only can the amplitude and duration of voltage changes be combined, but other influencing factors on voltage stability, such as system load changes and external disturbances, can also be effectively assessed. Through multi-dimensional correlation analysis, a more accurate and profound judgment on power grid stability is provided, reducing the possibility of misjudgment or omission. By performing eigenvalue and eigenvector analysis on the voltage stability assessment matrix, the complex assessment of voltage stability is further transformed into a voltage stability coefficient, which can provide a scientific basis for whether the voltage is stable, thereby achieving more efficient monitoring and prediction of voltage stability.

[0142] By comparing the voltage stability coefficient with a preset stability threshold, it is possible to effectively determine whether the grid voltage is in a stable state. Comparing the numerical voltage stability coefficient with the set threshold allows for a quick and objective assessment of grid voltage stability, reducing errors from human intervention and facilitating more efficient and intelligent voltage control during grid operation. This enhances the grid's self-regulation capabilities. When the voltage stability coefficient is not greater than the preset threshold, the voltage state is determined to be unstable. Obtaining a voltage transient distribution map based on the distribution of stable and unstable states helps to further refine the analysis of voltage change characteristics. The plotting of the voltage transient distribution map allows for a more detailed analysis of the grid's unstable state. The assessment and positioning of voltage changes provide multi-dimensional voltage variation data, enhancing the precision and accuracy of power grid regulation. By extracting the power control parameters and operating parameters corresponding to each state from the voltage transient distribution map and obtaining the control parameter correction, substantial support can be provided for the optimized control of the power grid, ensuring that the power grid maintains optimal voltage stability during operation. By optimizing and adjusting the control parameters, the optimized control parameters are obtained, enabling the power grid system to maintain optimal voltage stability under different operating conditions. This allows for dynamic adjustment based on real-time data, ensuring that the power grid can maintain efficient and stable operation under complex load conditions, reducing equipment damage and energy waste caused by voltage fluctuations.

[0143] In one embodiment, step S7, which involves obtaining a power-voltage correlation dataset based on a local power control curve and generating a voltage support control model based on the power-voltage correlation dataset and optimized control parameters, includes:

[0144] S71. Obtain the active power control value and reactive power control value corresponding to multiple moments on the local power control curve, and match the bus voltage transient data at the corresponding moments according to the multiple moments.

[0145] S72. Based on the active power control value, reactive power control value and corresponding bus voltage transient data at each moment, an effective power-voltage data pair is formed, and a power-voltage correlation dataset is constructed based on multiple effective power-voltage data pairs.

[0146] S73. Obtain the variation range of power parameters and the stability threshold of voltage parameters in the power-voltage correlation dataset, and determine the input dimension and output target of the preset regression analysis model based on the variation range, stability threshold and optimized control parameters.

[0147] S74. Input a portion of the data from the power-voltage correlation dataset as training samples into the preset regression analysis model, and adjust the model's weight coefficients according to the optimized control parameters.

[0148] S75. Verify the remaining data based on the adjusted model to obtain the verification results, and optimize the model parameters based on the verification results until the model error meets the preset requirements, thus obtaining the voltage support control model.

[0149] As described in steps S71-S75 above, this invention, by acquiring the active and reactive power control values ​​of the local power control curve at multiple moments, can more accurately capture the dynamic changes in grid operation, thereby reflecting the real-time response of the energy storage system under different loads and grid conditions. By matching the transient data of the bus voltage, it can track grid voltage fluctuations in real time, helping to identify voltage anomalies and the rapid response capability of the energy storage system. This allows power control to be quickly adjusted in unstable grid environments, thus avoiding the risks of excessively low or high voltage. Dynamic matching at multiple moments can more comprehensively reflect the adaptability of the energy storage system to grid voltage, improving the system's stability and adaptability under complex grid conditions. By combining the active power control value, reactive power control value, and bus voltage transient data, it can more accurately describe the impact of the energy storage system's power regulation on grid voltage. Effective data pairs provide higher-quality input data for subsequent analysis. Determining the input dimension and output target of the model based on the power-voltage correlation dataset is to ensure the regression analysis. The model can be applied in actual power grid operation. Different input dimensions and output targets can ensure that the model accurately predicts power regulation demand under specific power grid conditions. By obtaining the variation range and stability threshold, it can effectively predict and respond to extreme voltage fluctuations that may occur in the power grid. Setting a reasonable stability threshold is the key to ensuring that the energy storage system can quickly adjust power output and maintain power grid stability when facing large fluctuations in power grid voltage. By inputting training samples into the regression analysis model and adjusting the model's weight coefficients in combination with optimized control parameters, the model's adaptability to the power-voltage relationship under different power grid conditions can be improved, enabling the voltage support control model to adapt to real-time fluctuations in power grid load and ensure that the power grid voltage is within a safe range. By validating the adjusted model and optimizing parameters according to error requirements, the validation results help to detect model deviations in real time and make corrections, ensuring the stability of the system in long-term operation. Through gradual optimization, validation, and adjustment, the model can ensure precise control of the energy storage system and effectively cope with the challenges under various complex power grid conditions.

[0150] like Figure 2 As shown, this application also provides a voltage support control system for an energy storage system in a microgrid, comprising:

[0151] The determination module is used to acquire the basic operating parameters, real-time dynamic status parameters, real-time load change data and initial control parameters of the microgrid, and determine the initial active power and initial reactive power of the energy storage system based on the basic operating parameters and initial control parameters.

[0152] The first acquisition module is used to acquire the initial active power output and initial reactive power output of the corresponding energy storage system based on the initial active power and initial reactive power.

[0153] The second acquisition module is used to acquire the power regulation deviation value based on the real-time dynamic status parameters and real-time load change data;

[0154] The adjustment module is used to dynamically adjust the initial active power output and initial reactive power output of the energy storage system according to the power adjustment deviation value, and to acquire in real time multiple voltage fluctuation amplitudes and power response delay times of the microgrid under different load conditions during the adjustment process.

[0155] The first generation module is used to generate a local power control curve of the energy storage system based on multiple voltage fluctuation amplitudes and power response delay times, and to obtain bus voltage transient data at multiple consecutive moments based on the local power control curve.

[0156] The third acquisition module is used to acquire a voltage transient distribution map based on multiple bus voltage transient data, and to acquire optimized control parameters based on the voltage transient distribution map;

[0157] The second generation module is used to obtain a power-voltage correlation dataset based on the local power control curve, and generate a voltage support control model based on the power-voltage correlation dataset and optimized control parameters, so that the energy storage system can achieve voltage stability support of the microgrid according to the voltage support control model.

[0158] It should be noted that each module and unit in the voltage support control system of the energy storage system in the microgrid corresponds one-to-one with the steps in the voltage support control method of the energy storage system in the microgrid.

[0159] like Figure 3 As shown, this application also provides a computer device, which can be a server, and its internal structure can be as follows: Figure 3 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores all data required for the voltage support control method of the energy storage system in the microgrid. The network interface is used for communication with external terminals via a network connection. When the processor executes the computer program, it implements the voltage support control method of the energy storage system in the microgrid.

[0160] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer equipment on which the present application is applied.

[0161] An embodiment of this application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the voltage support control method of any of the above-described energy storage systems in a microgrid.

[0162] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in this application and in the embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual-speed SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0163] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0164] The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A voltage support control method for an energy storage system in a microgrid, characterized in that, include: Acquire the basic operating parameters, real-time dynamic status parameters, real-time load change data and initial control parameters of the energy storage system of the microgrid, and determine the initial active power and initial reactive power of the energy storage system based on the basic operating parameters and initial control parameters; The initial active power output and initial reactive power output of the corresponding energy storage system are obtained based on the initial active power and initial reactive power. The power regulation deviation value is obtained based on the real-time dynamic status parameters and real-time load change data; The initial active power output and initial reactive power output of the energy storage system are dynamically adjusted according to the power regulation deviation value, and multiple voltage fluctuation amplitudes and power response delay times of the microgrid under different load conditions are obtained in real time during the adjustment process. The local power control curve of the energy storage system is generated based on multiple voltage fluctuation amplitudes and power response delay times, and the bus voltage transient data at multiple consecutive moments are obtained based on the local power control curve. A voltage transient distribution map is obtained based on multiple bus voltage transient data, and optimized control parameters are obtained based on the voltage transient distribution map; The power-voltage correlation dataset is obtained based on the local power control curve, and a voltage support control model is generated based on the power-voltage correlation dataset and optimized control parameters, so that the energy storage system can achieve voltage stability support for the microgrid according to the voltage support control model.

2. The voltage support control method for an energy storage system in a microgrid according to claim 1, characterized in that, The step of determining the initial active power and initial reactive power of the energy storage system based on the basic operating parameters and initial control parameters includes: Acquire basic operating parameters and initial control parameters, wherein the basic operating parameters include the bus rated voltage, load rated power and line impedance value, and the initial control parameters include the initial duty cycle, initial current loop gain and initial voltage loop gain of the energy storage DC / DC converter; The voltage loss coefficient is obtained based on the rated bus voltage and line impedance value, and the rated voltage loss value is obtained based on the voltage loss coefficient and the rated load power. The allowable voltage deviation range is obtained based on the rated voltage loss value and the rated bus voltage, and the voltage control threshold range is determined based on the allowable voltage deviation range. The voltage regulation sensitivity is obtained based on the initial duty cycle and the initial voltage loop gain, and the reactive power regulation range is obtained based on the voltage regulation sensitivity and the voltage control threshold range. The current carrying capacity is obtained based on the initial current loop gain and the rated load power, and the active power adjustment range is obtained based on the current carrying capacity and the reactive power adjustment range. The median value of the active power adjustment range is selected as the initial active power, and the median value of the reactive power adjustment range is selected as the initial reactive power.

3. The voltage support control method for an energy storage system in a microgrid according to claim 1, characterized in that, The step of obtaining the power regulation deviation value based on the real-time dynamic state parameters and real-time load change data includes: Acquire real-time dynamic status parameters and real-time load change data, wherein the real-time dynamic status parameters include real-time bus voltage, real-time bus current and real-time output power of energy storage system, and the real-time load change data includes load active power fluctuation value and load reactive power fluctuation value; The voltage deviation is obtained based on the real-time bus voltage and the rated bus voltage, and the voltage deviation contribution value is obtained based on the voltage deviation and the preset voltage weighting coefficient. The line power loss is obtained based on the real-time bus current and line impedance value, and the loss deviation contribution value is obtained based on the line power loss and the preset loss weighting coefficient. The active load fluctuation ratio is obtained based on the active power fluctuation value and the rated power of the load, and the active power fluctuation contribution value is obtained based on the active load fluctuation ratio and the preset active power weighting coefficient. The reactive load fluctuation ratio is obtained based on the load reactive power fluctuation value and the load rated power, and the reactive power fluctuation contribution value is obtained based on the reactive load fluctuation ratio and the preset reactive power weighting coefficient. The power regulation deviation value is obtained by weighting and summing the voltage deviation contribution value, loss deviation contribution value, active power fluctuation contribution value, and reactive power fluctuation contribution value.

4. The voltage support control method for an energy storage system in a microgrid according to claim 1, characterized in that, The step of dynamically adjusting the initial active power output and initial reactive power output of the energy storage system based on the power regulation deviation value includes: Analyze the relationship between the power regulation deviation value and the preset deviation threshold range; If the power regulation deviation is within the preset deviation threshold range, the initial active power output and the initial reactive power output will remain unchanged. If the power adjustment deviation is greater than the upper limit of the preset deviation threshold range, the total adjustment increment is obtained based on the difference between the power adjustment deviation and the upper limit. The active power adjustment increment and reactive power adjustment increment are obtained according to the total adjustment increment, and the active power output and reactive power output are adjusted accordingly based on the active power adjustment increment and reactive power adjustment increment. If the power regulation deviation is less than the lower limit of the preset deviation threshold range, the total regulation reduction is obtained based on the difference between the lower limit and the power regulation deviation. The active power reduction and reactive power reduction are obtained based on the total reduction, and the active power output and reactive power output are adjusted accordingly based on the active power reduction and reactive power reduction.

5. The voltage support control method for an energy storage system in a microgrid according to claim 1, characterized in that, The step of generating the local power control curve of the energy storage system based on multiple voltage fluctuation amplitudes and power response delay times includes: The control sampling frequency and initial operating characteristics of the energy storage system are obtained, wherein the initial operating characteristics include initial active power output, initial reactive power output, initial bus voltage, and initial response delay; The time step is obtained according to the control sampling frequency, and the corresponding real-time update response delay is obtained according to the time step, the initial response delay, and the power response delay time. The real-time updated active power output is obtained based on each of the real-time update response delay, initial active power output, voltage fluctuation amplitude, and time step; the real-time updated reactive power output is obtained based on each of the real-time update response delay, initial reactive power output, voltage fluctuation amplitude, and time step. With time as the X-axis, active power output as the Y-axis, and reactive power output as the Z-axis, a three-dimensional coordinate axis of time-active power-reactive power is established, and the initial active power output, initial reactive power output, and initial response delay are plotted on the three-dimensional coordinate axis of time-active power-reactive power as the starting point. Plot the real-time updated active power output, real-time updated reactive power output, and real-time updated response delay at each time step point on the time-active-reactive three-dimensional coordinate axis as connection points. By sequentially connecting the starting point and multiple connection points with a smooth curve, a local power control curve is obtained.

6. The voltage support control method for an energy storage system in a microgrid according to claim 1, characterized in that, The step of obtaining a voltage transient distribution map based on multiple bus voltage transient data and obtaining optimized control parameters based on the voltage transient distribution map includes: Each bus voltage transient data is divided into multiple data windows according to the time series, and multiple voltage sampling points are obtained according to each data window; The voltage change rate and voltage duration of each voltage sampling point are obtained, and the standard deviation of the change rate and the average duration are obtained respectively according to the multiple voltage change rates and voltage durations; The voltage transient correlation is obtained based on multiple voltage change rates and voltage durations, and a voltage stability evaluation matrix is ​​constructed based on the voltage transient correlation, the standard deviation of the change rate, and the average duration. The eigenvalues ​​and eigenvectors are obtained from the voltage stability evaluation matrix, and the voltage stability coefficients are obtained from the eigenvalues ​​and eigenvectors. Determine whether the voltage stability coefficient is greater than a preset stability threshold; If the voltage stability coefficient is greater than the preset stability threshold, the voltage state of the corresponding data window is determined to be stable. If the voltage stability coefficient is not greater than the preset stability threshold, the voltage state of the corresponding data window is determined to be unstable, and the corresponding voltage transient distribution map is obtained according to the distribution of multiple stable states and unstable states. Based on the voltage transient distribution map, extract the power control parameters corresponding to each unstable state and the operating parameters of each stable state, and obtain the control parameter correction amount based on multiple power control parameters and operating parameters; The initial control parameters are optimized and adjusted based on the control parameter correction amount to obtain the optimized control parameters.

7. The voltage support control method for an energy storage system in a microgrid according to claim 1, characterized in that, The step of obtaining the power-voltage correlation dataset based on the local power control curve, and generating a voltage support control model based on the power-voltage correlation dataset and optimized control parameters, includes: Based on the local power control curve, obtain the active power control value and reactive power control value corresponding to multiple moments on the curve, and match the bus voltage transient data at the corresponding moment based on the multiple moments. Effective power-voltage data pairs are formed by combining the active power control value, reactive power control value and corresponding bus voltage transient data at each moment, and a power-voltage correlation dataset is constructed based on multiple effective power-voltage data pairs. The range of power parameter variation and the stability threshold of voltage parameter in the power-voltage correlation dataset are obtained, and the input dimension and output target of the preset regression analysis model are determined based on the range of variation, the stability threshold and the optimized control parameters. A portion of the data from the power-voltage correlation dataset is used as training samples and input into a preset regression analysis model, and the weight coefficients of the model are adjusted according to the optimized control parameters. The remaining data are verified using the adjusted preset regression analysis model to obtain the verification results. The model parameters are then optimized based on the verification results until the model error meets the preset requirements, thus obtaining the voltage support control model.

8. A voltage support control system for an energy storage system in a microgrid, characterized in that, include: The determination module is used to acquire the basic operating parameters, real-time dynamic status parameters, real-time load change data and initial control parameters of the microgrid, and determine the initial active power and initial reactive power of the energy storage system based on the basic operating parameters and initial control parameters. The first acquisition module is used to acquire the initial active power output and initial reactive power output of the corresponding energy storage system based on the initial active power and initial reactive power. The second acquisition module is used to acquire the power regulation deviation value based on the real-time dynamic status parameters and real-time load change data; The adjustment module is used to dynamically adjust the initial active power output and initial reactive power output of the energy storage system according to the power adjustment deviation value, and to acquire in real time multiple voltage fluctuation amplitudes and power response delay times of the microgrid under different load conditions during the adjustment process. The first generation module is used to generate a local power control curve of the energy storage system based on multiple voltage fluctuation amplitudes and power response delay times, and to obtain bus voltage transient data at multiple consecutive moments based on the local power control curve. The third acquisition module is used to acquire a voltage transient distribution map based on multiple bus voltage transient data, and to acquire optimized control parameters based on the voltage transient distribution map; The second generation module is used to obtain a power-voltage correlation dataset based on the local power control curve, and generate a voltage support control model based on the power-voltage correlation dataset and optimized control parameters, so that the energy storage system can achieve voltage stability support of the microgrid according to the voltage support control model.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

Images