Mobile energy storage-based substation user voltage out-of-limit governance method and system

Abstract

This invention discloses a method and system for managing voltage exceedances in distribution transformer areas based on mobile energy storage, relating to the field of distribution network operation control. The method includes: identifying user phases based on the correlation between user voltage and transformer low-voltage side voltage; determining end-users based on voltage difference distribution characteristics; constructing an upper bound model of line voltage drop uncertainty based on historical voltage differences between the transformer low-voltage side and end-users; obtaining the local voltage at the connection point; conservatively estimating the end-user voltage based on the upper bound model, ensuring the estimated value is no higher than the actual value; determining the target voltage based on the relationship between the estimated value and the voltage acceptable range; calculating the power command based on the voltage-power sensitivity coefficient; and executing constant power discharge after correcting the power command based on safety constraints. This invention does not rely on distribution transformer topology and intermediate node measurements, forming a positive safety margin through conservative estimation, avoiding the risk of missed detections, and achieving precise closed-loop management of end-user voltage.

Description

Technical Field

[0001] This invention belongs to the field of power distribution network operation and control technology, and in particular relates to a method and system for managing voltage over-limit issues of transformer users based on mobile energy storage. Background Technology

[0002] With the large-scale integration of distributed photovoltaic power generation systems and the continuous improvement of terminal electrification levels, the load characteristics of distribution networks are increasingly exhibiting high volatility and strong uncertainty. Constrained by objective conditions such as long power supply radius, small conductor cross-section, and dispersed end loads, voltage drops caused by line impedance increase significantly during peak summer and winter periods, resulting in frequent voltage drops below the national standard lower limit for end users in the distribution area, seriously affecting the power quality and reliability of users.

[0003] To address the aforementioned voltage exceedance issues, current traditional solutions primarily include: increasing the capacity and location of distribution transformers, upgrading and retrofitting transmission lines, and installing voltage regulators or reactive power compensation devices. However, these methods generally suffer from high investment costs, long construction periods, and difficulties in coordinating land use. Especially for periodic low voltage issues that only occur in specific seasons or short periods, traditional fixed asset investments often face drawbacks such as low equipment utilization and poor economic efficiency, failing to meet the requirements for flexible and efficient operation of the distribution network.

[0004] In recent years, mobile energy storage systems have been gradually applied in the fields of emergency power supply and voltage support in distribution networks due to their mobility, flexibility, and plug-and-play characteristics. Most existing mobile energy storage voltage support strategies employ fixed power injection or simple closed-loop control based on the grid connection point voltage, and typically place the connection point on the low-voltage side of the transformer or at the main busbar. The effective operation of these control methods relies on relatively complete electrical topology information and the availability of voltage measurements near the grid connection point.

[0005] However, in practical engineering, especially in distribution substations with long power supply radii and weak measurement conditions (such as rural substations), mobile energy storage systems often need to extend into the middle of the line to provide local voltage support. However, due to practical difficulties such as the lack of electrical topology records for the substation, the lack of communication conditions at intermediate nodes, and the difficulty in transmitting real-time voltage data from end users, existing technologies struggle to accurately perceive the voltage status of invisible end users. If adjustments are made solely based on the local voltage at the access point, it is highly susceptible to governance failure due to underestimation of the end-user voltage, or overcompensation due to overestimation, thereby affecting the voltage governance effect and system operational safety.

[0006] Therefore, how to construct a safe and effective end-point voltage projection model and achieve accurate and stable power control using only historical data from the beginning and end of the transformer area and local measurement information from the access point, without relying on the complete electrical topology of the transformer area and communication between intermediate nodes, is a key technical challenge that needs to be addressed in the application of mobile energy storage technology in the field of voltage management. Summary of the Invention

[0007] To address the aforementioned deficiencies in existing technologies, the present invention aims to provide a method and system for managing voltage over-limit issues in distribution transformer areas based on mobile energy storage. This solution addresses the problem that mobile energy storage struggles to accurately perceive the voltage status of end users when there is a lack of measurement data at intermediate nodes in the distribution transformer area and complete electrical topology information, leading to poor voltage management results or the risk of overcompensation.

[0008] This invention solves the above-mentioned technical problems through the following technical solution: a method for managing voltage exceedance by transformer substation users based on mobile energy storage, comprising:

[0009] Obtain historical operating data for the distribution area, including at least: the voltage sequence of each phase on the low-voltage side of the transformer in the distribution area, the active power sequence of the distribution area, and the voltage sequence of each user in the distribution area;

[0010] Based on the correlation between the voltage sequences of each user and the voltage sequences of each phase on the low-voltage side of the transformer in the distribution area, the phase to which each user belongs is identified; based on the voltage difference distribution characteristics between the user voltage and the voltage on the low-voltage side of the transformer under the same phase, the end user of that phase is determined.

[0011] Based on the voltage difference information between the low-voltage side of the transformer and the end user in the historical time series, an upper bound model reflecting the uncertainty of line voltage drop is constructed.

[0012] After the mobile energy storage system is connected to the preset access point of the branch where the end user is located, the local voltage of the access point is acquired in real time; based on the upper bound model and the local voltage of the access point, the voltage of the end user is conservatively estimated to obtain the estimated value of the end user voltage; wherein the conservative estimation ensures that the estimated value of the end user voltage is not higher than the actual voltage value of the end user.

[0013] Based on the relationship between the estimated voltage value of the end user and the preset voltage qualified range, the target voltage of the access point is determined, and based on the difference between the target voltage of the access point and the local voltage of the access point, combined with the preset voltage-power sensitivity coefficient, the active power reference command of the mobile energy storage system is calculated.

[0014] The active power reference command is modified based on preset operational safety constraints to generate a constant power discharge command and execute it.

[0015] This invention utilizes only historical operating data of the transformer substation, without relying on complete electrical topology files, to autonomously identify the phase of each user and accurately locate the end user. This provides a clear target for subsequent voltage management and overcomes the technical deficiency of existing technologies that cannot accurately locate management targets due to the lack of topology.

[0016] This invention utilizes only historical voltage data from the first end of the distribution area (low-voltage side of the transformer) and the end user. By constructing an upper bound model that reflects the uncertainty of line voltage drop, it can obtain the voltage extrapolation basis from the access point to the end user without deploying measurement equipment at intermediate nodes of the distribution area or relying on real-time communication. This overcomes the technical defect of existing technologies that cannot sense the end voltage due to the lack of measurement conditions at intermediate nodes.

[0017] This invention employs a conservative estimation mechanism to ensure that the estimated voltage value for end-users is always no higher than the actual value, thus creating a positive safety margin. When the estimated voltage value for end-users triggers a governance threshold, the actual voltage remains no lower than that threshold, fundamentally eliminating the risk of missed detection due to estimation errors and overcoming the governance failure problem caused by inaccurate end-user voltage sensing in existing technologies. The conservatively estimated end-user voltage value is used as the control basis, and the power command is calculated based on the difference between the target voltage and the local voltage, achieving closed-loop regulation of the end-user voltage. Due to the positive safety margin formed by the conservative estimation, the power command will not excessively increase the voltage, overcoming the overcompensation problem caused by overestimation in existing technologies from a control logic perspective.

[0018] This invention incorporates operational safety constraints (including line thermal stability limits, rated power of mobile energy storage systems, and overvoltage protection thresholds at access points) into the power command correction process, ensuring that the output power of the mobile energy storage system does not exceed the safety boundaries of the equipment and lines, thus overcoming the secondary safety risks that may arise from neglecting safety constraints in existing technologies.

[0019] Furthermore, based on the correlation between the voltage sequences of each user and the phase voltage sequences of each phase on the low-voltage side of the transformer substation, the phase to which each user belongs is identified, including:

[0020] For each user's voltage sequence, calculate its Pearson correlation coefficient with the voltage sequences of each phase on the low-voltage side of the transformer in the distribution area; determine the phase to which the user belongs as the phase with the largest Pearson correlation coefficient.

[0021] This invention employs the Pearson correlation coefficient as the specific algorithm for phase identification, utilizing the degree of linear correlation between voltage sequences to determine phase attribution. The Pearson correlation coefficient exhibits good noise immunity and computational stability, enabling accurate identification of the correlation between the user and the voltage of each phase on the low-voltage side of the transformer, even with slight fluctuations in historical data or measurement errors. This improves the accuracy and robustness of phase identification, providing a reliable phase basis for subsequent end-user location.

[0022] Furthermore, based on the voltage difference distribution characteristics between the user voltage and the low-voltage side voltage of the transformer under the same phase, the end users of this phase are determined, including:

[0023] Calculate the first difference sequence between the voltage sequence of each user and the low-voltage side voltage sequence of the transformer in the same phase, and calculate the mean of the first difference sequence. The user with the largest mean is determined as the end user of that phase.

[0024] This invention uses the average voltage difference as the specific criterion for locating end-users. The average voltage difference directly reflects the average level of line voltage drop; the user with the largest average value is the user with the most severe voltage drop in that phase, with clear physical meaning and simple calculation. This location method does not rely on line parameters and topology information; it can accurately identify the user with the highest risk of voltage exceeding limits using only historical voltage data, providing a precise target for mobile energy storage systems.

[0025] Furthermore, based on the voltage difference information between the low-voltage side of the transformer substation and the end user over historical time series, an upper bound model reflecting the uncertainty of line voltage drop is constructed, including:

[0026] For the end user, calculate the second difference sequence between the low-voltage side of the transformer and the end user in the historical time series;

[0027] The second difference sequence is traversed using a sliding window. The quantile of the voltage difference within each sliding window is calculated as the quantile reference value. The robustness of dispersion is calculated based on the median of the voltage difference within each sliding window and the preset system measurement tolerance.

[0028] The quantile benchmark values ​​of each sliding window are concatenated in chronological order to form a quantile benchmark sequence, and the robust dispersion of each sliding window is concatenated in chronological order to form a robust dispersion sequence.

[0029] Based on the quantile reference sequence and the robust dispersion sequence, the upper bound sequence of the line voltage drop uncertainty domain is calculated to form the upper bound model; wherein, the upper bound value of the line voltage drop uncertainty domain corresponding to each sliding window is the sum of the quantile reference value and the robust dispersion of that sliding window.

[0030] This invention uses a sliding window technique to segment historical voltage difference sequences, capturing the time-varying characteristics of line voltage drops at different times. It employs quantiles as benchmark values ​​to reflect voltage drop characteristics at different confidence levels and uses a median-based dispersion index to effectively suppress the impact of outliers on statistical results. The resulting upper bound sequence of the uncertainty domain for line voltage drops dynamically reflects the fluctuation range of line voltage drops, providing a reliable safety boundary for conservative estimation of terminal voltage and improving the accuracy and robustness of voltage estimation.

[0031] Furthermore, the robust dispersion is calculated using the following formula:

[0032] ;

[0033] in, Let be the robustness of the i-th phase within the k-th sliding window; The coefficient of distribution consistency; It is a median function; For user e at the end of phase i, the second difference sequence within the k-th sliding window; This is the preset system measurement tolerance.

[0034] This invention uses the median absolute deviation as the core measure of dispersion, which is more robust to outliers than traditional statistics such as standard deviation. The sensitivity of dispersion is adjusted by the distribution consistency coefficient to adapt to different data distribution characteristics. A preset system measurement tolerance ensures that the dispersion is always positive and avoids abnormal fluctuations caused by measurement noise. The robust dispersion formula achieves robust quantification of the volatility of the second difference sequence, providing an accurate calculation basis for constructing a reliable upper bound model.

[0035] Furthermore, the preset access point is the low-voltage busbar of the branch box of the branch to which the end user belongs; when there is no branch box, the preset access point is the low-voltage switch box busbar of the end pole of the end user branch.

[0036] This invention clarifies the specific access location for the mobile energy storage system. The low-voltage busbar in the branch box is a common electrical node in the distribution network, characterized by convenient access and ample physical space; the low-voltage switch box busbar on the end pole serves as an alternative access point, ensuring engineering feasibility in scenarios without branch boxes. This choice of access location allows the mobile energy storage system to penetrate deep into the middle of the line for local voltage support, shortening the electrical distance for voltage regulation and improving the sensitivity of control response and the effectiveness of voltage control.

[0037] Furthermore, the target voltage at the access point is determined as follows:

[0038] ;

[0039] in, Let be the target voltage at the access point of user e at the end of phase i at time t; Let be the local voltage at the access point of user e at the end of phase i at time t; Let be the voltage estimate of the terminal user e in phase i at time t, i.e., the terminal user voltage estimate. This is the lower limit of the acceptable voltage range; This is a preset dead zone margin.

[0040] This invention uses a piecewise function to determine the target voltage at the access point. When the estimated voltage of the end user is lower than the lower limit of the acceptable voltage range, the target voltage is calculated by adding a voltage deviation compensation (the difference between the lower limit and the estimated value) and a dead zone margin to the local voltage, ensuring that the voltage rise is sufficient to restore the end user voltage to above the acceptable range. When the estimated value is higher than the lower limit of the acceptable voltage range, the target voltage remains unchanged at the local voltage, avoiding unnecessary power output. This control strategy achieves precise start-up and stable operation of voltage regulation, balancing regulation effectiveness and system economy.

[0041] Furthermore, the active power reference command is determined according to the following formula:

[0042] ;

[0043] in, The active power reference command for the terminal user e of phase i at time t; Let be the target voltage at the access point of user e at the end of phase i at time t; Let be the local voltage at the access point of user e at the end of phase i at time t; This is the preset voltage-power sensitivity coefficient.

[0044] This invention employs a linear proportional control method to calculate the active power reference command. A linear mapping relationship between voltage deviation and power output is established through a voltage-power sensitivity coefficient. The control logic is simple and intuitive, facilitating engineering implementation. This formula converts the difference between the control target (target voltage at the access point) and the real-time measurement (local voltage at the access point) into a power command, achieving closed-loop correction of voltage deviation and ensuring the stability and response speed of the control system.

[0045] Furthermore, the active power reference command is modified based on preset operational safety constraints, including:

[0046] Calculate the maximum allowable output power:

[0047] ;

[0048] in, Let be the maximum allowable output power of the i-th phase terminal user e at time t; This refers to the rated power of the mobile energy storage system. This is the upper limit of the allowable current for the line; Let be the local voltage at the access point of user e at the end of phase i at time t; This represents the upper limit of the acceptable voltage range. This is the preset voltage-power sensitivity coefficient;

[0049] The active power reference command is limited and corrected using the maximum allowable output power to obtain the final power command;

[0050] The final power command is executed as a constant power discharge command.

[0051] This invention employs a minimum-value approach to comprehensively consider three types of safety constraints: the first constraint is the rated power of the mobile energy storage system itself, ensuring that the equipment is not overloaded; the second constraint is the line thermal stability limit, which limits the injected power by multiplying the upper limit of the line's allowable current by the local voltage (after unit conversion), ensuring that the line does not experience overcurrent; the third constraint is the overvoltage protection threshold at the access point, which limits the injected power by dividing the difference between the upper limit of the voltage acceptable range and the local voltage by a sensitivity coefficient to prevent the voltage at the access point from exceeding the upper limit. This multi-dimensional constraint correction mechanism ensures that the output power of the mobile energy storage system always remains within the triple safety boundaries of the equipment, line, and voltage, guaranteeing the safety of the governance process.

[0052] Based on the same concept, the present invention also provides a voltage over-limit management system for transformer substation users based on mobile energy storage, including a memory, a processor, and a computer program or instructions stored in the memory. The processor executes the computer program or instructions to implement the voltage over-limit management method for transformer substation users based on mobile energy storage as described above. Attached Figure Description

[0053] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only one embodiment of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0054] Figure 1 This is a flowchart of the method for managing voltage over-limit issues in distribution transformer areas based on mobile energy storage in an embodiment of the present invention;

[0055] Figure 2 This is the end-user voltage curve estimated by combining the uncertainty domain of line voltage drop in this embodiment of the invention;

[0056] Figure 3 This is the active power output curve of the mobile energy storage system in this embodiment of the invention;

[0057] Figure 4 This is a curve showing the change in end-user voltage before and after treatment in an embodiment of the present invention. Detailed Implementation

[0058] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0059] The technical solution of the present invention will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0060] Example 1

[0061] Reference Figure 1 The present invention provides a method for managing voltage exceedance in distribution transformer areas based on mobile energy storage, comprising the following steps:

[0062] Step S1: Obtain historical operation data of the transformer area.

[0063] The historical operating data of the distribution transformer area in this embodiment includes the voltage sequence of each phase on the low-voltage side of the transformer, the active power sequence of the distribution transformer area, and the voltage sequence of each user in the distribution transformer area. This historical operating data comes from the existing electricity consumption information collection system (or distribution automation system) of the distribution transformer area. The data sampling interval is set to 15 minutes, and the historical data time span is selected from the most recent 30 days to cover the operating status of the distribution transformer area under different load levels. The specific collection method is as follows:

[0064] Voltage sequence of each phase on the low-voltage side of the transformer substation: Obtain the voltage sequences of phases A, B, and C from the transformer's low-voltage side master meter (or three-phase voltage monitoring terminal), and denote them as follows. , , , where t is the sampling time.

[0065] Active power sequence of the transformer substation: Obtain the active power sequence of the transformer substation from the low-voltage side master meter, denoted as... .

[0066] Voltage sequences for each user in the distribution area: The voltage sequence for each user is obtained from their smart meters and denoted as follows. , where j is the user ID within the station area.

[0067] To ensure the accuracy of subsequent analysis, the collected raw data underwent cleaning and outlier removal. Specifically, this included:

[0068] Sampling points with missing data or significantly exceeding reasonable ranges (such as voltages below 0.7 times or above 1.2 times the rated voltage) are removed; isolated outliers (such as voltages that recover rapidly after a sudden change) are reconstructed using linear interpolation; time periods with multiple consecutive missing sampling points are directly removed and not included in subsequent calculations.

[0069] Meanwhile, according to the national standard GB / T12325 "Power Quality - Supply Voltage Deviation", a voltage acceptable range is set. In this embodiment, the rated voltage is 220V, therefore the lower limit U of the voltage acceptable range is... min Set to 198V (0.9 times the rated voltage), with the upper limit of the acceptable voltage range U. max Set to 235.4V (1.07 times the rated voltage). This acceptable voltage range will be used for subsequent voltage over-limit judgment and control target setting.

[0070] Step S2: Identify the phase to which each user belongs based on the correlation between the voltage sequence of each user and the voltage sequence of each phase on the low-voltage side of the transformer in the distribution area.

[0071] After completing the data acquisition and preprocessing in step S1, step S2 first identifies the phase to which each user belongs in the distribution area based on the correlation between the voltage sequence of each user and the voltage sequence of each phase on the low-voltage side of the transformer in the distribution area.

[0072] In this embodiment, the Pearson correlation coefficient is used as a quantitative indicator of correlation. For each user within the transformer substation, the correlation coefficient is calculated between their voltage sequence and the three-phase voltage sequences A, B, and C on the low-voltage side of the transformer.

[0073] Taking the j-th user within the transformer area as an example, its voltage sequence is denoted as: The voltage sequence of the i-th phase on the low-voltage side of the transformer is denoted as... , Calculate the Pearson correlation coefficient between the voltage sequence of the j-th user and the voltage sequence of the i-th phase. ;

[0074] Complete three correlation coefficients , , After calculation, the largest one is selected, and the phase to which the j-th user belongs is determined to be the phase corresponding to the largest correlation coefficient.

[0075] For example, the correlation coefficients between a user and phases A, B, and C are calculated to be 0.92, 0.31, and 0.25, respectively. Therefore, the user is determined to belong to phase A. The above calculation and judgment process is repeated for all users within the transformer area to complete phase identification for all users.

[0076] It should be noted that before calculating the correlation coefficient, historical data needs to be timestamped to ensure a strict correspondence between the voltage sequences and the time axis. For cases with minor deviations in sampling times, linear interpolation is used for synchronization. Furthermore, for users whose correlation coefficients are all less than a preset threshold (e.g., 0.8), it indicates that their voltage has a weak correlation with the voltages of each phase on the low-voltage side of the transformer, potentially indicating data quality issues or special electrical connection methods. These users are separately marked and not included in subsequent end-user location calculations.

[0077] Through the above steps, this invention can accurately identify the phase of each user using only historical voltage data without relying on the electrical topology file of the transformer area, providing a reliable phase basis for the subsequent location of end users under the same phase.

[0078] Step S3: Based on the voltage difference distribution characteristics between the user voltage and the low-voltage side voltage of the transformer under the same phase, determine the end user of this phase.

[0079] After completing the user phase identification in step S2, step S3 further determines the end users of each phase based on the voltage difference distribution characteristics between the user voltage and the low-voltage side voltage of the transformer under the same phase. In this embodiment, phases A, B, and C are processed independently, and the same method is used to determine the end users of each phase.

[0080] Taking phase A as an example, assuming there are N users under phase A after phase identification. For each user under phase A, calculate the point-by-point difference between its voltage sequence and the voltage sequence of phase A on the low-voltage side of the transformer to obtain the first difference sequence.

[0081] Specifically, for the j-th user under phase A, its voltage sequence is denoted as... The voltage sequence of phase A on the low-voltage side of the transformer is denoted as... Then the first difference sequence Calculate using the following formula:

[0082] (1)

[0083] Where t = 1, 2, ..., T, and T is the length of the historical voltage sequence (total number of sampling points). The physical meaning of the first difference sequence is the change in line voltage drop from the low-voltage side of the transformer to the j-th user over time. Before calculating the first difference sequence, it is necessary to ensure that the user voltage sequence and the low-voltage side phase voltage sequence of the transformer strictly correspond on the time axis. For cases where there are slight deviations in sampling times, linear interpolation is used for synchronization alignment.

[0084] The first difference sequence is obtained. Then, calculate the mean of the first difference sequence. Average voltage difference This reflects the average voltage drop of the j-th user relative to the low-voltage side of the transformer. Since the voltage drop caused by line impedance increases with the increase of power supply distance, users with a larger average voltage difference have a longer power supply radius and a higher risk of voltage limitation.

[0085] Calculate the average voltage difference for all users under phase A. Then, select the largest one and average the voltage difference. The largest user is identified as end user e in phase A.

[0086] For phases B and C, repeat the above process to determine the end users of phases B and C respectively.

[0087] In this embodiment, there are 5 users under phase A, and the calculated average voltage differences are as follows: User 1: 4.2V, User 2: 5.1V, User 3: 7.8V, User 4: 6.3V, and User 5: 3.9V. Therefore, User 3 (with the largest average voltage difference of 7.8V) is determined as the end user of phase A. Similarly, the end users of phases B and C are determined respectively.

[0088] It should be noted that before calculating the average voltage difference, outlier filtering can be performed on the first difference sequence to remove invalid data points caused by factors such as abnormal data acquisition or power outages, thus avoiding interference with the mean calculation. In this embodiment, the 3σ criterion (i.e., removing data points that deviate from the mean by more than 3 times the standard deviation) is used for outlier processing.

[0089] Through the above steps, this invention can accurately locate the end users of each phase (i.e. the users with the highest risk of voltage exceeding limits) using only historical voltage data without relying on line parameters and electrical topology information, providing a clear governance target for the selection of access locations for mobile energy storage systems and subsequent voltage management.

[0090] Step S4: Based on the voltage difference information between the low-voltage side of the transformer and the end user in the historical time series, construct an upper bound model that reflects the uncertainty of line voltage drop.

[0091] After completing step S3 to identify the end users of each phase, step S4 constructs an upper bound model reflecting the uncertainty of line voltage drop based on the voltage difference information between the low-voltage side of the transformer and the end user over historical time. This upper bound model is used to conservatively estimate the voltage of the end user when mobile energy storage is subsequently connected.

[0092] This embodiment uses Phase A end-users as an example for illustration; the processing methods for Phase B and Phase C end-users are exactly the same. Specifically, it includes the following sub-steps:

[0093] Step S4.1: For the identified A-phase end user (denoted as user e), first calculate its second difference sequence (i.e. voltage difference sequence) in the historical time series.

[0094] Let the voltage sequence of phase A on the low-voltage side of the transformer be: The end-user voltage sequence is Then the second difference sequence Calculate using the following formula:

[0095] (2)

[0096] The second difference sequence reflects the dynamic change of line voltage drop over time from the low-voltage side of the transformer to the end user.

[0097] Step S4.2: Use a sliding window to traverse the second difference sequence described above. The window width W is set according to the data characteristics and control requirements.

[0098] In this embodiment, considering the diurnal periodicity of voltage fluctuations, a window width W = 24 (corresponding to 6 hours) is chosen, and a window sliding step size S = 1 (i.e., moving backward by one sampling point each time). A total of T−W+1 windows are obtained, each containing W consecutive voltage difference data points. For the k-th sliding window (k = 1, 2, ..., T−W+1), the second difference sequence within the window is denoted as... ,Right now:

[0099] (3)

[0100] Step S4.3: For each window, calculate its quantile baseline value. and robust dispersion .

[0101] The quantile reference value is taken as the quantile of the voltage difference within the window, that is: ,in, For the target sequence Quantiles. In this embodiment, . This reflects the high level of line voltage drop in historical data, providing a benchmark for subsequent construction of the upper limit.

[0102] The robustness dispersion is calculated based on the median of the voltage difference within the window and the preset measurement tolerance. The calculation formula is as follows:

[0103] (4)

[0104] in, Let be the robustness of the A-th phase within the k-th sliding window; is the distribution consistency coefficient, used to adjust the sensitivity of dispersion; in this embodiment, it is set to 1.4826. It is a median function; The second difference sequence of user e at the end of phase A within the k-th sliding window; The preset system measurement tolerance is used to compensate for measurement errors and noise; in this embodiment, it is set to 0.5V.

[0105] Robust dispersion uses median absolute deviation (MAD) as its core metric, which is robust to outliers and can robustly reflect the fluctuation range of pressure drop within the window.

[0106] Step S4.4: Set the quantile reference values ​​for each window The quantile reference sequence is formed by concatenating the sequences in chronological order (i.e., in ascending order of window number k). ; the robustness of the dispersion of each window Concatenate them in the same order to form a robust discreteness sequence. .

[0107] Step S4.5: Calculate the upper bound sequence of the uncertainty domain of line voltage drop based on the quantile reference sequence and the robust dispersion sequence.

[0108] For the k-th window, the upper bound of its line voltage drop uncertainty region is... for:

[0109] (5)

[0110] This upper bound represents the highest possible level of line voltage drop in a historically statistical sense, taking into account fluctuation uncertainties and measurement errors. The upper bound values ​​for all windows are... By splicing the sequences in chronological order, we obtain the upper bound sequence of the uncertainty domain for line voltage drop. The upper bound sequence of the uncertainty domain of the line voltage drop is used as the final upper bound model for subsequent conservative estimation of the real-time voltage of end users.

[0111] In the subsequent step S5, after the mobile energy storage system is connected, the corresponding upper bound value is retrieved from the upper bound model based on the time interval to which the current time t belongs. (If the current time t falls within the time interval corresponding to window k, then take) Then, combined with the local voltage at the access point. This allows us to obtain a conservative estimate of the end-user voltage.

[0112] Since the upper bound model reflects the upper limit of the line voltage drop that it may reach, and the conservative estimation ensures that the estimated value is no higher than the actual value, it provides a reliable safety boundary for subsequent closed-loop control. The upper bound model constructed by the above method can dynamically adapt to the changing characteristics of line voltage drop under different seasons and load levels, and does not rely on intermediate node measurements and precise topology parameters, thus exhibiting strong engineering practicality and robustness.

[0113] Step S5: After the mobile energy storage system is connected to the preset access point of the branch where the end user is located, the local voltage of the access point is obtained in real time; based on the upper bound model and the local voltage of the access point, the voltage of the end user is conservatively estimated to obtain the estimated value of the end user voltage.

[0114] After completing step S4 to construct the upper bound model of the uncertainty domain of the line voltage drop, step S5 performs a conservative estimation of the access of the mobile energy storage system and the voltage of the end user. In this embodiment, the mobile energy storage system uses an autonomous mobile energy storage vehicle with a rated power of 50kW. Based on the location of the end user determined in step S3, the mobile energy storage vehicle is connected to a preset access point on the branch where the end user is located. The specific selection of the preset access point is as follows:

[0115] Preferred access point: the low-voltage busbar of the branch box of the branch to which the end user belongs. As a common power distribution device in the power distribution network, the low-voltage busbar of the branch box has sufficient wiring space and good electrical connection conditions, which facilitates the rapid access of mobile energy storage systems.

[0116] Alternative access point: When there is no branch box on the end-user branch, the mobile energy storage vehicle will be connected to the low-voltage switch box busbar on the pole at the end of the branch. This access point is located at the end of the line, close to the end user, and can maximize the voltage support effect.

[0117] In this embodiment, a branch box is provided on the branch where the end user of phase A is located. Therefore, the mobile energy storage vehicle is connected to the low-voltage busbar of the branch box, and the wiring is ensured to be secure and the phases are corresponding (connected to phase A busbar).

[0118] After the mobile energy storage system is connected, it acquires the local voltage at the connection point in real time through its built-in voltage acquisition device (or an external voltage transformer). The sampling period is set to 1 second (adjustable according to control requirements), and the acquired voltage value is recorded as follows. That is, the local voltage of the access point corresponding to the terminal user e of the i-th phase at time t.

[0119] During real-time control, based on the current time t, the corresponding upper bound value of the uncertainty domain of the line voltage drop is retrieved from the upper bound model constructed in step S4. The retrieval method is as follows:

[0120] Since the upper bound model constructed in step S4 is a sequence existing in the form of a sliding window, each window corresponds to a time interval (in this embodiment, the window width is 6 hours, the sliding step size is 1 sampling point, and adjacent windows overlap). For the current time t, first determine its time interval, find the corresponding window index k, and then take the upper bound value of that window. This serves as the upper bound for the current time t. Then, a conservative estimate of the end-user voltage is calculated using the following formula:

[0121] (6)

[0122] in: Let be the voltage estimate of the terminal user e in phase i at time t, i.e., the terminal user voltage estimate. Let be the local voltage at the access point of user e at the end of phase i at time t; Let be the upper bound of the uncertainty domain of the line voltage drop for the terminal user e of phase i at time t.

[0123] The conservative estimation method used in this step aims to ensure that the estimated value does not exceed the actual voltage value of the end user. The specific mechanism is as follows: due to the upper bound of the uncertainty domain of the line voltage drop... This is a voltage drop upper limit constructed based on historical data (meaning the probability that the actual line voltage drop is less than or equal to this upper limit is relatively high). ,in This represents the actual line voltage drop between the low-voltage side of the transformer and the end user at the current moment.

[0124] Due to the local voltage at the access point It equals the transformer's low-voltage side voltage minus the line voltage drop before the connection point, while the actual voltage at the end user... It equals the voltage on the low-voltage side of the transformer minus the total voltage drop across the entire line. Through derivation, we can obtain:

[0125] (7)

[0126] Therefore, the estimated value It should never exceed the actual voltage value of the end user. This creates a positive safety margin. When the estimated value triggers the governance threshold (i.e., When ), the actual voltage It remains no lower than the threshold, thus mitigating the risk of missed judgments due to estimation bias.

[0127] In this embodiment, the local voltage of the access point is collected at a certain moment. The upper bound value of the pressure drop at that moment is retrieved from the upper bound model in step S4. Therefore, the estimated voltage for the end user is 198.3V. This estimated value is slightly higher than the lower limit U of the acceptable voltage range.min =198V indicates that the actual voltage of the end user is still higher than 198V, and voltage regulation will not be initiated for the time being. If the subsequent increase in load leads to an increase in the upper limit of voltage drop or a decrease in local voltage, causing the estimated value to be lower than 198V, then the active power reference command calculation in step S6 will be triggered, and voltage support will be initiated.

[0128] Through the above steps, this invention enables accurate and conservative estimation of end-user voltage using only the local voltage at the access point and a pre-built upper bound model, without relying on real-time measurements by end-users or communication between intermediate nodes, thus providing a reliable control basis for subsequent closed-loop control.

[0129] Step S6: Based on the relationship between the estimated voltage value of the end user and the preset voltage qualified range, determine the target voltage of the access point, and based on the difference between the target voltage of the access point and the local voltage of the access point, combined with the preset voltage-power sensitivity coefficient, calculate the active power reference command of the mobile energy storage system.

[0130] After completing the conservative estimation of the end-user voltage in step S5, step S6 determines the target voltage of the access point based on the relationship between the estimated end-user voltage and the preset voltage acceptable range, and calculates the active power reference command of the mobile energy storage system based on the difference between the target voltage of the access point and the local voltage of the access point, combined with the preset voltage-power sensitivity coefficient.

[0131] First, obtain the estimated end-user voltage value calculated in step S5. And the preset lower limit of the qualified voltage range U min The judgment conditions are as follows:

[0132] like This indicates that there is a risk of the voltage at the end user falling below the lower limit, and voltage management needs to be initiated.

[0133] like This indicates that the voltage at the end user is within the acceptable range and no intervention is required.

[0134] Based on the above judgment results, the target voltage at the connection point... Determined by the following piecewise function:

[0135] (8)

[0136] in To pre-determine the dead zone margin and avoid frequent start-stop of control due to small voltage fluctuations, this embodiment uses 2V.

[0137] when At that time, the target voltage at the access point is superimposed on the local voltage by two items: one is the voltage deviation compensation amount. The first is used to raise the voltage of the end user to the acceptable lower limit; the second is dead zone margin. This restores the end-user voltage to slightly above the acceptable lower limit, preventing the control from being triggered again due to slight fluctuations.

[0138] when When the target voltage at the access point is equal to the local voltage, no voltage boosting is performed, and the mobile energy storage system remains in standby mode or implements a voltage reduction exit strategy.

[0139] After determining the target voltage at the access point, the active power reference command is calculated based on the difference between the target voltage and the local voltage at the access point, combined with the preset voltage-power sensitivity coefficient.

[0140] (9)

[0141] in, The active power reference command (kW) for the i-th phase terminal user e at time t is given, with a positive value indicating discharge; The preset voltage-power sensitivity coefficient represents the voltage change at the access point caused by unit power output.

[0142] Voltage-power sensitivity coefficient The determination method is as follows: Based on the historical operation data of the transformer area, the relationship between the power change and voltage change at the access point is fitted by the linear regression method to obtain... The estimated value. In this embodiment, based on historical data analysis, The value is 0.5V / kW, meaning that for every 1kW increase in power output, the voltage at the connection point increases by 0.5V.

[0143] The active power reference command in this step adopts a proportional control strategy and has the following characteristics:

[0144] The active power reference command is proportional to the voltage deviation, and the sensitivity coefficient is... This reflects the system's voltage response characteristics to power injection, facilitating engineering tuning; using the estimated voltage of the end-user as feedback, a closed-loop control circuit is formed, achieving precise regulation of the end-user voltage; and through dead-time margin... To avoid frequent start-stop operations and improve system stability; due to conservative estimates... ,when When the control is triggered, the actual end-user voltage is still within the safe range, ensuring the rationality of the control action.

[0145] Through the above steps, the present invention achieves closed-loop precise power control based on conservative estimates, effectively avoiding the problems of insufficient control or overcompensation caused by estimation deviations, and providing a reasonable power benchmark for the multidimensional constraint correction in the subsequent step S7.

[0146] Step S7: Based on the preset operating safety constraints, modify the active power reference command, generate a constant power discharge command, and execute it.

[0147] After completing the active power reference command calculation in step S6, step S7 modifies the active power reference command based on preset operational safety constraints, generates a constant power discharge command, and executes it. This step aims to ensure the safe and stable operation of the mobile energy storage system and the connected power lines.

[0148] In this embodiment, the preset operational safety constraints include the following three items:

[0149] Rated power constraint of mobile energy storage system: The maximum sustainable output power of the mobile energy storage system itself is determined by the equipment capacity, denoted as . In this embodiment, the mobile energy storage vehicle has a rated power of 50kW.

[0150] Line thermal stability limit constraints: To ensure that the connected line is not overloaded, the power injected by the mobile energy storage must not exceed the power value corresponding to the upper limit of the line's allowable current. The upper limit of the line's allowable current is denoted as... In this embodiment, the conductor type is LGJ-50, and the maximum allowable current is 200A.

[0151] Access point overvoltage protection threshold constraint: To prevent the access point voltage from exceeding the upper limit of the acceptable voltage range, the injected power is limited based on the difference between the current voltage (i.e., the local voltage at the access point) and the upper limit, as well as the voltage-power sensitivity coefficient, so that the voltage rise does not exceed the upper limit. The upper limit of the acceptable voltage range is denoted as U. max In this embodiment, 235.4V is used.

[0152] Based on the above three constraints, calculate the maximum allowable output power at the current moment. Take the minimum value of the three constraints:

[0153] (10)

[0154] The function of dividing by 1000 in formula (10) is to convert the product of the line allowable current and the local voltage (in W) into kW, so as to keep the unit consistent with the rated power and make it easier to take the minimum value for comparison.

[0155] In the above formula (10), the rated power constraint ensures that the mobile energy storage system does not exceed the rated capacity; the line thermal stability constraint ensures that the injected power does not exceed the thermal stability carrying capacity of the line; and the overvoltage protection constraint ensures that the injected power will not cause the voltage at the access point to exceed the upper limit.

[0156] The maximum allowable output power obtained through calculation The active power reference command obtained in step S6 Perform limiting correction to obtain the final power command. :

[0157] (11)

[0158] like If so, the active power reference command remains unchanged; if Then restrict it to Ensure that the output power does not exceed the safety limit.

[0159] The revised final power command The constant power discharge command for the current control cycle is sent to the power converter of the mobile energy storage system for execution. The mobile energy storage system outputs active power in constant power mode according to this command to provide voltage support at the connection point.

[0160] During operation, the mobile energy storage system continuously monitors the voltage at the access point. Once the voltage at the access point exceeds the preset overvoltage protection threshold (i.e., ...), the system will take action. Immediately stop discharging and issue an alarm signal to ensure system safety.

[0161] During the operation of a mobile energy storage system, when the local voltage at the access point is monitored to remain stable for a preset time period (e.g., 5 minutes), and the estimated voltage of the end user is higher than the lower limit of the voltage qualification range and remains stable, a step-by-step power reduction exit strategy is implemented: the output power is gradually reduced in preset steps (e.g., 5kW) until the output power reaches zero and discharge stops. This strategy ensures a smooth transition during the voltage support process, avoids voltage fluctuations caused by sudden power outages, and further improves the smoothness of system operation.

[0162] Through step S7, this invention quantifies multi-dimensional operational safety constraints (system rated power, line thermal stability, and overvoltage protection) into the maximum allowable output power and performs amplitude limiting correction on the active power reference command, ensuring that the output power of the mobile energy storage system is always within the safety boundary, while simultaneously achieving smooth execution of the constant power discharge command. This step effectively ensures the safety of the voltage regulation process and avoids secondary safety risks caused by power injection.

[0163] To verify the effectiveness and safety of the method proposed in this invention, a simulation model of a typical rural power distribution area was constructed for testing. The simulation parameters were set as follows:

[0164] The distribution transformer capacity is set at 200kVA with a transformation ratio of 10kV / 0.4kV; the line length is approximately 800m, the conductor type simulates the LGJ-50 commonly used in rural areas, the rated power of the mobile energy storage system is set at 50kW, the connection location is set at the middle section of the line approximately 500m away from the distribution transformer in the substation, and the voltage over-limit period for end users is set at 19:30-20:30.

[0165] Figures 2 to 4 The simulation results for this simulation scenario are shown. Figure 2 To estimate the end-user voltage by incorporating the uncertainty domain of line voltage drop, Figure 3 The active power output curve of the mobile energy storage system. Figure 4 The voltage change curves of end users before and after the treatment.

[0166] Depend on Figure 2 It can be seen that during periods not exceeding the lower limit, the estimated voltage of end-users is consistently lower than the actual voltage, and the two show the same trend. During periods exceeding the lower limit, the estimated voltage of end-users remains near the acceptable range, and is higher than the actual voltage at all times. This indicates that the estimated voltage of end-users consistently provides a certain safety margin for the actual voltage, mitigating overcompensation caused by low voltage estimates and undercompensation caused by high voltage estimates. This provides a robust benchmark for calculating the active power reference command of mobile energy storage systems, thus effectively supporting the management of voltage exceeding limits in distribution areas.

[0167] Figure 3 The solid lines in the diagram represent the actual voltage at the end user, while the dashed lines represent the estimated voltage at the end user. Figure 3 As can be seen, the dashed line representing the estimated voltage of the end-user is always below the solid line representing the actual voltage of the end-user; the region between them constitutes the constructed positive safety margin. The mechanism for this positive safety margin is as follows: the upper bound model of the line voltage drop uncertainty domain constructed in step S4 makes... Thus ensuring .

[0168] Depend on Figure 4 It can be seen that during the period when mobile energy storage is not outputting (i.e. before governance), the voltage of end users continues to drop and enters the lower limit range; after the mobile energy storage is connected (i.e. after governance), the voltage of end users rises back to above the lower limit of the voltage qualified range, indicating that the method of the present invention can effectively govern the problem of voltage exceeding the lower limit of end users.

[0169] Therefore, it can be seen that the method of the present invention provides a conservative estimate of the terminal voltage, ensuring that even when the specific parameters of the line are unknown, the estimated value will trigger the governance threshold (i.e., When the actual voltage is still higher than the threshold, the mechanism effectively avoids the risk of missed judgment due to estimation bias.

[0170] The simulation results above fully verify the effectiveness and safety of the method of the present invention: Figure 2 The method of the present invention has been verified to effectively address the problem of voltage exceeding limits at end users; Figure 3The positive safety margin formed by the conservative estimation mechanism was verified, thus mitigating the risk of missed detection from a mechanistic perspective. In summary, the method of this invention achieves accurate sensing and closed-loop management of end-user voltage without relying on the electrical topology information of the transformer area or real-time measurements of intermediate nodes, and has good engineering practical value.

[0171] Example 2

[0172] This invention also provides a voltage over-limit management system for transformer substation users based on mobile energy storage. The system includes a memory, a processor, and a computer program or instructions stored in the memory. The processor executes the computer program or instructions to implement the voltage over-limit management method for transformer substation users based on mobile energy storage in this invention.

[0173] Although not shown, the system includes a processor that can perform various appropriate operations and processes based on programs and / or data stored in read-only memory (ROM) or loaded from a storage portion into random access memory (RAM). The processor can be a multi-core processor or may contain multiple processors. In some embodiments, the processor may include a general-purpose main processor and one or more specialized coprocessors, such as a central processing unit, graphics processing unit (GPU), neural network processor (NPU), digital signal processor (DSP), etc. Various programs and data required for device operation are also stored in the RAM. The processor, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0174] The processor and memory described above are used together to execute programs / instructions stored in the memory. When the program / instructions are executed by the computer, they can implement the methods, steps, or functions described in the above embodiments.

[0175] The above description only discloses specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or modifications that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for managing voltage exceedance issues in distribution transformer areas based on mobile energy storage, characterized in that, The method includes: Obtain historical operating data for the distribution area, including at least: the voltage sequence of each phase on the low-voltage side of the transformer in the distribution area, the active power sequence of the distribution area, and the voltage sequence of each user in the distribution area; Based on the correlation between the voltage sequences of each user and the voltage sequences of each phase on the low-voltage side of the transformer in the distribution area, the phase to which each user belongs is identified; based on the voltage difference distribution characteristics between the user voltage and the voltage on the low-voltage side of the transformer under the same phase, the end user of that phase is determined. Based on the voltage difference information between the low-voltage side of the transformer and the end user in the historical time series, an upper bound model reflecting the uncertainty of line voltage drop is constructed. After the mobile energy storage system is connected to the preset access point of the branch where the end user is located, the local voltage of the access point is acquired in real time; based on the upper bound model and the local voltage of the access point, the voltage of the end user is conservatively estimated to obtain the estimated value of the end user voltage; wherein the conservative estimation ensures that the estimated value of the end user voltage is not higher than the actual voltage value of the end user. Based on the relationship between the estimated voltage value of the end user and the preset voltage qualified range, the target voltage of the access point is determined, and based on the difference between the target voltage of the access point and the local voltage of the access point, combined with the preset voltage-power sensitivity coefficient, the active power reference command of the mobile energy storage system is calculated. The active power reference command is modified based on preset operational safety constraints to generate a constant power discharge command and execute it.

2. The method for managing voltage exceedances in distribution transformer areas based on mobile energy storage according to claim 1, characterized in that, Based on the correlation between the voltage sequences of each user and the phase voltage sequences of each phase on the low-voltage side of the transformer substation, the phase to which each user belongs is identified, including: For each user's voltage sequence, calculate its Pearson correlation coefficient with the voltage sequences of each phase on the low-voltage side of the transformer in the distribution area; determine the phase to which the user belongs as the phase with the largest Pearson correlation coefficient.

3. The method for managing voltage exceedances in distribution transformer areas based on mobile energy storage according to claim 1, characterized in that, Based on the voltage difference distribution characteristics between the user voltage and the low-voltage side voltage of the transformer under the same phase, the end users of this phase are determined, including: Calculate the first difference sequence between the voltage sequence of each user and the low-voltage side voltage sequence of the transformer in the same phase, and calculate the mean of the first difference sequence. The user with the largest mean is determined as the end user of that phase.

4. The method for managing voltage exceedances in distribution transformer areas based on mobile energy storage according to claim 1, characterized in that, Based on the voltage difference information between the low-voltage side of the transformer and the end user over historical time periods, an upper bound model reflecting the uncertainty of line voltage drop is constructed, including: For the end user, calculate the second difference sequence between the low-voltage side of the transformer and the end user in the historical time series; The second difference sequence is traversed using a sliding window. The quantile of the voltage difference within each sliding window is calculated as the quantile reference value. The robustness of dispersion is calculated based on the median of the voltage difference within each sliding window and the preset system measurement tolerance. The quantile benchmark values ​​of each sliding window are concatenated in chronological order to form a quantile benchmark sequence, and the robust dispersion of each sliding window is concatenated in chronological order to form a robust dispersion sequence. Based on the quantile reference sequence and the robust dispersion sequence, the upper bound sequence of the line voltage drop uncertainty domain is calculated to form the upper bound model; wherein, the upper bound value of the line voltage drop uncertainty domain corresponding to each sliding window is the sum of the quantile reference value and the robust dispersion of that sliding window.

5. The method for managing voltage exceedances in distribution transformer areas based on mobile energy storage according to claim 4, characterized in that, The robustness of dispersion is calculated using the following formula: ； in, Let be the robustness of the i-th phase within the k-th sliding window; The coefficient of distribution consistency; It is a median function; For user e at the end of phase i, the second difference sequence within the k-th sliding window; This is the preset system measurement tolerance.

6. The method for managing voltage exceedances in distribution transformer areas based on mobile energy storage according to claim 1, characterized in that, The preset access point is the low-voltage busbar of the branch box of the branch to which the end user belongs; when there is no branch box, the preset access point is the low-voltage switch box busbar of the end pole of the end user branch.

7. The method for managing voltage exceedances in distribution transformer areas based on mobile energy storage according to claim 1, characterized in that, The target voltage at the access point is determined as follows: ； in, Let be the target voltage at the access point of user e at the end of phase i at time t; Let be the local voltage at the access point of user e at the end of phase i at time t; Let be the voltage estimate of user e at the end of phase i at time t; This is the lower limit of the acceptable voltage range; This is a preset dead zone margin.

8. The method for managing voltage exceedances in distribution transformer areas based on mobile energy storage according to claim 1, characterized in that, The active power reference command is determined according to the following formula: ； in, The active power reference command for the terminal user e of phase i at time t; Let be the target voltage at the access point of user e at the end of phase i at time t; Let be the local voltage at the access point of user e at the end of phase i at time t; This is the preset voltage-power sensitivity coefficient.

9. The method for managing voltage exceedance in distribution transformer areas based on mobile energy storage according to any one of claims 1 to 8, characterized in that, The active power reference command is modified based on preset operational safety constraints, including: Calculate the maximum allowable output power: ； in, Let be the maximum allowable output power of the i-th phase terminal user e at time t; This refers to the rated power of the mobile energy storage system. This is the upper limit of the allowable current for the line; Let be the local voltage at the access point of user e at the end of phase i at time t; This represents the upper limit of the acceptable voltage range. This is the preset voltage-power sensitivity coefficient; The active power reference command is limited and corrected using the maximum allowable output power to obtain the final power command; The final power command is executed as a constant power discharge command.

10. A voltage over-limit management system for transformer substation users based on mobile energy storage, comprising a memory, a processor, and a computer program or instructions stored in the memory, characterized in that, The processor executes the computer program or instructions to implement the method for managing voltage over-limit issues of transformer substation users based on mobile energy storage as described in any one of claims 1 to 9.

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