Control method and system for global power supply quality reconstruction of transformer area with long power supply radius

Abstract

The invention relates to the field of power system distribution network load adjustment, and discloses a control method and system for global power supply quality reconstruction of a long-power-supply-radius transformer district, and the method comprises the steps: calculating the capacity and position of a device based on voltage and distance parameters; collecting data to execute fuzzy control, and adjusting the electric energy flow direction; when the voltage is lower than a threshold value, closed-loop regulation is started to compensate a voltage gap; the power is adjusted on hour, and a rolling optimization strategy is executed; power is adjusted according to real-time data, and electric energy quality is guaranteed; the system comprises a voltage acquisition module, a voltage gap analysis module, an energy storage state monitoring module, a time monitoring module, a control module, an energy storage system and a photovoltaic power generation system. The SOC deviation calibration strategy based on the on-hour rolling mechanism is introduced, the target energy storage electric quantity dynamic comparison and power correction function is combined, the system operation state can be adjusted in real time in each on-hour period, and the electric quantity matching precision and strategy self-consistency in the operation process are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of load regulation of power system distribution networks, and in particular to a control method and system for reconstructing the global power supply quality in a long power supply radius area. Background Art

[0002] With the rapid integration of distributed power sources, various new loads, and energy storage devices into distribution networks, power quality issues in low-voltage substations are becoming increasingly prominent. This is particularly true in areas with long power supply distances and severe voltage drops at the end. Voltage overshoots, frequent fluctuations, and deteriorating power transmission stability are becoming increasingly apparent. In a typical radial power supply architecture, local voltage fluctuations are difficult to effectively manage through master-station-level control due to long branch lines, strong load fluctuations, and uneven distribution.

[0003] Existing global power quality reconstruction control technologies often employ centralized strategies, whereby substations or master station systems perform centralized analysis based on real-time voltage data to trigger corresponding energy storage charging and discharging operations. These methods typically set upper and lower thresholds, for example, initiating discharge when the monitored voltage falls below a fixed value and charging when it rises above another set value, thereby achieving coarse regulation of the substation voltage.

[0004] However, the existing global power supply quality reconstruction control technology lacks the ability to be deployed in a refined manner. It is difficult to accurately configure capacity according to parameters such as the geographical topology, cable paths, and voltage drop characteristics of different substations, resulting in large deviations in the layout of energy storage devices, or insufficient power or waste of costs. Secondly, this upper and lower limit triggering logic is prone to response delays or frequent jumps when the voltage fluctuates critically, and the adjustment continuity is poor. Therefore, the present invention provides a control method and system for global power supply quality reconstruction in long power supply radius substations to address the shortcomings of the prior art. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the present invention provides a control method and system for reconstructing the global power supply quality in a long power supply radius substation, which solves the problems of extensive energy storage capacity configuration, delayed voltage response, limited adjustment granularity and lack of state closed-loop control in the existing global power supply quality reconstruction technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a control method for reconstructing the global power supply quality in a long power supply radius area, comprising the following steps: Calculate the capacity and installation location of the power quality optimization device at each installation point based on the user's minimum voltage, the voltage drop percentage of the substation cable model, the distance from the installation point to the substation transformer, and the estimated duration of the voltage gap; Collect real-time voltage data, current time, and percentage of remaining energy storage capacity, and execute the energy flow fuzzy adaptive control algorithm based on the collected data to adjust the flow of electric energy; Based on the collected voltage data, when the voltage is lower than the preset threshold, the voltage lower limit gain closed-loop adjustment monitoring strategy is activated to compensate for the voltage gap; At every hour, the charging and discharging power is adjusted according to the difference between the real-time energy storage capacity and the preset energy storage capacity, and the hourly rolling optimization strategy is implemented; According to the real-time voltage collection value, energy storage capacity and target voltage value, the charging and discharging power is dynamically adjusted to ensure the power quality within the specified charging and discharging period.

[0007] Preferably, the calculation of the capacity and installation location of the power quality optimization device at each installation point comprises the following steps: Based on the user's minimum voltage and the voltage drop percentage of the cable model, obtain the impact of the cable model on the voltage by consulting the power distribution manual and calculate the voltage gap: ; in, is the power gap, is the voltage gap, is the voltage drop influence coefficient corresponding to the cable model; The calculation capacity gap is used as the energy value required by the energy storage system: ; in, is the duration of the voltage gap, The energy gap, The power gap.

[0008] Preferably, the step of adjusting the direction of electric energy flow comprises the following steps: Collect voltage data in real time and adjust charging and discharging power according to voltage fluctuations; Dynamically adjust the charge and discharge power of the energy storage system based on the difference between the collected voltage and the set target voltage value; When the voltage value is lower than the set threshold, the energy storage discharge power is adjusted through fuzzy control algorithm instructions.

[0009] Preferably, the starting voltage exceeding the lower limit gain closed-loop regulation monitoring strategy includes the following steps: Interrupt the main voltage fuzzy control strategy and start the gain closed-loop control strategy; According to the relationship between voltage gap and power compensation, the compensation power is adjusted by the gain coefficient: ; in, is the power compensation coefficient required for each 1V voltage gap, To compensate for power, Voltage gap; When the voltage returns to above the set threshold, the closed-loop regulation strategy is exited and the main voltage control strategy is restored.

[0010] Preferably, executing the hourly rolling optimization strategy includes the following steps: At every hour, compare the difference between the real-time collected energy storage power and the preset ideal energy storage power value; According to the difference ,in is the state difference, is the percentage of energy storage system power currently collected, Dynamically adjust the charging and discharging power of the energy storage device according to the target energy storage percentage set by the system; Power compensation is performed by adjusting the multiplication factor to ensure that the energy storage system operates within the optimal range.

[0011] Preferably, the dynamic adjustment of charge and discharge power includes the following steps: According to the real-time voltage and the set target voltage value, the voltage difference is calculated and fuzzy control is performed; During the charging period, if the voltage is higher than the negative small threshold, charging is started and the charging power is dynamically adjusted according to the voltage difference; During the discharge period, if the voltage is lower than the positive threshold, the discharge is started and the discharge power is dynamically adjusted according to the voltage difference.

[0012] Preferably, the charge and discharge power is calculated using the following formula: ; in, is the charge and discharge power, is the current voltage, Target voltage, is the current state of charge of the energy storage system, Based on voltage and Dynamic function of state, controlling charging and discharging power.

[0013] Preferably, the charging period is 8:00-18:00, the discharging period is 18:00-8:00, and the energy storage system During the charging period, the battery is charged from 5% to 95%, and during the discharging period, the battery is discharged from 95% to 5%.

[0014] It also provides a control system for reconfiguring the power supply quality of the entire area in a long power supply radius area, including: The voltage acquisition module is used to collect voltage data from each installation point in the substation in real time, calculate the voltage gap and voltage fluctuation based on the collected voltage information, and generate a voltage gap report; The voltage gap analysis module is used to analyze the voltage gap based on the voltage data and calculate the power gap at each installation point based on the voltage drop coefficient of the cable model and the transmission distance; The energy storage status monitoring module dynamically calculates the charging or discharging requirements of the energy storage device based on real-time voltage data and power gap data, monitors the remaining power percentage of the energy storage device, and outputs energy storage compensation instructions based on the difference between the preset target power value and the current remaining power; The time monitoring module is used to monitor the current time, provide time period information according to different time periods, and trigger hourly optimization and strategy adjustments; The control module executes the energy flow fuzzy adaptive control algorithm based on the power gap data, the remaining energy storage capacity and time period information provided by the energy storage status monitoring module; The energy storage system adjusts the charge and discharge power of the energy storage device according to the regulation instructions output by the control module; The photovoltaic power generation system works in conjunction with the energy storage system to provide electricity according to grid demand and power generation period. The photovoltaic system's power generation and output energy are regulated based on the decisions and strategy adjustments of the control module.

[0015] The present invention provides a control method and system for reconfiguring the power supply quality of a long-radius power supply area. It has the following beneficial effects: 1. This invention introduces an SOC deviation calibration strategy based on an hourly rolling mechanism. Combined with dynamic comparison of target energy storage capacity and a power correction function, it can adjust the system operating state in real time within each hourly cycle. This approach breaks through the passive scheduling method of "preset capacity unchanged, state lagging correction" in traditional energy storage control, significantly improving the power matching accuracy and strategy consistency during operation, and effectively avoiding the regulation offset problem caused by accumulated SOC errors.

[0016] 2. This invention utilizes a dynamic voltage deviation gain adjustment method, enabling the system to continuously fine-tune charge and discharge power within millisecond cycles, adjusting power accordingly for every 1V voltage deviation, achieving flexible response. Compared to existing stage-threshold-triggered discharge strategies, this design solves the problems of regulation lag and discontinuous control, making it particularly suitable for weak voltage nodes with frequent fluctuations in typical substations.

[0017] 3. This invention quantitatively models physical parameters such as the distance from the installation point to the transformer, the percentage of voltage drops, and the cable type. It further incorporates voltage-power influencing factors for precise capacity allocation, thereby constructing a local optimization model for distributed management of substations. This eliminates the reliance on uniformly configured capacity or simple empirical parameters, effectively overcoming the drawbacks of existing solutions, which rely on extensive deployment that is not tailored to the specific location.

[0018] 4. This invention uses a fuzzy algorithm to regulate power, immediately switching to a rigid gain compensation response upon exceeding limits. This system can flexibly transition between tight and loose springs, enhancing the stability and disturbance immunity of the control strategy, something that is difficult to achieve with traditional single-control models. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a flow chart of the method steps of the present invention; Figure 2 This is a system architecture diagram of the present invention. DETAILED DESCRIPTION

[0020] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the present specification. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0021] Please see the attached Figure 1 The embodiment of the present invention provides a control method for reconfiguring the global power supply quality in a long power supply radius area, comprising the following steps: S1. Calculate the capacity and installation location of the power quality optimization device at each installation point based on the user's minimum voltage, the voltage drop percentage of the substation cable model, the distance from the installation point to the substation transformer, and the estimated duration of the voltage gap; S2, collects real-time voltage data, current time and percentage of remaining energy storage capacity, and executes energy flow fuzzy adaptive control algorithm based on the collected data to adjust the flow of electric energy; S3. Based on the collected voltage data, when the voltage is lower than the preset threshold, the voltage lower limit gain closed-loop adjustment monitoring strategy is started to compensate for the voltage gap; S4. At every hour, the charging and discharging power is adjusted according to the difference between the real-time energy storage capacity and the preset energy storage capacity, and the hourly rolling optimization strategy is implemented; S5. Dynamically adjust the charge and discharge power according to the real-time voltage acquisition value, energy storage capacity and target voltage value to ensure the power quality within the specified charging and discharging period.

[0022] In step S1, in this embodiment, it is necessary to determine whether each installation site has the basic conditions for deploying energy storage and power quality optimization devices. Generally, locations where terminal voltage is prone to fluctuation are preferred as device deployment points to maximize their optimization benefits, including specific technical solutions in the following aspects: In one possible implementation, the minimum operating voltage of the installation point is obtained through actual measurement or scheduling data. At the same time, according to the type of cable used in the power supply line of the substation where the point is located, the unit voltage drop influence factor corresponding to the type of cable is obtained from the distribution system standard manual or engineering experience library. , that is, the voltage increase per unit distance for every 1kW of power injected (usually expressed in V / km·kW).

[0023] Specifically, the distance between the installation point and the transformer in the substation needs to be obtained. , in meters, is usually extracted through GIS system or distribution geographic information system. In addition, in order to estimate the demand for compensation energy when the load is in a long-term undervoltage state, it is also necessary to evaluate the duration of the voltage gap. , in hours, can be statistically averaged based on historical operating data.

[0024] According to the above parameters, first calculate the voltage gap value: ; in, The lower limit of the qualified power supply voltage specified by the power grid, for example, it can be set to 198V in a 220V system, the unit is volt (V); The lowest voltage value in history or actually measured at the installation point.

[0025] Based on the voltage impact factor of the cable line, the power gap can be calculated as follows: ; in, Indicates the active power required to compensate under this voltage gap (unit: kW); Indicates the influence coefficient of the cable type used on the voltage (unit: V / km·kW); the coefficient of 0.5 reflects the calculation method of the average path length of the injected power from the transformer to the midpoint. Continue to calculate the capacity gap (i.e. the required energy compensation): ; in, Indicates the total compensation energy required (unit: kWh), Indicates the duration of undervoltage.

[0026] As an option, the construction of distributed photovoltaic devices can be further evaluated based on the photovoltaic resource situation. For example, if the local effective sunshine time is 4 hours per day and a photovoltaic array with a capacity of 5kW is installed, the theoretical daily power generation capacity it can provide is: ; in, is the rated power of the photovoltaic array, The length of available sunshine.

[0027] In some embodiments, for example, a typical remote installation point has a minimum voltage of 190V, is 500 meters away from the transformer, uses an aluminum core cable with a diameter of 35mm, and assumes that the average duration of the voltage gap is 2 hours. Substituting into the above formula, we can get: ; ; in, is the power gap, which indicates the electric power that needs to be compensated due to insufficient voltage; Voltage gap, i.e. ; is the cable influence coefficient, which is 1.7358 here, corresponding to a 35mm² aluminum core cable (determined according to the cable model manual); Power shortage; The duration of the voltage gap is 2 hours here.

[0028] Based on this, an on-site power quality optimization device consisting of 5kW photovoltaic + 10kW / 20kWh energy storage can be configured to meet the power supply quality compensation needs of the installation point.

[0029] As an extended implementation method, in order to improve configuration accuracy, the user load curve and daily load fluctuation coefficient can be combined to appropriately adjust the equipment capacity redundancy rate and reserve redundant energy for extreme operating conditions.

[0030] In addition, to facilitate batch deployment and operation and maintenance management, a substation model can be built in advance through a digital simulation platform during the configuration process to evaluate the load, voltage change trends and cable impedance characteristics of each node, so as to assist in optimizing the scientific nature of equipment layout and capacity allocation strategies.

[0031] Regarding step S2, in this embodiment, after completing the capacity configuration of the device installation point, in order to achieve dynamic adjustment of the voltage response capability, it is necessary to introduce an energy flow control mechanism with adaptive regulation capability. As the core path to achieve this goal, the charging and discharging behavior of the energy storage system is dynamically adjusted based on the actual collected operating status data, so that the voltage stability control strategy has real-time response capabilities and is dynamically coupled with the energy storage margin.

[0032] The operating behavior of the energy storage system is driven by voltage data, and its control logic is based on the following variables: In one possible implementation, the system continuously collects the real-time voltage value and compares it with the set target voltage value to obtain the current voltage deviation. , the expression is: ; in, Indicates the measured voltage value at the current installation point, in volts (V); Indicates the system preset voltage reference value, generally 198V or the user-specified reference voltage.

[0033] Combined with the current energy storage remaining capacity SOC (State of Charge), this step calculates the power value that the current energy storage system should output or absorb in real time by establishing a dynamic control function This function comprehensively considers voltage error and remaining capacity conditions to ensure the physical feasibility and strategic effectiveness of charge and discharge behavior. The expression is as follows: ; in, The current charging power (positive) or discharging power (negative) required to be adjusted, in kilowatts (kW); It is a dynamic adjustment function under multiple input conditions, which is constructed by fuzzy control algorithm or interval linear function; is the percentage of energy storage system power currently collected, The target energy storage capacity percentage set for the system.

[0034] In general, this function has the following characteristics: when and When , the system enters the discharge mode, and the output power is positively correlated with the voltage difference; when and When the system allows charging, it absorbs excess power and suppresses overvoltage; when When the battery reaches the critical value, the system will gradually limit the charge and discharge rate to avoid overcharge / overdischarge faults.

[0035] As an option, in order to prevent malfunction in the fluctuation area, a dead zone setting can be introduced in the function design. interval, in Maintain power output constant or close to zero, thereby reducing invalid frequent adjustments.

[0036] Specifically, the system can also set sub-strategies based on the voltage-time-energy triple parameter space in different time periods: For example, during the main charging phase between 08:00 and 18:00, if Above 205V, the charging process starts; During the main discharge period from 18:00 to 08:00, if If the voltage is lower than 225V, the discharge function will be activated; If the voltage exceeds the upper target value (such as 230V), even in the discharge period, a short energy absorption process is allowed to be started to suppress the sudden high voltage phenomenon.

[0037] In some embodiments, after performing the power calculation, the system also performs secondary processing of the power adjustment limit to avoid hardware failure caused by the calculation result exceeding the rated power range of the device. This limit is expressed as: ; in, It is the maximum charge and discharge capacity boundary value of the device; is the charge and discharge power after final limitation.

[0038] In specific implementation, the regulation instructions are issued through the PCS power control unit or inverter manager, converted into PWM control or current control signals, and act on the power path of the energy storage system, thereby achieving scheduling-level power response.

[0039] For step S3, in this embodiment, in order to further improve the system's response accuracy and regulation strength to low-voltage abnormalities, the present invention embeds a voltage over-limit gain closed-loop regulation mechanism in the strategy structure. When the voltage fluctuation seriously deviates from the qualified power supply lower limit threshold, it quickly switches to the strong control mode and instantly compensates for the voltage gap through closed-loop gain regulation to prevent continuous voltage instability.

[0040] The closed-loop gain adjustment monitoring strategy includes the following: In one possible implementation, the system continuously monitors the current voltage value , when it is lower than the set threshold When the voltage exceeds the lower limit (such as 201V), the voltage fuzzy control main strategy is immediately interrupted and the voltage enters the lower limit gain closed-loop adjustment monitoring mode.

[0041] In general, the threshold The setting is slightly higher than the minimum qualified voltage of the national standard to ensure that there is a response lead time and improve the robustness of the system.

[0042] Specifically, the gain closed-loop strategy is based on the current voltage gap As well as the corresponding power compensation relationship at the device installation point, the required compensation power is calculated using the following formula: ; in, Indicates the current compensation power to be output (unit: kW); , is the real-time voltage gap (unit: V), where The target voltage for qualified power supply, such as 198V; The actual voltage value currently collected; It is the power compensation coefficient corresponding to the unit voltage gap (unit: kW / V). This coefficient is a preset value for the project and is predetermined based on factors such as line impedance, cable type, and access location. It reflects the physical relationship of "compensation power required for each 1V drop".

[0043] In some embodiments, the gain factor Multi-point calibration can be performed based on the distance between the installation point and the transformer, the cross-section of the line conductor, and the material. For example, if the installation point uses a 35mm diameter aluminum core wire at a distance of 500m, and the table shows that each 1kW injection can increase the voltage by 1.7358V, then the reverse calculation is: ; This coefficient can also be dynamically modified based on historical operating data to enhance adjustment accuracy.

[0044] As an option, the policy can introduce an output rate adjustment factor , to buffer the impact of power mutation on the equipment: ; in, Indicates the current compensation power to be output; Indicates the actual output power value; It is a real number factor, usually fine-tuned between 0.8 and 1.2, to facilitate the correction of the adjustment range according to the on-site fluctuation trend.

[0045] When the system operates under this closed-loop strategy, it will continuously detect If the continuous monitoring results show that , it is considered that the voltage has returned to the qualified range, and the system automatically exits the closed-loop gain strategy and resumes running the fuzzy control main strategy.

[0046] To avoid frequent switching causing policy oscillation, exit criterion hysteresis logic can be introduced, for example, requiring that the system be exited only after three consecutive sampling cycles are met or the voltage is kept stable for 1 minute.

[0047] In addition, in some extended implementation methods, this strategy can be linked with the fault recording module. When the closed-loop strategy is triggered continuously for more than a certain number of times, a low-voltage management record of the substation area is automatically generated for subsequent analysis.

[0048] Regarding step S4, in this embodiment, after completing the preliminary deployment of the user's minimum voltage analysis, the cable type of the substation, the voltage drop percentage, and the energy storage device capacity configuration, in order to further improve the dynamic adaptability of the system during operation, it is necessary to implement a periodic review and correction of the charging and discharging behavior of the energy storage system, thereby alleviating the voltage response strategy in the long-term operation due to load changes, voltage reference drift or Response bias caused by error accumulation.

[0049] The hourly rolling optimization strategy specifically includes the following technical processes: In one possible implementation, the system sets every hour (such as 00:00, 01:00, etc.) as the dispatch optimization benchmark time. The system will automatically collect the SOC (State of Charge) of the current energy storage device at this time, which is recorded as , and synchronously call the target SOC value preset by the system in the previous period, recorded as The difference is calculated based on the deviation between the actual value and the target value: ; in, is the current state deviation (unit: %); The percentage of energy storage power collected at the current moment; The system pre-sets the target energy storage percentage, which can take typical values such as 60%, 70%, etc. according to different substation configurations.

[0050] Generally speaking, if , that is, the current energy storage capacity is less than the target value, and the system needs to compensate by increasing the charging power. On the contrary, if , it means that there is a surplus of energy storage capacity, which needs to be released appropriately to improve the response redundancy.

[0051] Specifically, the charge and discharge power correction value It can be calculated by the following formula: ; in, is the adjustment value of charge and discharge power (unit: kW); It is the dispatching proportional factor (unit: kW / %), which is dynamically set according to the equipment capacity and response period, and generally ranges from 0.1 to 1.5.

[0052] As an option, It can be determined by the following empirical model: ; in is the rated charge and discharge power of the energy storage device (unit: kW), so that every 1% deviation can be adjusted to 1% of the rated power.

[0053] In order to avoid short-term power deviations causing policy fluctuations, a “slow-release correction function” can be introduced to limit the power adjustment range. Its expression is: ; in is the power limit threshold (unit: kW) to prevent the correction strategy from exceeding the system's safe operation boundary; is the final adjusted output power; is the power adjustment result before correction.

[0054] In some embodiments, the system also uses a rolling window mechanism to calculate the number of consecutive hourly periods. Fitting analysis is performed on the changing trend. If the continuous deviation direction is consistent, the system will improve weights to achieve faster convergence; if the deviation direction repeats, the correction strength is weakened to prevent strategy oscillation.

[0055] In addition, the system can also be combined with the grid load forecast model to moderately increase the load 1-2 hours before the peak load. , appropriately lower the target during the trough period , in order to cooperate with the main voltage response strategy to adjust the rhythm and achieve internal and external coordination of charging and discharging scheduling.

[0056] For step S5, in this embodiment, on the basis of completing strategies such as substation-level voltage monitoring, energy storage device configuration, energy flow control and hourly calibration, in order to further improve the system's dynamic response accuracy and real-time adjustment capability under conditions of slight voltage fluctuations, it is necessary to introduce a dynamic charge and discharge power adjustment strategy based on a voltage deviation closed-loop mechanism, using the voltage error as the adjustment driving factor to achieve slight and sensitive adjustment of the charge and discharge power of the energy storage device within a continuous period, thereby realizing dual closed-loop response control of voltage and power.

[0057] The strategy for dynamically adjusting charge and discharge power includes the following: In one possible implementation, the system first sets the target voltage value The value can be set according to the power supply standard, such as 198V. The system also collects the current voltage value at a frequency of not less than 1Hz. , and calculate the voltage deviation in real time: ; in, is the real-time voltage difference (unit: V); The current voltage collected in real time (unit: V); is the target voltage setting value (unit: V).

[0058] Based on the above difference, the system determines whether the current operating state is in a state that requires adjustment, which is divided into the charging adjustment stage and the discharging adjustment stage. In general: like , that is, the current voltage is significantly higher than the target value, and the system enters the charging regulation stage; like , that is, the current voltage is lower than the target value, and the system enters the discharge regulation stage; like , the system does not make any adjustments and maintains the current power state.

[0059] in is the deviation dead zone value (unit: V), usually 0.5V or 1V, used to prevent frequent adjustments. During the charging stage, the power regulation value is given by the following formula: ; During the discharge phase, the power regulation value is: ; in, They are the current adjusted charging power and discharging power (unit: kW); They are respectively the charging regulation gain and the discharging regulation gain (unit: kW / V), which are generally calibrated by experiments and set according to the voltage sensitivity coefficient of the installation point and the response speed of the energy storage device. The common value range is .

[0060] Specifically, if the voltage is in a "slight overvoltage" state, such as higher than the target value but not exceeding 220V, then A smaller value can be used for slow charging; if the voltage deviates seriously, such as higher than 225V, the system will automatically increase , quickly absorb energy and suppress overvoltage.

[0061] As an option, adjust the gain It can also be adjusted dynamically according to SOC. The specific expression is: ; ; in, is the basic gain (unit: kW / V); The above dynamic coefficient adjustment strategy can effectively avoid overcharging or over-discharging, and improve the overall response flexibility of the system.

[0062] In some embodiments, to cope with sudden voltage disturbances or short-term load disturbances, the system can set a response delay time threshold When the voltage deviation exceeds the set threshold continuously for more than When the power consumption is less than 3 seconds (e.g. 3 seconds), power adjustment is started to reduce frequent power changes caused by peak fluctuations.

[0063] In addition, the system can also introduce an adjustment rate limiting mechanism, that is, setting a maximum adjustment step for the power change per unit time. , whose expression is: ; in, 、 The power values for the current and previous cycles (unit: kW) are adjusted respectively. It is the maximum adjustment range, usually set at 5%-10% of the rated power.

[0064] The control system for reconstructing the global power supply quality in a long power supply radius area described below and the control method for reconstructing the global power supply quality in a long power supply radius area described above can be referred to each other.

[0065] Please see the attached Figure 2 The present invention also provides a control system for reconstructing the global power supply quality in a long power supply radius area, comprising: The voltage acquisition module is used to collect voltage data from each installation point in the substation in real time, calculate the voltage gap and voltage fluctuation based on the collected voltage information, and generate a voltage gap report; The voltage gap analysis module is used to analyze the voltage gap based on the voltage data and calculate the power gap at each installation point based on the voltage drop coefficient of the cable model and the transmission distance; The energy storage status monitoring module dynamically calculates the charging or discharging requirements of the energy storage device based on real-time voltage data and power gap data, monitors the remaining power percentage of the energy storage device, and outputs energy storage compensation instructions based on the difference between the preset target power value and the current remaining power; The time monitoring module is used to monitor the current time, provide time period information according to different time periods, and trigger hourly optimization and strategy adjustments; The control module executes the energy flow fuzzy adaptive control algorithm based on the power gap data, the remaining energy storage capacity and time period information provided by the energy storage status monitoring module; The energy storage system adjusts the charge and discharge power of the energy storage device according to the regulation instructions output by the control module; The photovoltaic power generation system works in conjunction with the energy storage system to provide electricity according to grid demand and power generation period. The photovoltaic system's power generation and output energy are regulated based on the decisions and strategy adjustments of the control module.

[0066] The system of this embodiment can be used to execute the above method embodiments, and its principles and technical effects are similar, so they will not be repeated here.

[0067] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A control method for reconfiguring the global power supply quality in a long power supply radius area, characterized in that: The following steps are involved: Calculate the capacity and installation location of the power quality optimization device at each installation point based on the user's minimum voltage, the voltage drop percentage of the substation cable model, the distance from the installation point to the substation transformer, and the estimated duration of the voltage gap; Collect real-time voltage data, current time, and percentage of remaining energy storage capacity, and execute the energy flow fuzzy adaptive control algorithm based on the collected data to adjust the flow of electric energy; Based on the collected voltage data, when the voltage is lower than the preset threshold, the voltage lower limit gain closed-loop adjustment monitoring strategy is activated to compensate for the voltage gap; At every hour, the charging and discharging power is adjusted according to the difference between the real-time energy storage capacity and the preset energy storage capacity, and the hourly rolling optimization strategy is implemented; According to the real-time voltage collection value, energy storage capacity and target voltage value, the charging and discharging power is dynamically adjusted to ensure the power quality within the specified charging and discharging period.

2. The control method for reconfiguring the global power supply quality in a long power supply radius area according to claim 1 is characterized in that: Calculating the capacity and installation location of the power quality optimization device at each installation point includes the following steps: Based on the user's minimum voltage and the voltage drop percentage of the cable model, obtain the impact of the cable model on the voltage by consulting the power distribution manual and calculate the voltage gap: ； in, is the power gap, is the voltage gap, is the voltage drop influence coefficient corresponding to the cable model; The calculation capacity gap is used as the energy value required by the energy storage system: ； in, is the duration of the voltage gap, The energy gap, The power gap.

3. The control method for reconfiguring the global power supply quality in a long power supply radius area according to claim 1, characterized in that: The regulating of the electric energy flow comprises the following steps: Collect voltage data in real time and adjust charging and discharging power according to voltage fluctuations; Dynamically adjust the charge and discharge power of the energy storage system based on the difference between the collected voltage and the set target voltage value; When the voltage value is lower than the set threshold, the energy storage discharge power is adjusted through fuzzy control algorithm instructions.

4. The control method for reconfiguring the global power supply quality in a long power supply radius area according to claim 1 is characterized in that: The starting voltage over-lower limit gain closed-loop regulation monitoring strategy comprises the following steps: Interrupt the main voltage fuzzy control strategy and start the gain closed-loop control strategy; According to the relationship between voltage gap and power compensation, the compensation power is adjusted by the gain coefficient: ； in, is the power compensation coefficient required for each 1V voltage gap, To compensate for power, Voltage gap; When the voltage returns to above the set threshold, the closed-loop regulation strategy is exited and the main voltage control strategy is restored.

5. The control method for reconfiguring the global power supply quality in a long power supply radius area according to claim 1 is characterized in that: Executing the hourly rolling optimization strategy includes the following steps: At every hour, compare the difference between the real-time collected energy storage power and the preset ideal energy storage power value; According to the difference ,in is the state difference, is the percentage of energy storage system power currently collected, Dynamically adjust the charging and discharging power of the energy storage device according to the target energy storage percentage set by the system; Power compensation is performed by adjusting the multiplication factor to ensure that the energy storage system operates within the optimal range.

6. The control method for reconfiguring the global power supply quality in a long power supply radius area according to claim 1, characterized in that: The dynamic adjustment of charge and discharge power comprises the following steps: According to the real-time voltage and the set target voltage value, the voltage difference is calculated and fuzzy control is performed; During the charging period, if the voltage is higher than the negative small threshold, charging is started and the charging power is dynamically adjusted according to the voltage difference; During the discharge period, if the voltage is lower than the positive threshold, the discharge is started and the discharge power is dynamically adjusted according to the voltage difference.

7. The control method for reconfiguring the global power supply quality in a long power supply radius area according to claim 3 is characterized in that: The charge and discharge power is calculated using the following formula: ； in, is the charge and discharge power, is the current voltage, Target voltage, is the current state of charge of the energy storage system, Based on voltage and Dynamic function of state, controlling charging and discharging power.

8. The control method for reconfiguring the global power supply quality in a long power supply radius area according to claim 6, characterized in that: The charging period is 8:00-18:00, the discharging period is 18:00-8:00, and the energy storage system During the charging period, the battery is charged from 5% to 95%, and during the discharging period, the battery is discharged from 95% to 5%.

9. A control system for reconstructing the power supply quality of a long power supply radius area, characterized in that: include: The voltage acquisition module is used to collect voltage data from each installation point in the substation in real time, calculate the voltage gap and voltage fluctuation based on the collected voltage information, and generate a voltage gap report; The voltage gap analysis module is used to analyze the voltage gap based on the voltage data and calculate the power gap at each installation point based on the voltage drop coefficient of the cable model and the transmission distance; The energy storage status monitoring module dynamically calculates the charging or discharging requirements of the energy storage device based on real-time voltage data and power gap data, monitors the remaining power percentage of the energy storage device, and outputs energy storage compensation instructions based on the difference between the preset target power value and the current remaining power; The time monitoring module is used to monitor the current time, provide time period information according to different time periods, and trigger hourly optimization and strategy adjustments; The control module executes the energy flow fuzzy adaptive control algorithm based on the power gap data, the remaining energy storage capacity and time period information provided by the energy storage status monitoring module; The energy storage system adjusts the charge and discharge power of the energy storage device according to the regulation instructions output by the control module; The photovoltaic power generation system works in conjunction with the energy storage system to provide electricity according to grid demand and power generation period. The photovoltaic system's power generation and output energy are regulated based on the decisions and strategy adjustments of the control module.

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