Double-layer voltage cooperative control method for high-proportion distributed photovoltaic access power distribution network

Abstract

The invention relates to the technical field of power grid operation and maintenance, in particular to a double-layer voltage cooperative control method of a high-proportion distributed photovoltaic access power distribution network, which comprises the following steps of: deploying a centralized control unit and a distributed local control unit in the power distribution network; dividing the time period of each day into a plurality of centralized control time periods, wherein two adjacent centralized control time periods are continuous; in each centralized control time period, the centralized control unit executes centralized control for one time based on a total optimization target to carry out optimized voltage regulation; and dividing each centralized control time period into a plurality of continuous local control time periods. According to the embodiment of the invention, on the basis of double-layer voltage cooperative control, through multi-time multi-scale cooperation of hour-level centralized optimization and five-minute-level local correction, and in combination with a rudder equipment cooperative voltage regulation strategy, the service life protection of voltage precise control box equipment can be effectively realized under the condition of considering global and local conditions; and a cooperative target of power loss minimization and voltage compliance is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power grid operation and maintenance, in particular to a double-layer voltage collaborative control method for a power distribution network with high proportion of distributed photovoltaic access. BACKGROUND

[0002] With the increasing proportion of photovoltaic distributed generation in low-voltage distribution networks, the intermittent characteristics of photovoltaic power generation bring severe challenges to voltage stability control of distribution networks. Traditional voltage control devices such as capacitor banks and on-load voltage regulating transformers are difficult to adapt to the dynamic adjustment requirements under high photovoltaic penetration due to their slow response speed and frequent operation which shortens their service life. There is a lack of multi-time scale coordination strategies that take into account global optimization and local correction. Meanwhile, traditional optimization algorithms are prone to local optimization when dealing with mixed integer nonlinear programming problems of distribution networks, and it is difficult to achieve the collaborative goal of power loss minimization and voltage compliance. SUMMARY

[0003] In view of the deficiencies in the prior art, the present application provides a double-layer voltage collaborative control method for a power distribution network with high proportion of distributed photovoltaic access. Based on double-layer voltage collaborative control, the method can effectively achieve precise voltage control and device life protection, and achieve the collaborative goal of power loss minimization and voltage compliance by combining multi-time multi-scale coordination of hour-level centralized optimization and five-minute-level local correction, and collaborative voltage regulation strategies of pilot devices, while taking into account the global and local situations.

[0004] The above application objectives of the present application are achieved by the following technical solutions: A double-layer voltage collaborative control method for a power distribution network with high proportion of distributed photovoltaic access, comprising the following steps: Deploying a centralized control unit and a distributed local control unit in the power distribution network; Dividing the time period of each day into a plurality of centralized control time periods, and the adjacent two centralized control time periods are continuous; In each centralized control time period, the centralized control unit performs centralized control optimization for voltage regulation based on a total optimization target; Dividing each centralized control time period into a plurality of continuous local control time periods; In each local control time period, the local control unit performs local control optimization for voltage regulation based on the total optimization target.

[0005] Optionally, after the centralized control unit performs centralized control, the optimized control variables are transmitted to the local control unit; After the local control unit performs local control, the results are fed back to the centralized control unit to update the optimization base parameters of the next time period.

[0006] Optionally, the total optimization target is to minimize a comprehensive cost including a power loss cost and a device life operation and maintenance cycle cost. The centralized control unit and the local control unit optimize based on the total optimization target, and meet a power balance constraint condition of the power distribution network, a voltage amplitude constraint condition of the power distribution network, and a device constraint condition.

[0007] Optionally, the device constraint condition includes a load tap changer constraint condition, a capacitor bank combination constraint condition, a photovoltaic inverter reactive power constraint condition, and a battery energy storage system key constraint condition.

[0008] Optionally, the centralized control includes: acquiring and inputting data of a node system of the power distribution network, and predicted node load and photovoltaic output data; forming a power flow constraint of a node of the power distribution network, and constructing a linearized flow model; setting a SSA population size, a maximum iteration number, a guard ratio, and a variable dimension parameter, and an optimization variable of each individual including a load tap changer tap, a capacitor bank combination switching step, a photovoltaic inverter reactive power, a battery energy storage system charging and discharging power, and a battery energy storage system reactive power; based on the iteration number, outputting an optimal control parameter combination of the load tap changer, the capacitor bank combination, the photovoltaic inverter, and the battery energy storage system.

[0009] Optionally, the acquiring of the data of the node system of the power distribution network includes: acquiring load prediction data of the power distribution network through a SCADA system; acquiring photovoltaic output prediction data through communication of an irradiance intensity sensor and a photovoltaic inverter.

[0010] Optionally, the local control includes: accepting a control variable setting of the centralized control; acquiring a node voltage; judging whether the node voltage is out of limit; when the node voltage is out of limit, executing a photovoltaic inverter and battery energy storage system adjustment strategy.

[0011] Optionally, the local control further includes: dividing a voltage deviation level according to the acquired node voltage; determining a photovoltaic inverter and battery energy storage system adjustment strategy according to the voltage deviation level; adjusting the photovoltaic inverter and battery energy storage system according to the photovoltaic inverter and battery energy storage system adjustment strategy; judging whether a constraint test is passed; when the constraint test is not passed, continuing to divide the voltage deviation level.

[0012] Optionally, the local control further comprises: when the voltage deviation unit value does not exceed 0.01, a regulation strategy of no action of the photovoltaic inverter and the battery energy storage system is executed; when the voltage deviation unit value exceeds 0.01 and does not exceed 0.03, a regulation strategy of photovoltaic inverter regulation of reactive power and no action of the battery energy storage system is executed; when the voltage deviation unit value exceeds 0.03 and does not exceed 0.05, a regulation strategy of battery energy storage system dominant regulation of active power and photovoltaic inverter auxiliary regulation of reactive power is executed; when the voltage deviation unit value exceeds 0.05, a regulation strategy of battery energy storage system full power regulation and photovoltaic inverter maximum reactive regulation is executed, and a next period centralized control correction benchmark is triggered.

[0013] The embodiment of the application further provides a double-layer voltage collaborative control system of a high-proportion distributed photovoltaic access power distribution network, which is used for executing the double-layer voltage collaborative control method of the high-proportion distributed photovoltaic access power distribution network. a centralized control unit, configured to execute power distribution network centralized control, control of the on-load voltage regulating transformer, the capacitor combination, the photovoltaic inverter and the battery energy storage system; a local control unit, configured to execute local control, control of the photovoltaic inverter and the battery energy storage system; a communication unit, configured to communication of the centralized control unit and the local control unit.

[0014] In summary, the application has the following beneficial technical effects: The embodiment of the application is based on double-layer voltage collaborative control, and through multi-time multi-scale collaboration of hour-level centralized optimization and five-minute-level local correction, combined with the collaborative voltage regulation strategy of the rudder device, the voltage accurate control and the rudder device life protection can be effectively realized in the case of considering the global and local, and the collaborative target of power loss minimization-voltage compliance is realized. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 is a DLVCC architecture flowchart schematic diagram of the application; Figure 2 is a centralized control flowchart schematic diagram of the application; Figure 3 is a local control flowchart schematic diagram of the application; Figure 4 is an IEEE-33 node power distribution network simulation model schematic diagram of the application; Figure 5 is a convergence effect comparison schematic diagram of SSA and other algorithms of the application; Figure 6is a voltage comparison diagram of the node 17 before and after local control. DETAILED DESCRIPTION

[0016] The following description will be made in conjunction with the accompanying drawings as follows Figures 1-6 The application will be further described in detail.

[0017] In order to more clearly understand the technical solutions exhibited by the embodiments of the application, first, the problems existing in the existing power distribution network containing high proportion of photovoltaic treatment are simply introduced.

[0018] With the continuous increase of the proportion of photovoltaic distributed power generation in low-voltage power distribution network, the intermittent characteristics of its output bring severe challenges to the voltage stability control of the power distribution network. The traditional voltage control equipment such as CBs (capacitor bank) and OLTC (onload tap changing transformer) has been difficult to adapt to the dynamic adjustment demand under high photovoltaic penetration rate due to slow response speed, frequent operation and short service life. The centralized control dominated by traditional equipment needs to frequently adjust OLTC and CBs, far beyond the mechanical life. If there is an extreme voltage deviation, PVI (photovoltaic inverter) cannot adjust the voltage, and needs to wait for 1 hour to adjust the traditional equipment, resulting in long voltage out-of-limit duration, single voltage adjustment dimension, and failure at load peak or trough: all rely on "reactive power regulation", and lack active power regulation means. At night without photovoltaic, reactive power regulation of PV inverter can easily lead to voltage surge; at the evening load peak, the effect of reactive power injection is weak, and the voltage is easy to be lower than the lower limit, PVI has high reactive power pressure and high loss, at noon photovoltaic peak, photovoltaic active power is high, reactive power capacity of inverter is compressed, and it cannot cope with large voltage rise, long-term high reactive power load will also shorten the service life of inverter, photovoltaic curtailment rate is high, and economic efficiency is poor: in order to avoid voltage rise, photovoltaic active power needs to be reduced at noon, which wastes resources; distributed control may overcurtail power generation due to lack of global planning, and reduces power generation income; In addition, VVC (voltage coordinated control) focuses on the active power injection of PV (photovoltaic) power generation, does not fully tap the potential of reactive power regulation of photovoltaic inverter, and lacks a multi-time scale coordination strategy that takes into account "hourly global optimization-hourly local correction", and the traditional optimization algorithm is easy to fall into local optimum when dealing with mixed integer nonlinear programming problems of power distribution network, and it is difficult to achieve the coordinated goal of "minimum power loss-voltage compliance".

[0019] To ensure that the high photovoltaic proportion power distribution network maintains voltage stability in the allowable range of 0.95-1.05pu in the whole period, while realizing the maximization reduction of active power and reactive power loss, and effectively prolonging the service life of various voltage control devices in the power distribution network, a DLVCC (dual-layer voltage coordinated control) method considering the continuity of multiple constraints of devices, multi-time scale coordination, and taking into account the calculation efficiency and physical interpretability is needed.

[0020] Based on this, the embodiment of the application provides a dual-layer voltage coordinated control method for a high-proportion distributed photovoltaic access power distribution network, comprising the following steps: S101: deploying a centralized control unit arranged in a centralized manner and a plurality of local control units arranged in a distributed manner in the power distribution network, the centralized control unit controlling the on-load voltage regulating transformer, the capacitor bank, the photovoltaic inverter and the battery energy storage system, and the local control unit controlling the photovoltaic inverter and the battery energy storage system; S102: dividing the time period of each day into a plurality of centralized control time periods, the adjacent two centralized control time periods being continuous, that is, dividing the 24 hours of each day into a plurality of centralized control time periods, the adjacent two centralized control time periods being continuous in time, in the embodiment of the application, each centralized control time period is set to one hour, to realize hour-level offline optimization; S103: in each centralized control time period, the centralized control unit performs centralized control optimization based on the total optimization target; S104: dividing each centralized control time period into a plurality of continuous local control time periods, in the embodiment of the application, each local control time period is set to five minutes, to realize five-minute-level online optimization; S105: in each local control time period, the local control unit performs local control optimization based on the total optimization target.

[0021] Overall, the embodiment of the application can effectively realize voltage accurate control and device life protection, and realize the coordinated goal of power loss minimization-voltage compliance, by hour-level centralized optimization and five-minute-level local correction of multi-time multi-scale coordination based on dual-layer voltage coordinated control, combined with rudder device coordinated voltage regulation strategy, while taking into account the global and local conditions.

[0022] It should be understood that the offline and online states described in the embodiments of this application do not describe the on-grid status. Offline and online refer to whether or not the system is disconnected from the real-time operation system of the power grid. Offline optimization by the centralized control unit means that the centralized control unit selects the optimal control scheme in advance based on prediction and historical data. It is relatively separated from the real-time system and does not rely on the real-time operation data of the distribution network. The calculation process is physically or logically isolated from the real-time control system. Online optimization is to access the power grid operation data in real time and dynamically adjust the control scheme. Online means to be synchronized with the real-time operation system of the power grid and directly participate in real-time control. It accesses the real-time monitoring system of the power grid and obtains real-time data at the second and minute levels, including load changes, equipment status, power flow distribution, etc. The calculation process is synchronized with the power grid operation status and can quickly respond to instantaneous fluctuations in the power grid, such as sudden load changes or sudden changes in the output of new energy sources. It can directly issue real-time control commands to the power grid equipment, forming a closed loop of data acquisition-calculation optimization-command execution.

[0023] As a feasible specific implementation of the present application, when the centralized control unit and the local control unit optimize based on the overall optimization objective, they satisfy the power balance constraint condition of the distribution network, the voltage amplitude constraint condition of the distribution network, and the equipment constraint condition. The overall optimization objective is to minimize the comprehensive cost, including the power loss cost and the equipment life maintenance cycle cost. The mathematical expression for the overall optimization objective is: In the formula: Indicates the overall system cost; This represents the cost of line losses; it also considers the time-of-use pricing differences between active and reactive power losses. Indicates the first Hourly active electricity price This represents the reactive power loss conversion factor; and They represent the first Hour Active power loss and reactive power loss of each node; , , and These represent the maintenance costs over the lifecycle of the corresponding equipment; During the operation of a distribution network system, two core constraints—power balance and voltage—must be met. Simultaneously, the inherent operating characteristics of connected OLTC, CBs, BESS, and PVI devices must be considered. These constraints and device operating rules can be transformed into the following equations or inequality sets, where the active and reactive power balance constraints of the distribution network are: In the formula: Indicates the first The active and reactive power obtained from the power grid per hour; and This represents the set of node numbers for CBs, PVIs, and energy storage systems. Indicates the first Hour The active and reactive power requirements of each node load; Indicates the first Hour Active and reactive power of each node PVI; Indicates the first Hour Active and reactive power of each node energy storage system; Indicates the first Hour The reactive power injected by each node through CBs.

[0024] Voltage amplitude constraints in power distribution networks: In the formula: Indicates the system's first Hour The voltage of each node.

[0025] The equipment constraints include on-load tap-changing transformer constraints, capacitor combination constraints, photovoltaic inverter reactive power constraints, and key constraints of the battery energy storage system. Among these, the equipment constraints considering OLTC are as follows: In the formula: Indicates the first Hourly OLTC tap position.

[0026] Consider the equipment constraints of CBs: In the formula: Indicates the first Hourly CBs switching status; indicating No. The reactive power change caused by switching CBs at each node; Consider the reactive power constraints of PVI: In the formula: Indicates the first Apparent power of each node's PVI; Indicates the first The upper limit of reactive power of each node PVI.

[0027] Key constraints to consider for energy storage systems: Charge and discharge constraints: State of charge constraints: Reactive power output constraint: In the formula: This indicates the state of charge of the BESS.

[0028] As a feasible specific implementation method of this application, centralized control is optimized offline at the hourly level, and the specific steps are as follows: S201: Acquire photovoltaic power output forecast data and distribution network load forecast data through SCADA (Supervisory Control and Data Acquisition). S202: Input data of the distribution network node system, as well as the predicted node load and photovoltaic output data; S203: Form power flow constraints for distribution network nodes and construct a linear power flow model; S204: Set the SSA population size, maximum number of iterations, vigilant ratio, and variable dimension parameters. The optimization variables for each individual include the on-load tap changer taps, capacitor bank switching steps, photovoltaic inverter reactive power, battery energy storage system charging and discharging power, and battery energy storage system reactive power, as shown in Table 1. Table 1: SSA Population Optimization Variables Based on comprehensive cost As the core, for individuals that do not meet the system's operational constraints, a constraint penalty term is added to the fitness function to ensure the feasibility of the solution. The formula is: Where: Voltage over-limit penalty coefficient SOC over-limit penalty coefficient ; S205: Classify individuals by type and update their positions according to the rules. The formula for updating the discoverer's position is: In the formula: Indicates the first In the nth iteration The first individual One dimension, It is a constant; Indicates the maximum number of iterations; A random number in the range [0,1]. For flight functions; The formula for updating the joiner's position is: In the formula: Indicates population size; Indicates the first The global optimal position in the next iteration; Indicates the first The worst position in the next iteration; A random number between [0, 1]; These are random numbers that follow a normal distribution. The formula for updating the location of vigilant is: In the formula: A random number in the range [0,1]. The parameters are constants; the remaining parameters are consistent with the discoverer update rule. S206: Record the global optimal position in each iteration. And the optimal fitness value; if the current iteration number Continue iterating; if The iteration terminates, and the global optimal solution is output, which is the optimal combination of control parameters for “OLTC+CB+PVI+BESS”.

[0029] As a feasible specific implementation of this application, the local control is a five-minute online adjustment process, and the specific control steps are as follows: S301: Accept the control variable settings of the prior centralized control, wherein the prior centralized control is the closest prior centralized control of the current local control; S302: In five-minute time steps Measure node voltage ; S303: Determine if the node voltage exceeds the limit; S304: When the node voltage exceeds the limit, the deviation is calculated based on the measured voltage and classified into levels, as shown in Table 2: Table 2: Voltage Deviation Level Classification S305: Determine the regulation strategy for the photovoltaic inverter and battery energy storage system based on the voltage deviation level, as shown in Table 3: Table 3: Adjustment strategies corresponding to voltage deviation levels Among these measures, BESS active power regulation is prioritized, and the real-time active power regulation of BESS is calculated based on the deviation level. The core principle is to use active power to quickly smooth out most voltage deviations within the centralized control baseline range. The formulas are designed according to different scenarios: When the voltage is too high Excessive photovoltaic output leads to voltage rise, and BESS charging reduces power feeding: In the formula: This represents the calculated active power of BESS charging. This indicates the node's "active power-voltage sensitivity"; This indicates the upper limit of the baseline set by centralized control; Indicates the maximum charging power allowed by the current SOC; When the voltage is low Overload caused a voltage drop, and the BESS discharged to compensate for the demand. In the formula: This represents the calculated active power of the BESS discharge. This indicates the lower limit of the baseline set by centralized control. This represents the absolute value of the maximum allowable discharge power at the current SOC; PVI reactive power regulation is an auxiliary operation. After BESS regulation, the residual voltage deviation is calculated, and PVI is used to fine-tune the reactive power to eliminate the deviation, while adhering to the reactive power reference range of centralized control. The relevant calculation formulas are as follows: In the formula: The residual voltage deviation after BESS active power regulation; This represents the reactive power regulation of the calculated PVI. This indicates the node's "reactive power-voltage sensitivity"; This indicates the PVI reactive power reference range set by the centralized control. This represents the absolute value of reactive power capacity calculated based on the apparent power capacity of PVI and the real-time active power output. S306: Constraint Verification and Command Issuance. Verify the SOC status and PVI capacity of the BESS. If they meet the requirements, issue the command: Distributed to BESS's BMS system, The signal is sent to the PVI inverter to complete local control. If the constraint test fails, the process returns to step S304 to continue classifying the voltage deviation level. S307: Feedback the adjustment results to the centralized control unit and update the optimized basic parameters for the next period. Only when neither BESS nor PVI can meet the pressure regulation requirements will the centralized control adjust the OLTC tap or CBs step count in the next hour and simultaneously correct the reference range of BESS and PVI.

[0030] Reference Figures 4-6 To verify the effectiveness and adaptability of the proposed two-layer voltage collaborative control method for high-proportion distributed photovoltaic (PV) grid integration, an IEEE-33 node distribution network simulation model was built based on the MATLAB simulation platform, as follows: Figure 4 As shown; In the modified test feeder, four types of distribution network equipment are aggregated at nodes {1,3,8,17,21,24,25,29}, including photovoltaic units, BESS, OLTC, and CBs. Among them, the on-load tap-changing transformer is installed at {1}, with a tap adjustment range of -5 to +5 levels, and each level adjustment range is 0.5% of the rated voltage. The capacitor bank is installed at {3,8,24,29}, with a single bank capacity of 600kVAR and 0 to 3 switching steps. The battery energy storage system is installed at {17,21,25}, with a rated capacity of 2MW.h, a charge / discharge range of -1.0 to +1.0MW, a SOC constraint of 20% to 80%, and a reactive power adjustment range of -0.5 to +0.5MVAR. The DLVCC architecture proposed in this invention achieves breakthroughs in voltage control accuracy, equipment lifespan protection, economy, and robustness through a multi-timescale collaborative mechanism of "hourly centralized optimization + five-minute local correction" combined with SSA and multi-device collaborative voltage regulation strategies. The core beneficial effects are as follows: From the perspective of voltage stability control, this scheme can effectively solve the voltage exceeding the limit problem under high photovoltaic penetration, and maintain the voltage of the distribution network within the allowable range of 0.95-1.05 pu throughout the entire period. Figure 6 As shown, without this scheme, node 17 is prone to voltage exceeding the upper or lower limit during sudden increases in photovoltaic output or peak load, with the over-limit lasting for up to 30 minutes or more. However, through the local control hierarchical response mechanism—minor deviations are fine-tuned by PVI for reactive power, while moderate and above deviations are first smoothed by BESS for active power deviation and then the residual reactive power deviation is eliminated—the node voltage fluctuation amplitude is reduced to within ±0.02 pu, and the over-limit phenomenon is basically eliminated. Compared with the traditional scheme that only uses OLTC and CBs, adjusts equipment status hourly, and has no real-time fine-tuning, the voltage stability of this application embodiment is better during use.

[0031] Regarding extending equipment lifespan and reducing maintenance costs, this method significantly reduces the operation frequency of traditional voltage control equipment by strictly adhering to the benchmark range set by centralized control. Traditional centralized control requires adjusting the OLTC tap changer and CBS switching status every hour, and extreme voltage deviations necessitate waiting until the next hour for adjustment, leading to accelerated mechanical wear. This solution only adjusts traditional equipment in the next hour when neither BESS nor PVI can meet the voltage regulation requirements, thus reducing the number of OLTC operations and CBS switching operations and significantly extending the equipment lifespan. Simultaneously, the coordinated voltage regulation of BESS and PVI also alleviates the reactive power pressure on the PVI, preventing the inverter from operating at high reactive loads for extended periods and extending its lifespan.

[0032] In terms of economic efficiency, the solution aims to minimize overall cost, using the SSA algorithm to achieve global optimization of line loss, equipment lifespan loss, and operating costs. For example... Figure 5 As shown, compared to PSO and GA algorithms, SSA converges faster and is less prone to getting trapped in local optima when dealing with mixed integer nonlinear programming problems in distribution networks. It can more accurately optimize parameters such as OLTC tap changer location and BESS charging and discharging power. In actual operation, the total active and reactive power losses of the lines are reduced. At the same time, because BESS can absorb excess photovoltaic output, the noon photovoltaic curtailment rate decreases, significantly improving the utilization rate of photovoltaic resources and power generation revenue. Compared with the traditional scheme that only uses OLTC and CBs, adjusts equipment status hourly, and has no real-time fine-tuning, the embodiments of this application significantly improve the overall economic efficiency.

[0033] Furthermore, the solution exhibits strong robustness, capable of handling the intermittency and uncertainty of photovoltaic (PV) output. During the centralized control phase, baseline parameters are optimized based on load and PV output forecast data. In the local control phase, voltage data is collected in real-time via the CAN bus and dynamically adjusted. Even in scenarios involving sudden drops in PV output, such as cloudy or overcast days, voltage correction can be completed within five minutes. Compared to the hourly response time of traditional solutions, this significantly enhances anti-interference capabilities, providing reliable technical support for the safe, efficient, and economical operation of distribution networks with high PV penetration.

[0034] This application also provides a two-layer voltage coordination control system for high-proportion distributed photovoltaic (PV) grid integration, employing a multi-level architecture of a centralized control unit, local control units, and a device execution layer. This system is used to execute the aforementioned two-layer voltage coordination control method for high-proportion distributed PV grid integration, including: The execution unit includes on-load tap-changing transformers, capacitor banks, photovoltaic inverters, and battery energy storage systems. The parameters and installation locations of each device need to be determined based on the distribution network topology. The centralized control unit is used to perform centralized control of the distribution network. The centralized control unit is deployed in the distribution network dispatch center and adopts an industrial control computer. The centralized control unit obtains the distribution network load forecast data through the SCADA system and obtains the PV output forecast data through the irradiance sensor and the PV inverter. After optimization by the SSA algorithm, it outputs the basic control parameters of OLTC tap, CB switching steps, and PVI / BESS. The local control unit, used to perform local control, is integrated into the control cabinet of PVI and BESS and uses an embedded processor. It collects the bus voltage in real time via CAN bus. If a voltage over-limit or PV output drop is detected, it dynamically adjusts the reactive / active output of PVI / BESS based on the adjustment strategy and feeds the adjustment results back to the centralized control unit to update the optimized basic parameters for the next time period, realizing five-minute dynamic voltage correction. The communication unit is used for communication between the execution unit, the centralized control unit, and the local control unit.

[0035] The embodiments described in this specific implementation are preferred embodiments of this application and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A two-layer voltage coordinated control method for high-proportion distributed photovoltaic power grid integration, characterized in that, include: Deploy centralized control units and distributed local control units in the power distribution network; The daily time period is divided into several centralized control periods, with two adjacent centralized control periods being consecutive. During each centralized control period, the centralized control unit performs centralized control once to optimize voltage regulation based on the overall optimization objective, which is to minimize the overall cost, including power loss cost and equipment life and maintenance cycle cost. Each centralized control period is divided into several consecutive local control periods; Within each local control period, the local control unit performs local control once to optimize voltage regulation based on the overall optimization objective.

2. The two-layer voltage coordination control method for high-proportion distributed photovoltaic power grid access according to claim 1, characterized in that, After the centralized control unit performs centralized control, it transmits the optimized control variables to the local control unit. After performing local control, the local control unit feeds back the results to the central control unit to update the optimized basic parameters for the next time period.

3. The two-layer voltage coordinated control method for high-proportion distributed photovoltaic power grid access according to claim 1, characterized in that, When the centralized control unit and the local control unit optimize based on the overall optimization objective, they satisfy the power balance constraints of the distribution network, the voltage amplitude constraints of the distribution network, and the equipment constraints.

4. The two-layer voltage coordinated control method for high-proportion distributed photovoltaic power grid access according to claim 3, characterized in that, The equipment constraints include on-load tap-changing transformer constraints, capacitor combination constraints, photovoltaic inverter reactive power constraints, and key constraints of the battery energy storage system.

5. The two-layer voltage coordinated control method for high-proportion distributed photovoltaic power grid access according to claim 1, characterized in that, The centralized control includes: Acquire and input data from the distribution network node system, as well as predicted node load and photovoltaic output data; Form power flow constraints for distribution network nodes and construct a linear power flow model; Set the SSA population size, maximum number of iterations, proportion of vigilants, and variable dimension parameters. The optimization variables for each individual include the on-load tap changer taps, capacitor combination switching steps, photovoltaic inverter reactive power, battery energy storage system charging and discharging power, and battery energy storage system reactive power. Based on the number of iterations, the optimal combination of control parameters for the on-load tap-changing transformer, capacitor bank, photovoltaic inverter, and battery energy storage system is output.

6. The two-layer voltage coordinated control method for high-proportion distributed photovoltaic power grid access according to claim 5, characterized in that, The acquisition of data from the distribution network node system includes: Obtain power distribution network load forecast data through SCADA system; Photovoltaic output prediction data is obtained by communicating with the photovoltaic inverter through an irradiance intensity sensor.

7. The two-layer voltage coordinated control method for high-proportion distributed photovoltaic power grid access according to claim 1, characterized in that, The local control includes: Control variable settings that are subject to centralized control; Obtain node voltage; Determine if the node voltage exceeds the limit; When the node voltage exceeds the limit, the regulation strategy of the photovoltaic inverter and battery energy storage system is executed.

8. The two-layer voltage coordinated control method for high-proportion distributed photovoltaic power grid access according to claim 7, characterized in that, The local control also includes: Voltage deviation levels are determined based on the obtained node voltages; Determine the regulation strategy for photovoltaic inverters and battery energy storage systems based on the voltage deviation level; The photovoltaic inverter and battery energy storage system are adjusted according to the adjustment strategy determined by the regulation. Determine whether the constraint test is passed; If the constraint test is not passed, continue to classify the voltage deviation level.

9. A two-layer voltage coordinated control method for high-proportion distributed photovoltaic power grid access according to claim 8, characterized in that, The local control also includes: When the voltage deviation per unit value does not exceed 0.01, the regulation strategy of neither the photovoltaic inverter nor the battery energy storage system shall be implemented. When the per-unit voltage deviation exceeds 0.01 but does not exceed 0.03, the photovoltaic inverter adjusts the reactive power and the battery energy storage system does not operate. When the per-unit voltage deviation exceeds 0.03 but does not exceed 0.05, the regulation strategy of battery energy storage system dominating the regulation of active power and photovoltaic inverter assisting in the regulation of reactive power is implemented. When the voltage deviation per unit value exceeds 0.05, the full power regulation of the battery energy storage system and the maximum reactive power regulation of the photovoltaic inverter are executed, and the centralized control correction benchmark for the next period is triggered.

10. A two-layer voltage coordination control system for high-proportion distributed photovoltaic power grid integration, characterized in that, A two-layer voltage coordination control method for implementing a high-proportion distributed photovoltaic grid connection as described in any one of claims 1-9 includes: The centralized control unit is used to perform centralized control of the distribution network, controlling on-load tap-changing transformers, capacitor banks, photovoltaic inverters, and battery energy storage systems. The local control unit is used to perform local control, controlling the photovoltaic inverter and battery energy storage system; The communication unit is used for communication between the centralized control unit and the local control unit.

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