Active power distribution network partitioning multi-time-scale collaborative control method, system and apparatus

Abstract

The present application is applicable to the technical field of electric power. Provided are an active power distribution network partitioning multi-time-scale collaborative control method, system and apparatus. The method comprises: on the basis of operation data of a power distribution network, determining a voltage sensitivity indicator for each node in each partition; dividing response capability levels on the basis of the tracking response performance of regulation resources, and on the basis of the response capability levels and the voltage sensitivity indicators, determining a response sequence of regulation resources of each node in each partition; on the basis of the response sequence, performing day-ahead optimization to determine a day-ahead regulation strategy for hour-level regulation resources of each partition, performing intra-day optimization to determine an intra-day regulation strategy for hour-level and / or minute-level regulation resources of each partition and an intra-day regulation strategy for minute-level regulation resources of each node, and performing real-time optimization to obtain a regulation strategy for second-level or below regulation resources of each node; and, on the basis of the regulation strategies, controlling the regulation resources. The present application can effectively improve the stable voltage operation level of active power distribution networks and reduce line losses.

Description

Active power distribution network zone multi-timescale coordinated control method, system and device

[0001] This application claims priority to Chinese Patent Application No. 2024119314377, filed on December 26, 2024, entitled “Active Distribution Network Partition Multi-Time Scale Coordinated Control Method, System and Device”, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application belongs to the field of power technology, and in particular relates to a method, system and device for multi-timescale coordinated control of active distribution network zones. Background Technology

[0003] Under the new circumstances of energy transition, active distribution networks are rapidly evolving into multi-port active networks with supply and demand interaction. The interactive coupling characteristics of multi-level power grids are gradually emerging, and problems such as disordered distribution of network power flow, poor flexibility of resource regulation, and bidirectional voltage over-limit are becoming increasingly prominent.

[0004] In typical active distribution networks, voltage regulation can be achieved by controlling the reactive power of distributed generation converters. However, the reactive power capacity of these converters is relatively small, limiting their ability to regulate large-scale distributed generation grid connections. Although voltage regulation can be achieved by temporarily reducing the active power of distributed generation sources, this inevitably affects the grid's absorption of distributed generation resources.

[0005] With the continuous development of energy storage technology, single or multiple distribution areas can form distribution area-level microgrids through energy storage, controlling the power output at their grid connection points, which is an important regulation means to support the voltage control of active distribution networks. Furthermore, distribution network voltage control technologies are mostly concentrated at the "source" and "load" levels, with relatively little research on flexible control technologies at the "line" level. With the maturity of power electronics technology, flexible regulation devices based on power electronics technology are connected to feeders in series / parallel and utilize voltage amplitude compensation for voltage regulation, representing another important regulation means for active distribution network voltage control. However, from feeders to distribution areas (including distribution area-level microgrids), the heterogeneous resources differ in structure, controllability, and demand response. The significant differences in the performance of different regulation resources make the power flow direction and magnitude of the distribution network more complex and variable. How to fully leverage the performance advantages of source-grid-load regulation resources and intelligently regulate the voltage operation level of the active distribution network is an urgent problem to be solved. Summary of the Invention

[0006] In view of this, embodiments of this application provide a method, system, and apparatus for multi-time-scale coordinated control of active distribution network zones, so as to improve the voltage stability operation level of active distribution networks.

[0007] The first aspect of this application provides a method for multi-time-scale coordinated control of active distribution network zones, including:

[0008] Obtain operational data of the power distribution network;

[0009] Based on the operational data, the power distribution network is divided into zones, and the voltage sensitivity index of each node in each zone is determined.

[0010] The response capability levels are divided according to the tracking response performance of the regulating resources. Based on the response capability levels and the voltage sensitivity index, the response order of the regulating resources of each node in each partition is determined.

[0011] Based on the response order, the day-ahead adjustment strategy for hourly adjustment resources of each partition is determined by day-ahead optimization, the intraday adjustment strategy for hourly and / or minute-level adjustment resources of each partition is determined by intraday optimization, and the intraday adjustment strategy for minute-level adjustment resources of each node is determined by intraday optimization. The adjustment strategy for second-level and below adjustment resources of each node is obtained by real-time optimization.

[0012] Based on the regulation strategies of the hourly regulation resources, the minute-level regulation resources, and the second-level and below regulation resources, the corresponding regulation resources in the distribution network are controlled.

[0013] In conjunction with the first aspect, in one possible implementation of the first aspect, determining the voltage sensitivity index of each node within each partition includes:

[0014] Based on the relationship between node injected power and node voltage, the sensitivity factor matrices of the influence of active power increment and reactive power increment on node voltage amplitude are determined respectively.

[0015] Singular values ​​are extracted from the sensitivity factor matrix of the influence of active and reactive power increments on node voltage amplitude to obtain the reactive voltage sensitivity index and active voltage sensitivity index of the node.

[0016] In conjunction with the first aspect, in one possible implementation of the first aspect, the partitioning includes: reactive power compensation partitioning, active power reduction partitioning, and special node partitioning;

[0017] The step of determining the response order of resource adjustment for each node within each partition based on the response capability level and the voltage sensitivity index includes:

[0018] For reactive power compensation zones, the distribution network is divided into reactive power zones according to the community discovery algorithm. The response order of the adjustment resources of each node in the zone is as follows: if the adjustment resource tracking response speed is slow, it shall be prioritized according to the power control command requirements. If the tracking response speed is the same, the reactive power resource adjustment order of each node in the zone shall be determined according to the reactive power voltage sensitivity index of each node in the zone from large to small.

[0019] For active power reduction zones, priority is given to active power reduction of energy storage, microgrids, flexible interconnection devices, and devices with both energy storage and release capabilities. The active power reduction order of each node in the zone is determined according to the active power voltage sensitivity index of each node in the zone from largest to smallest. If the active power reduction of any node cannot be flexibly controlled, then the node is removed from the sequence.

[0020] For special node partitions, the access locations of special node partitions are determined according to the functional attributes of the voltage regulation devices of the distribution network lines participating in voltage control. The order of regulation resource response of each node in the partition is determined in descending order of the active voltage sensitivity index of each node in the partition.

[0021] In conjunction with the first aspect, in one possible implementation of the first aspect, the day-ahead adjustment strategy for determining the hourly adjustment resources of each partition through day-ahead optimization includes:

[0022] A first objective function is established with the goal of minimizing the sum of voltage deviation and line loss of all nodes in the distribution network on the day to be dispatched.

[0023] Establish the constraints for the first objective function;

[0024] Based on the response order and the constraints of the first objective function, the solution of the first objective function is calculated to obtain the hourly adjustment strategy for each node's adjustment resources.

[0025] In conjunction with the first aspect, in one possible implementation of the first aspect, the determination of the intraday adjustment strategy for hourly and / or minute-level adjustment resources for each partition through intraday optimization, and the intraday adjustment strategy for minute-level adjustment resources for each node, includes:

[0026] The days to be scheduled are divided into multiple first time periods;

[0027] With the goal of minimizing the sum of voltage deviation and line loss of all nodes in the distribution network in each first time period, a second objective function is established and solved based on the optimization strategy given previously, to obtain a centralized regulation strategy for the hourly and / or minute-level regulation resources of each node in each first time period;

[0028] Each first time period is divided into multiple second time periods;

[0029] For each partition, based on the centralized regulation strategy, a third objective function is established and solved with the goal of minimizing the sum of voltage deviation and line loss of all nodes in the partition in each second time period. This yields a distributed regulation strategy for the minute-level regulation resources of each node in each second time period. The distributed regulation strategy is the regulation strategy for the minute-level regulation resources of each node determined through intraday optimization.

[0030] In conjunction with the first aspect, in one possible implementation of the first aspect, the adjustment strategy for adjusting resources at the second level or below for each node through real-time optimization includes:

[0031] Obtain the real-time voltage value of the power distribution network;

[0032] Based on the real-time voltage value and the preset target voltage value, determine the adjustment strategy for the adjustment resources at the second level and below for each node.

[0033] In conjunction with the first aspect, in one possible implementation of the first aspect, the objective function takes the form of:

[0034] In the formula, U t,i and U t,j Let U and t be the voltages at nodes i and j at time t, respectively, where j ≥ i; U0 is the nominal value of the node voltage; G ij and B ij These represent the line conductance and susceptance between node i and node j, respectively; θ t,ij U is the voltage phase angle difference between node i and node j at time t; α and β are weighting coefficients; U N P is the nominal voltage of the line. zbN For the main transformer capacity of the line;

[0035] The objective function is a first objective function, a second objective function, or a third objective function;

[0036] When the objective function is the first objective function or the second objective function, n is the total number of nodes in the distribution network; when the objective function is the third objective function, n is the total number of nodes in the partition.

[0037] In conjunction with the first aspect, in one possible implementation of the first aspect, the second objective function and the third objective function also satisfy the condition of minimizing the active power balance control regulation index:

[0038] In the formula, P resum,i The active power reduction at node i; t is time, t∈[1,T], and T is the number of time points; α R For binary coefficients, if P resum,i =0 when α R =0, otherwise α R =1;

[0039] If the objective function is a first objective function or a second objective function, then the constraints include: power balance constraints and control variable constraints;

[0040] If the objective function is a third objective function, then the constraints include: power balance constraints, control variable constraints, and total operating power constraints for the second time period determined according to the centralized adjustment strategy.

[0041] The power balance constraints include:

[0042] In the formula, P t,i P represents the active power injected into node i at time t. DG,t,i P represents the active power output of the distributed power inverter at node i at time t. DGth,t,i and P DGre,t,i These represent the theoretical output and active power reduction of the distributed power source at node i at time t, respectively; P micg,t,i and Q micg,t,i P represents the active and reactive power consumed by energy storage, microgrids, flexible interconnection devices, or regulating resources with energy storage functions at node i at time t, respectively; micgth,t,i and P micgre,t,i P represents the theoretical active power consumed and active power reduced at node i at time t, whether it is an energy storage device, microgrid, flexible interconnection device, or regulation resource with energy storage function. Lo,t,i λ represents the active power consumed by the load at node i at time t; ty P is the loss coefficient of the line flexible regulation device. ty,t,i Let be the active power of the series transformer in the flexible regulating device at node i of the line at time t; The voltage phasor of the line flexible regulating device at node i at time t; Let i be the current phasor of the line from node i-1 to node i.

[0043] The second aspect of this application provides an active power distribution network zoned multi-time-scale collaborative control system for implementing the method described in the first aspect or any of its implementations; the system includes a master station and substations, and the control process of the system includes centralized control, distributed control, and local control;

[0044] The main station employs centralized control to determine the daytime adjustment strategy through daytime optimization and intraday optimization to determine the centralized adjustment strategy. The control period for centralized control is t. jz The substation employs distributed control for intraday optimization to determine the distributed adjustment strategy, and local control for real-time optimization. The control period for distributed control is t. fbs , t jz =K dk t fbs K dk It is a positive number;

[0045] Among them, centralized control determines the next t.jz The operating power of each partition during the time period, and the next t determined by the distributed control and centralized control. jz Operating power constraints for a given time period determine the next t. jz within the time period t fbs The operating power of each partition during the time period, to meet the needs of each partition in that time period. jz Each t within the time period fbs The total power over a given period equals the sum of the power over that period t. jz Total operating power during the period:

[0046] In the formula, S jz S is the apparent power command for a certain zone issued by centralized control. fbs k represents the apparent power of the partition during actual operation. fbs k is the adjustable coefficient for the operating power of this partition. min,fbs ≤k fbs ≤k max,fbs k min,fbs and k max,fbs These are the minimum and maximum values ​​of the adjustable coefficient for the operating power of this partition, respectively.

[0047] The centrally controlled partitions are numbered i jz Let the maximum value of the number be I. jz Then, globally, the following equality constraint is satisfied:

[0048] In the formula, k jz This is an adjustable coefficient for the total operating power of a zone under centralized control, and the coefficient is determined based on the network loss situation of the zone. For the i-th jz The coefficient for adjustable operating power of each partition; k dk For integers, 1 ≤ k dk ≤K dk ; Centralized control is issued to the i-th jz Apparent power command for each partition; For the i-th jz The apparent power of each partition in actual operation;

[0049] The substation system of the partition receives each control cycle t fbs The power value within, and the controlled power value and adjustable power coefficient. Feedback is sent to the main station, which then uses the controlled power value and adjustable power coefficient fed back by the substation. Make overall control and decision-making decisions.

[0050] A third aspect of this application provides an active power distribution network zone multi-time-scale coordinated control device, comprising:

[0051] The acquisition module is used to acquire operational data of the power distribution network;

[0052] The first processing module is used to divide the power distribution network into zones based on the operating data and determine the voltage sensitivity index of each node in each zone.

[0053] The second processing module is used to classify the tracking response capability levels of the adjustment resources according to the tracking response capability of the adjustment resources, and determine the orderly response order of the adjustment resources of each node in each partition.

[0054] The third processing module is used to classify response capability levels according to the tracking response performance of the adjustment resources, and to determine the response order of the adjustment resources of each node in each partition according to the response capability level and the voltage sensitivity index.

[0055] The fourth processing module is used to determine the day-ahead adjustment strategy of the hourly adjustment resources of each partition through day-ahead optimization, the intraday adjustment strategy of the hourly and / or minute-level adjustment resources of each partition through intraday optimization, the intraday adjustment strategy of the minute-level adjustment resources of each node, and the adjustment strategy of the second-level and below adjustment resources of each node through real-time optimization, based on the response order.

[0056] The control module is used to control the corresponding regulation resources in the distribution network based on the regulation strategies of the hourly regulation resources, the minute-level regulation resources, and the second-level and below regulation resources.

[0057] The beneficial effects of the embodiments in this application compared with the prior art are:

[0058] This application implements a partitioned distribution network model. Based on the voltage sensitivity index of each node within each partition, the response order of regulation resources for each node within each partition is determined. Then, based on the response order of regulation resources, a multi-timescale optimization model is established, encompassing day-ahead, intraday, and real-time metrics. Day-ahead optimization determines the day-ahead regulation strategy for hourly regulation resources of each node; intraday optimization determines the intraday regulation strategy for hourly and minute-level regulation resources of each partition and node; and real-time optimization yields the regulation strategy for second-level and sub-second-level regulation resources of each node. This achieves multi-timescale partitioned collaborative control of distribution network regulation resources. This application can fully leverage the performance advantages of source-grid-load regulation resources and improve the voltage stability of active distribution networks. Attached Figure Description

[0059] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0060] Figure 1 is a schematic diagram of the implementation process of the active distribution network partition multi-time scale collaborative control method provided in the embodiment of this application;

[0061] Figure 2 is a schematic diagram of the implementation process of the active distribution network partition multi-time scale collaborative control method provided in the embodiment of this application;

[0062] Figure 3 is a schematic diagram of the structure of the active power distribution network zone multi-time scale collaborative control device provided in the embodiment of this application. Detailed Implementation

[0063] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0064] To illustrate the technical solution described in this application, specific embodiments are provided below.

[0065] Referring to Figure 1, the active distribution network zone multi-time-scale coordinated control method of this application embodiment includes:

[0066] Step S101: Obtain the operation data of the power distribution network.

[0067] Here, the operating data of the distribution network includes, but is not limited to: distribution network line parameters, load operation data, distributed power generation operation data, installation location and capacity of flexible regulation devices, and the location of microgrid nodes connected to the distribution network.

[0068] Load operation data includes historical power data of node loads, etc.

[0069] Distributed power source operation data includes historical irradiance data, wind speed, temperature, distributed power source installation location and capacity, etc. Distributed power sources can be distributed wind power generation or distributed photovoltaic power generation.

[0070] Optionally, the flexible regulating device can consist of a series transformer, a parallel power-collecting transformer, and thyristors. The parallel power-collecting transformer draws power from the line voltage; the series transformer adds or subtracts the voltage amplitude of the series line based on voltage amplitude feedback; the series transformer and the parallel power-collecting transformer are connected via thyristors, and the number of turns in the coil of the parallel power-collecting transformer is adjusted by switching the thyristors on and off, thereby changing the turns ratio of the series transformer's voltage amplitude feedback regulation.

[0071] Optionally, the flexible regulation device can consist of a series transformer, a series converter, and a parallel converter, wherein the series converter is an AC / DC converter and the parallel converter is a DC / AC converter. The parallel converter draws voltage from the line and converts AC to DC; the series converter converts DC to AC and adds or subtracts the line voltage amplitude through the series transformer.

[0072] Step S102: Based on the operating data, the distribution network is divided into zones, and the voltage sensitivity index of each node in each zone is determined.

[0073] In this embodiment, the voltage sensitivity index is calculated as follows:

[0074] The main factors affecting the voltage at the point of connection of distributed generation are the active and reactive power injected by the distributed generation. First, we explore the relationship between the injected power and the node voltage in the system. Based on the Jacobian matrix in power flow calculations, we obtain the following:

[0075] In the formula, ΔP and ΔQ represent the increments of active and reactive power injected into the node; A Pδ B PU The relationship between the increase in active power injected into the node and the node phase angle and voltage increment; C Qδ D QU This represents the relationship between the reactive power increment at the injected node and the node phase angle and voltage increment; ΔU is the voltage amplitude increment; Δδ is the voltage phase angle increment.

[0076] The above equation can be transformed to obtain:

[0077] In the formula, R δP R δQ R is a sensitivity factor for the influence of active power increment and reactive power increment on the node voltage phase angle; UP R UQ This is a sensitivity factor for the influence of active power increment and reactive power increment on the voltage amplitude of this node.

[0078] Therefore, the formula relating the node voltage change and the injected power change sequence of an n-node distribution network can be obtained: ΔU = R UP ΔP+RUQ ΔQ;

[0079] In the formula, ΔU=[ΔU1,ΔU2,…,ΔUn], ΔP=[ΔP1,ΔP2,…,ΔPn], and ΔQ=[ΔQ1,ΔQ2,…,ΔQn] represent the voltage amplitude increment sequence, active power increment sequence, and reactive power increment sequence of the node, respectively; n is the number of nodes.

[0080] Further extract the sensitivity factor matrix R UP and R UQ The singular values ​​are used as sensitivity indicators for the corresponding nodes. The reactive voltage sensitivity indicators and active voltage sensitivity indicators are as follows:

[0081] In the formula, S P,i S is the active voltage sensitivity index of the i-th node in the distribution network; Q,i σ is the reactive voltage sensitivity index of the i-th node in the distribution network; UP,i and σ UQ,i The sensitivity factor matrix R is respectively UP and R UQ The i-th singular value.

[0082] The reactive power voltage sensitivity index directly describes the sensitivity of node voltage to injected reactive power. It indicates the sensitivity of each node voltage to reactive power injection from distributed generation sources under the current grid topology; a higher index value indicates a more sensitive node voltage to reactive power injection from distributed generation sources. Similarly, the active power voltage sensitivity index describes the sensitivity of each node voltage to active power injection from distributed generation sources under the current grid topology; a higher index value indicates a more sensitive node voltage to active power injection from distributed generation sources. Under normal operating conditions of the distribution network, insufficient or excessive active and reactive power will lead to voltage exceeding limits. This index allows for an effective quantitative evaluation of the impact of active and reactive power from distributed generation sources on distribution network nodes.

[0083] Step S103: Response capability levels are assigned based on the tracking response performance of the regulation resources. Based on the response capability level and voltage sensitivity index, the response order of the regulation resources of each node within each partition is determined. The response order of each node is used to prioritize the use of regulation resources from certain nodes during subsequent optimization.

[0084] Optionally, the partitions may include: reactive power compensation partitions, active power reduction partitions, and special node partitions.

[0085] For reactive power compensation zones, the distribution network is divided into reactive power zones according to the community discovery algorithm. The response order of the adjustment resources of each node in the zone is as follows: if the adjustment resource tracking response speed is slow, it shall be prioritized according to the power control command requirements. If the tracking response speed is the same, the reactive power resource adjustment order of each node in the zone shall be determined according to the reactive power voltage sensitivity index of each node in the zone from large to small.

[0086] For active power reduction zones, priority is given to active power reduction from energy storage, microgrids, flexible interconnection devices, and devices with both energy storage and release capabilities. The active power reduction sequence for each node within a zone is determined by ranking the active power voltage sensitivity index from largest to smallest. If the active power reduction of any node cannot be flexibly controlled, that node is removed from the sequence. The active power reduction of distributed generation is the difference between the theoretical and actual output of the distributed generation.

[0087] For special node partitions, the access locations of special node partitions are determined according to the functional attributes of the voltage regulation devices of the distribution network lines participating in voltage control. The order of regulation resource response of each node in the partition is determined in descending order of the active voltage sensitivity index of each node in the partition.

[0088] For example, the classification of regulating resources tracking response capabilities includes, but is not limited to, the functional classification of photovoltaic inverters, wind turbine converters, energy storage converters, microgrids, line voltage regulating devices, on-load tap changer taps, flexible interconnection devices, and reactive power compensation devices. Table 1 shows the common classifications of regulating resources tracking response capabilities in distribution networks. Other regulating resources in distribution networks include SVCs, SVGs, distributed generation converters, microgrids, energy storage, and electric vehicle charging stations.

[0089] Table 1. Classification of Adjustment Resource Tracking and Response Capabilities

[0090] Step S104: Based on the response order, determine the day-ahead adjustment strategy of hourly adjustment resources for each partition through day-ahead optimization, determine the intraday adjustment strategy of hourly and / or minute-level adjustment resources for each partition through intraday optimization, determine the intraday adjustment strategy of minute-level adjustment resources for each node, and obtain the adjustment strategy of second-level and below adjustment resources for each node through real-time optimization.

[0091] This embodiment classifies the response capability of a node's adjustment resources into hourly, minutely, and secondly tracking response levels based on the response speed of adjustment resources within a node or partition. Adjustment resources are divided into hourly adjustment resources, minutely adjustment resources, and secondly and below adjustment resources. Depending on the adjustment needs of the node, hourly response can be performed first, followed by minutely response, and finally secondly response.

[0092] For example:

[0093] In the day-ahead period, voltage optimization is based on the day-ahead forecast curves of distributed generation and load. Hourly-level regulation resources (such as capacitor banks, fixed charging and discharging of energy storage can be used as hourly-level tracking response regulation resources, or regulation resources with limited cycles, distributed control areas, etc.) are used as the control objects for day-ahead optimization. In this embodiment, the method for determining the day-ahead forecast curves of distributed generation and load is not limited. For example, the day-ahead forecast curves of distributed generation and load at each node can be predicted based on the power prediction function of the existing distribution automation master station. Alternatively, the day-ahead forecast curve of load can be predicted based on historical load power operation data, combined with a Markov chain algorithm or artificial neural network intelligent algorithm to establish a prediction model for the load's day-ahead forecast; the day-ahead forecast curve of distributed generation can be predicted based on the historical photovoltaic power operation data of the node, numerical weather forecasts, combined with a Markov chain algorithm or artificial neural network intelligent algorithm to establish a prediction model for the photovoltaic output's day-ahead forecast.

[0094] Intraday optimization optimizes the operating power of control and regulation resources in each time period using a cyclical rolling method across a single time segment. Intraday optimization mainly utilizes minute-level regulation resources such as line flexible regulation devices, distributed power sources and energy storage controlled by centralized control commands, and microgrids to perform minute-level power regulation.

[0095] Real-time regulation can be based on the target voltage value as the control condition, and can be performed on second-level and below regulation resources such as local control and grid control, to further optimize the voltage operation level.

[0096] By systematically regulating resources at the hourly, minute, and second-level and below levels, the voltage stability of active distribution networks can be effectively improved.

[0097] Step S105: Based on the regulation strategies of hourly regulation resources, minute-level regulation resources, and second-level and below regulation resources, control the corresponding regulation resources in the distribution network.

[0098] Here, a centralized-distributed-local control approach for the coordinated regulation of distribution network regulation resources is adopted. This embodiment establishes a zoned coordinated control system for distribution network regulation resources based on a master station and substations. The master station determines the regulation amounts for slow-response equipment, equipment with limited usage times, power output with fixed time periods, and resources in each reactive power zone based on day-ahead and intraday optimization, and issues commands to the substations via centralized control. The substations employ distributed control, determining the regulation amounts for reactive power zone regulation resources through intraday and real-time optimization, and providing data feedback to the master station. Local control performs real-time adjustments based on set target voltage values. In this way, multi-timescale zoned coordinated control of distribution network regulation resources is achieved.

[0099] This application's embodiments divide the distribution network into zones. Based on the voltage sensitivity index of each node within each zone, the response order of the regulation resources for each node in each zone is determined. Then, based on the response order of the regulation resources, a multi-timescale optimization model is established, encompassing day-ahead, intraday, and real-time dimensions. Day-ahead optimization determines the hourly regulation strategy for each node's regulation resources, intraday optimization determines the minute-level regulation strategy, and real-time optimization yields the second-level and sub-second-level regulation strategies for each node. This achieves multi-timescale zoned collaborative control of the distribution network's regulation resources. This application can fully leverage the performance advantages of source-grid-load regulation resources, improving the voltage stability of active distribution networks.

[0100] Referring to Figure 2, the multi-timescale optimization process of step S104, including day-ahead, intraday, and real-time optimization, will be described in detail in the following embodiments.

[0101] Step S1041: Determine the day-ahead adjustment strategy for hourly adjustment resources in each partition through day-ahead optimization.

[0102] In addition to transmitting active power, the total capacity of distributed power converters can also be used for reactive power compensation to regulate voltage. Based on the system's reactive power optimization requirements and the remaining capacity range, the reactive power optimization result is determined. The reactive power optimization decision variables include the reactive power output of each inverter, the amount of active power reduction, and the reactive power capacity released. The optimization objective is to achieve optimal voltage control. The relationship between reactive power and active power on voltage is described by power flow equations.

[0103] (1) On the current date, with the objective of minimizing the sum of voltage deviation and line loss of all nodes in the distribution network on the day to be dispatched, a first objective function is established:

[0104] In the formula, U t,i and U t,j Let U and t be the voltages at nodes i and j at time t, respectively, where j ≥ i; U0 is the nominal value of the node voltage; G ij and B ij These represent the line conductance and susceptance between node i and node j, respectively; θ t,ij U is the voltage phase angle difference between node i and node j at time t; α and β are weighting coefficients; U N P is the nominal voltage of the line. zbN The capacity of the main transformer in the line is denoted as n. Since the first objective function calculates all nodes in the distribution network, n here represents the total number of nodes in the distribution network.

[0105] (2) Establish the constraints for the first objective function.

[0106] The power balance constraint must be satisfied at all times. Taking time t as an example, the power balance constraint between nodes is established as follows:

[0107] In the formula, P t,i and Q t,i Let be the active power and reactive power injected into node i at time t, respectively. P DG,t,i and Q DG,t,i P represents the active power and reactive power output of the distributed power inverter at node i at time t, respectively. DGth,t,i and P DGre,t,i These represent the theoretical output and active power reduction of the distributed power source at node i at time t, respectively; P micg,t,i and Q micg,t,i P represents the active power and reactive power consumed by the microgrid at node i at time t, respectively. micgth,t,i and P micgre,t,i Q represents the theoretical active power consumed and active power reduced at node i of the microgrid at time t, respectively. micgth,t,i and Q micgre,t,i P represents the theoretical reactive power consumed by the microgrid at node i at time t and the reactive power compensated for by regulation, respectively. Lo,t,i and Q Lo,t,i Let Q represent the active power and reactive power consumed by the load at node i at time t, respectively; C,t,i Q represents the switching capacity of the parallel capacitor bank at node i at time t; SVG,t,i λ represents the reactive power compensated by the SVG at node i at time t; ty P is the loss coefficient of the line flexible regulation device. ty,t,i Let be the active power of the series transformer in the flexible regulating device at node i of the line at time t; The voltage phasor of the line flexible regulating device at node i at time t; Let be the current phasor of the line from node i-1 to node i. This can be solved using the ratio of the voltage drop across the line from node i-1 to node i to the line impedance. Where R i-1,i and X i-1,i These are the line resistance and reactance from node i-1 to node i, respectively.

[0108] The node voltage constraint is U Nmin ≤U t,i ≤U Nmax ;

[0109] In the formula, U Nmax and U Nmin These are the upper and lower limits of the node voltage, respectively.

[0110] Based on the response order and the constraints of the first objective function, the solution of the first objective function can be calculated, and the adjustment strategy of the hourly adjustment resources for each node can be obtained.

[0111] Step S1042: Determine the intraday adjustment strategy for hourly and / or minute-level adjustment resources for each partition, and the intraday adjustment strategy for minute-level adjustment resources for each node through intraday optimization.

[0112] (1) First, the day to be dispatched can be divided into multiple first time periods, for example, each hour as a first time period. With the goal of minimizing the sum of voltage deviation and line loss of all nodes in the distribution network in each first time period, a second objective function is established and solved to obtain the centralized adjustment strategy of hourly and / or minute-level adjustment resources of each node in each first time period.

[0113] Here, the form of the second objective function can be the same as that of the first objective function, and the constraints are also similar to those of the first objective function, which will not be elaborated upon in this embodiment. The only difference is that the second objective function uses the first time period as the optimization range, and the solution result is a resource adjustment strategy for minute-level adjustments.

[0114] (2) Then, each first time period can be divided into multiple second time periods, for example, every 15 minutes is a second time period. For each partition, based on the centralized adjustment strategy, with the goal of minimizing the sum of voltage deviation and line loss of all nodes in the partition in each second time period, a third objective function is established and solved to obtain the distributed adjustment strategy of minute-level adjustment resources of each node in each second time period. The distributed adjustment strategy is the adjustment strategy of minute-level adjustment resources of each node determined by intraday optimization.

[0115] Here, the third objective function can have the same form as the first objective function, except that the third objective function uses the second time period as the optimization scope and performs intra-partition optimization on a per-partition basis. Therefore, in the third objective function, n is the total number of nodes in the partition. Simultaneously, the constraints of the third objective function also include the total operating power constraint for the second time period determined according to the centralized adjustment strategy.

[0116] Step S1043: Obtain adjustment strategies for resources at the second level and below for each node through real-time optimization.

[0117] The specific implementation method of this step can be found in the description of the embodiment in Figure 1 above, and will not be repeated in this embodiment.

[0118] This embodiment fully explores the potential of regulation resources such as flexible regulation devices for distribution network lines, distributed power sources, and microgrids. By combining reactive power zoning and centralized-distributed-local control methods, it can effectively suppress voltage fluctuations in the distribution network, improve the system voltage operation level, reduce line losses, and alleviate the communication burden of data transmission in the distribution network.

[0119] This application also proposes an active distribution network voltage optimization control system. The control system includes a master station and substations. Each reactive power zone has a system substation, and the master station and substations can interact with each other. The master station performs centralized control considering the overall optimization of the distribution network, issuing instructions to the system substations in the reactive power zones, and the substations perform distributed control. The substations communicate with the master station, and the master station shares the needs and optimization objectives of each substation with each substation. The communication data between the master station and the substations includes time-varying reactive power demand values ​​and active power reduction values. Power allocation between microgrids within the reactive power zone, and between microgrids and adjustable resources in the distribution area, is coordinated by the substations.

[0120] The active distribution network voltage optimization control system adopts a centralized and distributed control architecture. It considers day-ahead global optimization to optimize the power of regulated resources in each reactive power zone, determining the reactive power demand curve, thus achieving centralized control. Intraday optimization, based on the day-ahead optimization results, performs rolling optimization on each reactive power zone, achieving centralized-distributed control. The centralized control of intraday optimization considers minimizing the average voltage deviation of the entire network within a time period, with optimization variables including the regulation amount of line flexible regulation devices and the reactive / active power regulation amount of each reactive power zone. The distributed control of intraday optimization considers the optimal operation of each reactive power zone at any given time, prioritizing the optimization of regulated resources in order of tracking response speed from slowest to fastest, and then considering reactive power voltage sensitivity indicators for reactive power resource optimization. Optimization variables include the reactive / active power regulation amount of regulated resources within each reactive power zone. Real-time regulation, based on intraday optimization, performs real-time adjustments according to set voltage or power thresholds to stabilize voltage fluctuations.

[0121] This embodiment achieves voltage optimization control by prioritizing reactive power regulation followed by active power reduction regulation. Optionally, active power reduction can also be implemented through proportional, uniform reduction. During the reduction period, if there is energy storage in the reactive power zone, active power reduction is prioritized by controlling energy storage charging, without affecting the unified arrangement of energy storage charging and discharging, followed by active power reduction for distributed power sources. The Jain fairness index is established to assess the fairness of active power reduction for each distributed power source, using the ratio of the reduced active power to the theoretical maximum active power output as a benchmark.

[0122] Specifically:

[0123] The main station employs centralized control to determine the daytime adjustment strategy through daytime optimization and intraday optimization to determine the centralized adjustment strategy. The control period for centralized control is t. jz The substation employs distributed control for intraday optimization to determine the distributed adjustment strategy, and local control for real-time optimization. The control period for distributed control is t. fbs , t jz =K dk t fbs K dk It is a positive number;

[0124] Among them, centralized control determines the next t. jz The operating power of each partition during the time period, and the next t determined by the distributed control and centralized control. jz Operating power constraints for a given time period determine the next t. jz within the time period t fbs The operating power of each partition during the time period, to meet the needs of each partition in that time period. jz Each t within the time period fbs The total power over a given period equals the sum of the power over that period t. jz Total operating power during the period:

[0125] In the formula, S jz S is the apparent power command for a certain zone issued by centralized control. fbs k represents the apparent power of the partition during actual operation. fbs k is the adjustable coefficient for the operating power of this partition. min,fbs ≤k fbs ≤k max,fbs k min,fbs and k max,fbs These are the minimum and maximum values ​​of the adjustable coefficient for the operating power of this partition, respectively.

[0126] The centrally controlled partitions are numbered i jz Let the maximum value of the number be I. jz Then, globally, the following equality constraint is satisfied:

[0127] In the formula, k jz This is an adjustable coefficient for the total operating power of a zone under centralized control, and the coefficient is determined based on the network loss situation of the zone. For the i-th jz The coefficient for adjustable operating power of each partition; k dk For integers, 1 ≤ k dk ≤K dk ; Centralized control is issued to the i-th jz Apparent power command for each partition; For the i-thjz The apparent power of each partition in actual operation;

[0128] The substation system of the partition receives each control cycle t fbs The power value within, and the controlled power value and adjustable power coefficient. Feedback is sent to the main station, which then uses the controlled power value and adjustable power coefficient fed back by the substation. Make overall control and decision-making decisions.

[0129] In this embodiment, controllable distribution area resources are considered as resource control nodes, including each distribution area-level microgrid as a controllable node. A microgrid can be a distribution area-level microgrid formed by one or more distribution areas. Considering reactive power zoning of the distribution network, different areas are divided for reactive power coordination control. These zones also include both controllable and non-controllable resource nodes. By optimizing the control of active and reactive power of distributed generation sources, active and reactive power at microgrid grid connection points, and the compensation amount of flexible regulation devices, the bidirectional voltage limit exceedance problem in active distribution networks can be effectively solved, and the voltage stability operation level can be improved.

[0130] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0131] Figure 3 is a schematic diagram of the structure of the active power distribution network zone multi-time-scale coordinated control device 30 provided in an embodiment of this application, including:

[0132] The acquisition module 31 is used to acquire the operating data of the power distribution network;

[0133] The first processing module 32 is used to divide the distribution network into zones based on the operating data and determine the voltage sensitivity index of each node in each zone.

[0134] The second processing module 33 is used to classify response capability levels according to the tracking response performance of the adjustment resources, and to determine the response order of each node adjustment resource in each partition according to the response capability level and voltage sensitivity index.

[0135] The third processing module 34 is used to determine the day-ahead adjustment strategy of the hourly adjustment resources of each partition through day-ahead optimization, determine the intraday adjustment strategy of the hourly and / or minute-level adjustment resources of each partition through intraday optimization, and the intraday adjustment strategy of the minute-level adjustment resources of each node through real-time optimization.

[0136] The control module 35 is used to control the corresponding regulation resources in the distribution network based on the regulation strategies of hourly regulation resources, minute-level regulation resources and second-level and below regulation resources.

[0137] As one possible implementation, the first processing module 32 is specifically used for:

[0138] Based on the relationship between node injected power and node voltage, the sensitivity factor matrices of the influence of active power increment and reactive power increment on node voltage amplitude are determined respectively.

[0139] Singular values ​​are extracted from the sensitivity factor matrix of the influence of active and reactive power increments on node voltage amplitude to obtain the reactive voltage sensitivity index and active voltage sensitivity index of the node.

[0140] As one possible implementation method, partitioning includes: reactive power compensation partitioning, active power reduction partitioning, and special node partitioning;

[0141] The second processing module 33 is specifically used for:

[0142] For reactive power compensation zones, the distribution network is divided into reactive power zones according to the community discovery algorithm. The response order of the adjustment resources of each node in the zone is as follows: if the adjustment resource tracking response speed is slow, it shall be prioritized according to the power control command requirements. If the tracking response speed is the same, the reactive power resource adjustment order of each node in the zone shall be determined according to the reactive power voltage sensitivity index of each node in the zone from large to small.

[0143] For active power reduction zones, priority is given to active power reduction of energy storage, microgrids, flexible interconnection devices, and devices with both energy storage and release capabilities. The active power reduction order of each node in the zone is determined according to the active power voltage sensitivity index of each node in the zone from largest to smallest. If the active power reduction of any node cannot be flexibly controlled, then the node is removed from the sequence.

[0144] For special node partitions, the access locations of special node partitions are determined according to the functional attributes of the voltage regulation devices of the distribution network lines participating in voltage control. The order of regulation resource response of each node in the partition is determined in descending order of the active voltage sensitivity index of each node in the partition.

[0145] As one possible implementation, the third processing module 34 is specifically used for:

[0146] The first objective function is established with the goal of minimizing the sum of voltage deviation and line loss of all nodes in the distribution network on the day to be dispatched.

[0147] Establish the constraints for the first objective function;

[0148] Based on the response order and the constraints of the first objective function, the solution of the first objective function is calculated, and the adjustment strategy of the hourly adjustment resources for each node is obtained.

[0149] As one possible implementation, the third processing module 34 is specifically used for:

[0150] The days to be scheduled are divided into multiple first time periods;

[0151] With the goal of minimizing the sum of voltage deviation and line loss of all nodes in the distribution network in each first time period, a second objective function is established and solved based on the optimization strategy given previously, to obtain the centralized regulation strategy of hourly and / or minute-level regulation resources for each node in each first time period;

[0152] Each first time period is divided into multiple second time periods;

[0153] For each partition, based on the centralized regulation strategy, a third objective function is established and solved with the goal of minimizing the sum of voltage deviation and line loss of all nodes in the partition in each second time period. This yields the distributed regulation strategy for the minute-level regulation resources of each node in each second time period. The distributed regulation strategy is the regulation strategy for the minute-level regulation resources of each node determined through intraday optimization.

[0154] As one possible implementation, the third processing module 34 is specifically used for:

[0155] Obtain the real-time voltage value of the power distribution network;

[0156] Based on the real-time voltage value and the preset target voltage value, determine the adjustment strategy for the adjustment resources at the second level and below for each node. As one possible implementation, the objective function takes the form:

[0157] In the formula, U t,i and U t,j Let U and t be the voltages at nodes i and j at time t, respectively, where j ≥ i; U0 is the nominal value of the node voltage; G ij and B ij These represent the line conductance and susceptance between node i and node j, respectively; θ t,ij U is the voltage phase angle difference between node i and node j at time t; α and β are weighting coefficients; U N P is the nominal voltage of the line. zbN For the main transformer capacity of the line;

[0158] The objective function can be a first objective function, a second objective function, or a third objective function;

[0159] When the objective function is the first objective function or the second objective function, n is the total number of nodes in the distribution network; when the objective function is the third objective function, n is the total number of nodes in the partition.

[0160] As one possible implementation, the second and third objective functions also satisfy the condition of minimizing the active power balance control regulation index:

[0161] In the formula, P resum,i The active power reduction at node i; t is time, t∈[1,T], and T is the number of time points; α R For binary coefficients, if P resum,i =0 when α R =0, otherwise α R =1.

[0162] As one possible implementation, if the objective function is a first objective function or a second objective function, then the constraints include: power balance constraints and control variable constraints;

[0163] If the objective function is a third objective function, then the constraints include: power balance constraints, control variable constraints, and total operating power constraints for the second time period determined according to the centralized adjustment strategy.

[0164] Power balance constraints include:

[0165] In the formula, P t,i P represents the active power injected into node i at time t. DG,t,i P represents the active power output of the distributed power inverter at node i at time t. DGth,t,i and P DGre,t,i These represent the theoretical output and active power reduction of the distributed power source at node i at time t, respectively; P micg,t,i and Q micg,t,i P represents the active and reactive power consumed by energy storage, microgrids, flexible interconnection devices, or regulating resources with energy storage functions at node i at time t, respectively; micgth,t,i and P micgre,t,i P represents the theoretical active power consumed and active power reduced at node i at time t, whether it is an energy storage device, microgrid, flexible interconnection device, or regulation resource with energy storage function. Lo,t,i λ represents the active power consumed by the load at node i at time t; ty P is the loss coefficient of the line flexible regulation device. ty,t,i Let be the active power of the series transformer in the flexible regulating device at node i of the line at time t; The voltage phasor of the line flexible regulating device at node i at time t; Let i be the current phasor of the line from node i-1 to node i.

[0166] This application implements a partitioned distribution network model. Based on the voltage sensitivity index of each node within each partition, the response order of regulation resources for each node within each partition is determined. Then, based on the response order of regulation resources, a multi-timescale optimization model is established, encompassing day-ahead, intraday, and real-time metrics. Day-ahead optimization determines the day-ahead regulation strategy for hourly regulation resources of each node; intraday optimization determines the intraday regulation strategy for hourly and minute-level regulation resources of each partition and node; and real-time optimization yields the regulation strategy for second-level and sub-second-level regulation resources of each node. This achieves multi-timescale partitioned collaborative control of distribution network regulation resources. This application can fully leverage the performance advantages of source-grid-load regulation resources and improve the voltage stability of active distribution networks.

[0167] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0168] Those skilled in the art will recognize that the templates, units, and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0169] If the module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above-described embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the above-described embodiments of the multi-time-scale zoned coordinated control method for active power distribution networks. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory, a random access memory, an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0170] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. An active power distribution network partition multi-time scale collaborative control method, characterized in that, include: Obtain operational data of the power distribution network; Based on the operational data, the power distribution network is divided into zones, and the voltage sensitivity index of each node in each zone is determined. The response capability levels are divided according to the tracking response performance of the regulating resources. Based on the response capability levels and the voltage sensitivity index, the response order of the regulating resources of each node in each partition is determined. Based on the response order, the day-ahead adjustment strategy for hourly adjustment resources of each partition is determined by day-ahead optimization, the intraday adjustment strategy for hourly and / or minute-level adjustment resources of each partition is determined by intraday optimization, and the intraday adjustment strategy for minute-level adjustment resources of each node is determined by intraday optimization. The adjustment strategy for second-level and below adjustment resources of each node is obtained by real-time optimization. Based on the regulation strategies of the hourly regulation resources, the minute-level regulation resources, and the second-level and below regulation resources, the corresponding regulation resources in the distribution network are controlled.

2. The active power distribution network partition multi-time scale collaborative control method of claim 1, wherein, The determination of the voltage sensitivity index of each node within each partition includes: Based on the relationship between node injected power and node voltage, the sensitivity factor matrices of the influence of active power increment and reactive power increment on node voltage amplitude are determined respectively. Singular values ​​are extracted from the sensitivity factor matrix of the influence of active and reactive power increments on node voltage amplitude to obtain the reactive voltage sensitivity index and active voltage sensitivity index of the node.

3. The active power distribution network partition multi-time scale collaborative control method of claim 2, wherein, The partitions include: reactive power compensation partitions, active power reduction partitions, and special node partitions; The step of determining the response order of resource adjustment for each node within each partition based on the response capability level and the voltage sensitivity index includes: For reactive power compensation zones, the distribution network is divided into reactive power zones according to the community discovery algorithm. The response order of the adjustment resources of each node in the zone is as follows: if the adjustment resource tracking response speed is slow, it will take priority action according to the power control command requirements. If the tracking response speed is the same, the reactive power resource adjustment order of each node in the zone will be determined according to the reactive power voltage sensitivity index of each node in the zone from large to small. For active power reduction zones, priority is given to active power reduction of energy storage, microgrids, flexible interconnection devices, and devices with both energy storage and release capabilities. The active power reduction order of each node in the zone is determined according to the active power voltage sensitivity index of each node in the zone from largest to smallest. If the active power reduction of any node cannot be flexibly controlled, then the node is removed from the sequence. For special node partitions, the access locations of special node partitions are determined according to the functional attributes of the voltage regulation devices of the distribution network lines participating in voltage control. The order of regulation resource response of each node in the partition is determined in descending order of the active voltage sensitivity index of each node in the partition.

4. The active power distribution network partition multi-time scale collaborative control method of claim 1, wherein, The day-ahead adjustment strategy for determining hourly adjustment resources for each partition through day-ahead optimization includes: A first objective function is established with the goal of minimizing the sum of voltage deviation and line loss of all nodes in the distribution network on the day to be dispatched. Establish the constraints for the first objective function; Based on the response order and the constraints of the first objective function, the solution of the first objective function is calculated to obtain the hourly adjustment strategy for each node's adjustment resources.

5. The active power distribution network partition multi-time scale collaborative control method of claim 1, wherein, The intraday adjustment strategy for determining hourly and / or minute-level resource adjustments for each partition through intraday optimization, and the intraday adjustment strategy for minute-level resource adjustments for each node, include: The days to be scheduled are divided into multiple first time periods; With the goal of minimizing the sum of voltage deviation and line loss of all nodes in the distribution network in each first time period, a second objective function is established and solved based on the optimization strategy given previously, to obtain a centralized regulation strategy for the hourly and / or minute-level regulation resources of each node in each first time period; Each first time period is divided into multiple second time periods; For each partition, based on the centralized regulation strategy, a third objective function is established and solved with the goal of minimizing the sum of voltage deviation and line loss of all nodes in the partition in each second time period. This yields a distributed regulation strategy for the minute-level regulation resources of each node in each second time period. The distributed regulation strategy is the regulation strategy for the minute-level regulation resources of each node determined through intraday optimization.

6. The active power distribution network partition multi-time scale collaborative control method of claim 1, wherein, The adjustment strategy for adjusting resources at the second level and below for each node through real-time optimization includes: Obtain the real-time voltage value of the power distribution network; Based on the real-time voltage value and the preset target voltage value, determine the adjustment strategy for the adjustment resources at the second level and below for each node.

7. The active power distribution network partition multi-time scale collaborative control method of claim 4 or 5, wherein, The objective function has the form: where U t,i and U t,j are the voltages of nodes i and j at time t, respectively, j > i; U0 is the nominal value of the node voltage; G ij and B ij are the conductance and susceptance of the line between nodes i and j, respectively; θ t,ij is the voltage phase angle difference between node i and node j at time t; and a and β are weight coefficients. U N is the line nominal voltage; P zbN is the line main transformer capacity; The objective function is a first objective function, a second objective function, or a third objective function; When the objective function is the first objective function or the second objective function, n is the total number of nodes in the distribution network; when the objective function is the third objective function, n is the total number of nodes in the partition.

8. The active power distribution network partition multi-time scale collaborative control method of claim 7, wherein, The second target function and the third target function also satisfy the condition that the active balance control adjustment index is minimum: In the formula, P resum,i is the active power reduction of node i; t is the time, t ∈ [1, T], T is the number of time; α R is a binary coefficient, if P resum,i = 0, α R = 0, otherwise α R = 1; If the objective function is a first objective function or a second objective function, then the constraints include: power balance constraints and control variable constraints; If the objective function is a third objective function, then the constraints include: power balance constraints, control variable constraints, and total operating power constraints for the second time period determined according to the centralized adjustment strategy. The power balance constraint includes: In the formula, P t,i P represents the active power injected into node i at time t. DG,t,i P represents the active power output of the distributed power inverter at node i at time t. DGth,t,i and P DGre,t,i These represent the theoretical output and active power reduction of the distributed power source at node i at time t, respectively; P micg,t,i and Q micg,t,i P represents the active and reactive power consumed by energy storage, microgrids, flexible interconnection devices, or regulating resources with energy storage functions at node i at time t, respectively; micgth,t,i and P micgre,t,i P represents the theoretical active power consumed and active power reduced at node i at time t, whether it is an energy storage device, microgrid, flexible interconnection device, or regulation resource with energy storage function. Lo,t,i λ represents the active power consumed by the load at node i at time t; ty P is the loss coefficient of the line flexible regulation device. ty,t,i Let be the active power of the series transformer in the flexible regulating device at node i of the line at time t; Vt(i) is the voltage phasor regulated by the line flexible regulation device at node i at time t; Let i be the current phasor of the line from node i-1 to node i.

9. An active power distribution network partition multi-time scale collaborative control system, characterized in that, The system is used to implement the method as described in any one of claims 1 to 8; the system includes a master station and a substation, and the control process of the system includes centralized control, distributed control, and local control; The main station adopts centralized control to determine day-ahead regulation strategy through day-ahead optimization and to determine centralized regulation strategy through day-in optimization, and the regulation time period of the centralized control is t jz ; the substation adopts distributed control to determine distributed regulation strategy through day-in optimization and adopts local control to perform real-time optimization, and the regulation time period of the distributed control is t fbs , t jz = K dk t fbs , K dk is a positive number; Among them, centralized control determines the next t. jz The operating power of each partition during the time period, and the next t determined by the distributed control and centralized control. jz Operating power constraints for a given time period determine the next t. jz within the time period t fbs The operating power of each partition during the time period, to meet the needs of each partition in that time period. jz Each t within the time period fbs The total power over a given period equals the sum of the power over that period t. jz Total operating power during the period: In the formula, S jz is the apparent power instruction of a certain subzone under centralized control, S fbs is the actual apparent power of the subzone, k fbs is the coefficient of the adjustable operating power of the subzone, k min,fbs ≤k fbs ≤k max,fbs , k min,fbs and k max,fbs are the minimum and maximum values of the coefficient of the adjustable operating power of the subzone, respectively. Number the partitions of the centralized control i jz , let the numbering value maximum I jz , then on the global meet the following equation constraints: In the formula, k jz is the coefficient of the total operating power adjustable under the partition of centralized control, which is determined according to the network loss of the partition; for the i jz th partition; k dk is an integer, 1≤k dk ≤K dk ; The apparent power command for the i-th jz zone is given by the centralized control; For the i-th jz The apparent power of each partition in actual operation; The substation system of the partition obtains the power value in each control period t fbs and the adjustable power coefficient Feedback to the master station, which determines the power value to be controlled and the adjustable power coefficient based on the feedback from the slave stations Make overall control and decision-making decisions.

10. An active power distribution network partition multi-time scale collaborative control device, characterized in that, include: The acquisition module is used to acquire operational data of the power distribution network. The first processing module is used to divide the power distribution network into zones based on the operating data and determine the voltage sensitivity index of each node in each zone. The second processing module is used to classify the tracking response capability levels of the adjustment resources according to the tracking response capability of the adjustment resources, and determine the orderly response order of the adjustment resources of each node in each partition. The third processing module is used to classify response capability levels according to the tracking response performance of the adjustment resources, and to determine the response order of each node's adjustment resources in each partition according to the response capability level and the voltage sensitivity index. The fourth processing module is used to determine the day-ahead adjustment strategy of the hourly adjustment resources of each partition through day-ahead optimization, the intraday adjustment strategy of the hourly and / or minute-level adjustment resources of each partition through intraday optimization, the intraday adjustment strategy of the minute-level adjustment resources of each node, and the adjustment strategy of the second-level and below adjustment resources of each node through real-time optimization, based on the response order. The control module is used to control the corresponding regulation resources in the distribution network based on the regulation strategies of the hourly regulation resources, the minute-level regulation resources, and the second-level and below regulation resources.

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