CN117394380A - Distributed reactive voltage control method and system for power distribution network by adopting relaxation iteration - Google Patents

Distributed reactive voltage control method and system for power distribution network by adopting relaxation iteration Download PDF

Info

Publication number
CN117394380A
CN117394380A CN202311677656.2A CN202311677656A CN117394380A CN 117394380 A CN117394380 A CN 117394380A CN 202311677656 A CN202311677656 A CN 202311677656A CN 117394380 A CN117394380 A CN 117394380A
Authority
CN
China
Prior art keywords
reactive
distributed
regional
optimization model
distribution network
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202311677656.2A
Other languages
Chinese (zh)
Other versions
CN117394380B (en
Inventor
徐秋实
卢子敬
贺继峰
王俊琪
张焱哲
李子寿
王博
林常青
乔立
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
State Grid Hubei Electric Power Co Ltd
Economic and Technological Research Institute of State Grid Hubei Electric Power Co Ltd
Original Assignee
State Grid Hubei Electric Power Co Ltd
Economic and Technological Research Institute of State Grid Hubei Electric Power Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by State Grid Hubei Electric Power Co Ltd, Economic and Technological Research Institute of State Grid Hubei Electric Power Co Ltd filed Critical State Grid Hubei Electric Power Co Ltd
Priority to CN202311677656.2A priority Critical patent/CN117394380B/en
Publication of CN117394380A publication Critical patent/CN117394380A/en
Application granted granted Critical
Publication of CN117394380B publication Critical patent/CN117394380B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • H02J3/16—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by adjustment of reactive power
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
    • H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/18—Arrangements for adjusting, eliminating or compensating reactive power in networks
    • H02J3/1821—Arrangements for adjusting, eliminating or compensating reactive power in networks using shunt compensators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/48—Controlling the sharing of the in-phase component
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
    • G06F2111/04—Constraint-based CAD
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00—Details relating to the application field
    • G06F2113/04—Power grid distribution networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/40—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation wherein a plurality of decentralised, dispersed or local energy generation technologies are operated simultaneously
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/30—Reactive power compensation

Abstract

A distributed reactive voltage control method and system for a power distribution network adopts relaxation iteration, firstly, a centralized reactive voltage optimization model P2 considering discrete and continuous reactive equipment is constructed, then the power distribution network is split into a plurality of regional subnetworks, the model P2 is converted into a distributed reactive power optimization model P3 based on the regional subnetworks, then discrete variables in the model P3 are relaxed into continuous variables, so that a relaxed distributed reactive power optimization model P4 is constructed, a distributed reactive power optimization model P5 of each regional subnetwork is constructed according to the model P2 and given boundary variables, and then the models P4 and P5 are solved in an interactive iteration mode by adopting a nested circulation alternating direction multiplier method, so that a distributed reactive voltage optimal control strategy is obtained. The method improves the convergence and the calculation feasibility of the non-convex reactive power optimization model, and realizes the accurate and efficient solution of the reactive power voltage optimization model of the power distribution network.

Description

Distributed reactive voltage control method and system for power distribution network by adopting relaxation iteration
Technical Field
The invention belongs to the field of reactive voltage control of power distribution networks, and particularly relates to a distributed reactive voltage control method and system for a power distribution network by adopting relaxation iteration.
Background
The distributed new energy is developed greatly, the energy structure of the power grid is optimized, and the planning of the construction of a novel power system is complied with. However, the complexity of operation management of the power distribution network is increased due to the fact that a large amount of distributed energy sources are connected, reactive power optimization is used as an effective management means of the power distribution network, network loss can be effectively reduced through cooperative control of the distributed energy sources and reactive power compensation equipment, voltage out-of-limit is eliminated, and the power distribution network is widely focused in recent years.
It is worth noting that most of the existing reactive power optimization methods adopt a centralized framework, and along with expansion of the interconnection network, the applicability of the centralized reactive power voltage control methods is limited due to communication bottlenecks, privacy protection, computational complexity and the like. At present, various distributed optimization algorithms have been successfully applied to the field of power distribution networks, such as an alternate multiplier method, an auxiliary problem principle method and a target cascade analysis method. The alternative direction multiplier method (Alternating direction method of multipliers, ADMM) is widely used because of its easy convergence and strong scalability. For this reason, researchers have developed distributed reactive voltage control schemes using ADMM, with information exchange between adjacent distribution networks.
However, since discrete reactive power resources are not fully considered in existing distributed reactive voltage control schemes. They are all based on continuous reactive resources, so that better convergence can be achieved. Notably, the sub-problem convexity is the key to the ability of ADMM to converge. In the reactive voltage control problem, a large number of integer variables are introduced into the discrete reactive equipment, so that the reactive voltage optimization sub-problem belongs to a non-convex problem, and the problems of non-convergence and poor solvability of the ADMM method occur. Therefore, to better solve the distributed reactive voltage control problem of the power distribution network, improvements to the ADMM method are needed to improve model convergence and resolvability.
Disclosure of Invention
The invention aims to solve the problems in the prior art and provide a distributed reactive voltage control method and a distributed reactive voltage control system for a power distribution network, which can improve model convergence and calculation efficiency and adopt relaxation iteration.
In order to achieve the above object, the technical scheme of the present invention is as follows:
in a first aspect, the present invention proposes a distributed reactive voltage control method for a power distribution network using relaxation iteration, including:
s1, constructing a centralized reactive voltage optimization model considering discrete and continuous reactive equipment, wherein the discrete reactive equipment comprises an on-load voltage regulating transformer and a switchable capacitor;
s2, splitting the power distribution network into a plurality of regional subnetworks, and converting the centralized reactive voltage optimization model into a distributed reactive power optimization model based on the plurality of regional subnetworks;
s3, loosening discrete variables in the distributed reactive power optimization model based on the multiple regional subnetworks into continuous variables to construct a loose distributed reactive power optimization model; constructing a distributed reactive power optimization model of each regional subnetwork according to the distributed reactive power optimization model based on the multiple regional subnetworks and a given boundary variable;
s4, solving a loose distributed reactive power optimization model by adopting an alternate direction multiplier method to obtain an optimal solution of the boundary coupling variable;
s5, solving a distributed reactive power optimization model of each regional subnetwork based on an optimal solution of the boundary coupling variable to obtain an integer solution of each reactive power device;
and S6, judging whether convergence conditions are met, if so, outputting a distributed reactive voltage optimal control strategy, otherwise, reconstructing a loose distributed reactive optimization model based on integer solutions of all reactive equipment, and returning to S4 for the next iteration.
In the step S2, converting the centralized reactive voltage optimization model into a distributed reactive power optimization model based on a plurality of regional subnetworks includes:
s21, adopting an alternate direction multiplication method to carry out consistency relaxation treatment on boundary coupling variables between adjacent regional subnetworks by adopting a Lagrangian function;
s22, constructing a distributed reactive power optimization model based on a plurality of regional subnetworks based on the boundary coupling variables after relaxation:
；
in the above-mentioned method, the step of,for regional subnetwork->Is used for the function of the object of (a),/>、/>regional subnetworks->Inequality, equality constraint of->For regional subnetwork->Local variable of->、/>Regional subnetworks->Local discrete variable, local continuous variable,/-for (a)>For regional subnetwork->And its neighboring regional subnetwork->The boundary between the two is coupled with a variable,for regional subnetwork->And its neighboring regional subnetwork->Global variable between->Is the number of regional subnetworks.
In the step S3, the loose distributed reactive power optimization model is as follows:
；
in the above-mentioned method, the step of,to +.>Continuous variable after relaxation treatment, +.>Is a->A set of adjacent regional subnetworks;
the distributed reactive power optimization model of each regional subnetwork is as follows:
；
in the above-mentioned method, the step of,is a positive integer.
In S6, the convergence condition includes:
；
in the above-mentioned method, the step of,is the sum of the objective functions of all area subnetworks in the z-th iteration, is +.>Is a set convergence criterion.
The S1 comprises the following steps:
s11, constructing a centralized reactive voltage optimization initial model considering discrete and continuous reactive equipment by taking network loss and minimum voltage deviation as targets, wherein the objective function of the centralized reactive voltage optimization initial model considering the discrete and continuous reactive equipment is as follows:
；
in the above-mentioned method, the step of,for the purpose of +.>、/>Weight coefficients of active loss and node voltage deviation of power distribution network respectively, < >>For distribution network branches->Resistance value of>For t period distribution network branch->Is>For optimizing the duration of the period>For the voltage amplitude of node i of period t, +.>For the reference voltage value>、/>The distribution network branch sets and the distribution network node sets are respectively +.>To optimize the number of time periods;
the constraint conditions comprise power flow constraint of the power distribution network, operation constraint of the on-load voltage regulating transformer, operation constraint of the switchable capacitor and operation constraint of the distributed power supply;
s12, performing convex relaxation conversion on variables in the centralized reactive voltage optimization initial model considering the discrete and continuous reactive equipment, so as to construct and obtain the centralized reactive voltage optimization model considering the discrete and continuous reactive equipment.
The power distribution network power flow constraint comprises:
；
；
；
；
；
in the above-mentioned method, the step of,、/>distribution network branches with t time periods respectively>、/>Active power, < >>、/>Active power and reactive power of a node i are respectively injected into a distributed power supply in a t period, and the power is +.>、/>Active, reactive load of node i at time t respectively,>、/>distribution network branches with t time periods respectively>、/>Reactive power of>Reactive power of node i is injected into the switchable capacitor bank at time t +.>、/>The upper limit and the lower limit of the voltage amplitude are allowed respectively;
the on-load tap changer operating constraints include:
；
；
；
in the above-mentioned method, the step of,for distribution network branches->Initial transformation ratio of upper transformer, +.>For t period distribution network branch->The number of gears of the upper transformer, +.>For distribution network branches->Increment of each gear ratio of upper transformer, +.>For optimizing the gear value of the transformer's allowed action during the period,/->For the maximum gear value of the transformer, < >>Is a positive integer;
the switchable capacitor operating constraints include:
；
；
；
in the above-mentioned method, the step of,the number of capacitors put into node i for the period t, < >>Reactive power output for node i single capacitor, +.>To optimize the number of allowable actions of the switchable capacitor bank during the time period +.>The maximum number of the capacitors in the capacitor bank can be switched for the node i;
the distributed power operation constraint includes:
；
；
；
in the above-mentioned method, the step of,predicted value of active power output of distributed power supply at node i at time t>For the distributed power factor angle at node i, +.>Active capacity of the distributed power supply at node i;
in S12, the convex relaxation conversion includes:
linearizing and relaxing power flow constraint of the power distribution network; linearizing the absolute value phase in the centralized reactive voltage optimization initial model; and performing second-order cone relaxation treatment on the operation constraint of the distributed power supply.
In a second aspect, the invention provides a distributed reactive voltage control system of a power distribution network, which comprises a centralized reactive voltage optimization model construction module, a distributed reactive power optimization model construction module, a relaxation processing module, a sub-network model construction module and an iterative calculation module, wherein the distributed reactive power optimization model construction module is used for carrying out relaxation iteration;
the centralized reactive voltage optimization model construction module is used for constructing a centralized reactive voltage optimization model considering discrete and continuous reactive equipment, wherein the discrete reactive equipment comprises an on-load voltage regulating transformer and a switchable capacitor;
the distributed reactive power optimization model construction module is used for splitting the power distribution network into a plurality of regional subnetworks and converting the centralized reactive power voltage optimization model into a distributed reactive power optimization model based on the regional subnetworks;
the relaxation processing module is used for relaxing discrete variables in the distributed reactive power optimization model based on the plurality of regional subnetworks into continuous variables so as to construct a relaxed distributed reactive power optimization model;
the sub-network model building module is used for building a distributed reactive power optimization model of each regional sub-network according to the distributed reactive power optimization model based on a plurality of regional sub-networks and given boundary variables;
the iterative computation module is used for solving the loose distributed reactive power optimization model by adopting an alternate direction multiplier method to obtain an optimal solution of the boundary coupling variable, then solving the distributed reactive power optimization model of each regional subnetwork based on the optimal solution of the boundary coupling variable to obtain an integer solution of each reactive power equipment, judging whether convergence conditions are met, outputting a distributed reactive power voltage optimal control strategy if the convergence conditions are met, otherwise, reconstructing the loose distributed reactive power optimization model based on the integer solution of each reactive power equipment, and performing the next iteration.
The distributed reactive power optimization model building module comprises an area decomposition unit, a consistency relaxation processing unit and a distributed reactive power optimization model building unit;
the regional decomposition unit is used for dividing the power distribution network into a plurality of regional subnetworks;
the consistency relaxation processing unit is used for carrying out consistency relaxation processing on boundary coupling variables between adjacent regional subnetworks by adopting a Lagrange method by using an alternate direction multiplier method;
the distributed reactive power optimization model construction unit is used for constructing a distributed reactive power optimization model based on a plurality of regional subnetworks based on the boundary coupling variable after relaxation treatment as follows:
；
in the above-mentioned method, the step of,for regional subnetwork->Is>、/>Regional subnetworks->Inequality, equality constraint of->For regional subnetwork->Local variable of->、/>Regional subnetworks->Local discrete variable, local continuous variable,/-for (a)>For regional subnetwork->And its neighboring regional subnetwork->The boundary between the two is coupled with a variable,for regional subnetwork->And its neighboring regional subnetwork->Global variable between.
The relaxation processing module is used for constructing a relaxation distributed reactive power optimization model:
；
in the above-mentioned method, the step of,to +.>Continuous variable after relaxation treatment, +.>Is a->A set of adjacent regional subnetworks;
the sub-network model building module is used for building a distributed reactive power optimization model of each region sub-network as follows:
；
in the above-mentioned method, the step of,is a positive integer.
The iterative computation module is used for judging whether the convergence condition is met or not based on the following formula:
；
in the above-mentioned method, the step of,is the sum of the objective functions of all area subnetworks in the z-th iteration, is +.>Is a set convergence criterion.
The centralized reactive voltage optimization model building module comprises an initial module building unit and a convex relaxation conversion unit;
the initial module construction unit is used for constructing a centralized reactive voltage optimization initial model taking the minimum network loss and voltage deviation into consideration, wherein the centralized reactive voltage optimization initial model is as follows:
；
in the above-mentioned method, the step of,for the purpose of +.>、/>Weight coefficients of active loss and node voltage deviation of power distribution network respectively, < >>For distribution network branches->Resistance value of>For t period distribution network branch->Is>For optimizing the duration of the period>For the voltage amplitude of node i of period t, +.>For the reference voltage value>、/>The distribution network branch sets and the distribution network node sets are respectively +.>To optimize the number of time periods;
the constraint conditions comprise power flow constraint of the power distribution network, operation constraint of the on-load voltage regulating transformer, operation constraint of the switchable capacitor and operation constraint of the distributed power supply;
the convex relaxation conversion unit is used for carrying out convex relaxation conversion on variables in the initial model of the centralized reactive voltage optimization considering the discrete and continuous reactive equipment, so that the centralized reactive voltage optimization model considering the discrete and continuous reactive equipment is constructed.
The power distribution network power flow constraint comprises:
；
；
；
；
；
in the above-mentioned method, the step of,、/>distribution network branches with t time periods respectively>、/>Active power, < >>、/>Active power and reactive power of a node i are respectively injected into a distributed power supply in a t period, and the power is +.>、/>Active, reactive load of node i at time t respectively,>、/>distribution network branches with t time periods respectively>、/>Reactive power of>Reactive power of node i is injected into the switchable capacitor bank at time t +.>、/>The upper limit and the lower limit of the voltage amplitude are allowed respectively;
the on-load tap changer operating constraints include:
；
；
；
in the above-mentioned method, the step of,for distribution network branches->Initial transformation ratio of upper transformer, +.>For t period distribution network branch->The number of gears of the upper transformer, +.>For distribution network branches->Increment of each gear ratio of upper transformer, +.>For optimizing the gear value of the transformer's allowed action during the period,/->For the maximum gear value of the transformer, < >>Is a positive integer;
the switchable capacitor operating constraints include:
；
；
；
in the above-mentioned method, the step of,the number of capacitors put into node i for the period t, < >>Single capacitor output for node iReactive power of>To optimize the number of allowable actions of the switchable capacitor bank during the time period +.>The maximum number of the capacitors in the capacitor bank can be switched for the node i;
the distributed power operation constraint includes:
；
；
；
in the above-mentioned method, the step of,predicted value of active power output of distributed power supply at node i at time t>For the distributed power factor angle at node i, +.>Active capacity of the distributed power supply at node i;
the convex relaxation transition comprises:
linearizing and relaxing power flow constraint of the power distribution network; linearizing the absolute value phase in the centralized reactive voltage optimization initial model; and performing second-order cone relaxation treatment on the operation constraint of the distributed power supply.
Compared with the prior art, the invention has the beneficial effects that:
the invention discloses a distributed reactive voltage control method of a power distribution network, which comprises the steps of firstly constructing a distributed reactive voltage optimization model considering discrete and continuous reactive power equipment, splitting the power distribution network into a plurality of regional sub-networks, converting the distributed reactive voltage optimization model into a distributed reactive power optimization model based on the plurality of regional sub-networks, loosening discrete variables in the distributed reactive power optimization model based on the plurality of regional sub-networks into continuous variables to construct the loose distributed reactive power optimization model, constructing the distributed reactive power optimization model of each regional sub-network according to the distributed reactive power optimization model based on the plurality of regional sub-networks and given boundary variables, then solving the loose distributed reactive power optimization model by adopting an alternate direction multiplier method to obtain an optimal solution of boundary coupling variables, then solving the distributed reactive power optimization model of each regional sub-network based on the optimal solution of boundary coupling variables, finally judging whether convergence conditions are met, if so, outputting the optimal solution, otherwise, carrying out next iteration after reconstructing the loose distributed reactive power optimization model based on the integer solution of each reactive power equipment, solving the discrete reactive power optimization model by adopting the alternate direction multiplier method, and solving the problem of the alternate reactive power optimization model, thereby realizing the optimal solution of the reactive power distribution network by adopting the alternate direction multiplier method, and the method is difficult to realize, and the optimal solution of the reactive power distribution network is improved.
Drawings
Fig. 1 is an exploded view of a power distribution network according to embodiment 1.
Fig. 2 is a topology structure diagram of the power distribution network after the area decomposition in embodiment 1.
FIG. 3 is a flow chart of model solving using the nested cyclic alternating direction multiplier method in example 1
Fig. 4 is a distributed reactive voltage optimization convergence curve of example 1.
Fig. 5 is a block diagram of the system described in embodiment 2.
Detailed Description
The present invention will be described in further detail with reference to the following detailed description and the accompanying drawings.
The invention provides a distributed reactive voltage control method of a power distribution network by adopting relaxation iteration, which takes minimum network loss and voltage deviation as objective functions, builds a centralized reactive optimization model to realize coordinated optimization of continuous and discrete reactive equipment, then introduces an alternate direction multiplier method, converts the centralized reactive voltage control model into a distributed model by carrying out Lagrange relaxation on coupling variables among different power distribution networks and utilizing information exchange among adjacent power distribution networks, and finally carries out iterative computation by the variable relaxation and using a nested circulation alternate direction multiplier method, wherein the nested circulation alternate direction multiplier method allows the relaxed distributed reactive optimization model to be solved in a distributed mode to obtain optimal solutions of boundary coupling variables among all regional subnetworks, thereby ensuring the convergence of an algorithm; on the basis, based on the boundary coupling variable optimal solution, solving a distributed reactive power optimization model of each regional subnetwork to determine an optimal solution of the discrete reactive power equipment; through interactive iteration of the two models, the convergence and the calculation efficiency of the distributed reactive voltage control model are improved, and an accurate and feasible distributed reactive voltage optimal control strategy can be obtained.
Example 1:
a distributed reactive voltage control method for a power distribution network adopting relaxation iteration is carried out sequentially according to the following steps:
1. the method comprises the steps of constructing a centralized reactive voltage optimization initial model taking network loss and voltage deviation as targets, wherein the centralized reactive voltage optimization initial model takes discrete and continuous reactive equipment into consideration, the discrete reactive equipment comprises an on-load voltage regulating transformer and a switchable capacitor, the continuous reactive equipment is a distributed power supply, and the objective function of the centralized reactive voltage optimization model taking the discrete and continuous reactive equipment into consideration is as follows:
（1）
in the above-mentioned method, the step of,for the purpose of +.>、/>Weight coefficients of active loss and node voltage deviation of power distribution network respectively, < >>For distribution network branches->Resistance value of>For t period distribution network branch->Is>For optimizing the duration of the period>For the voltage amplitude of node i of period t, +.>For reference voltage values, when the node voltage is within the desired voltage range, i.e.，/>，/>And->An upper limit and a lower limit of the set desired voltage, respectively; when the node voltage satisfies->，/>The method comprises the steps of carrying out a first treatment on the surface of the When the node voltage satisfies->，/>；/>、/>The distribution network branch sets and the distribution network node sets are respectively +.>To optimize the number of time periods;
the constraint conditions include:
power distribution network tide constraint
（2）
（3）
（4）
（5）
（6）
In the above formula, the formula (2) and the formula (3) respectively represent active power flow and reactive power flow equations, the formula (4) is a branch voltage equation, the formula (5) is a branch power flow equation, the formula (6) represents a node voltage safety range,、/>distribution network branches with t time periods respectively>、/>Active power, < >>、/>Active and reactive power of the node i are respectively injected into the distributed power supply in the period t,、/>active, reactive load of node i at time t respectively,>、/>distribution network branches with t time periods respectively>、Reactive power of>Reactive power of node i is injected into the switchable capacitor bank at time t +.>、/>The upper limit and the lower limit of the voltage amplitude are allowed respectively;
on-load tap changer operating constraints
（7）
（8）
（9）
In the above formula, the formula (7) represents a voltage constraint equation at two ends of the transformer, the formula (8) represents a transformer action time constraint, the formula (9) represents a gear constraint,for distribution network branches->Initial transformation ratio of upper transformer, +.>For t period distribution network branch->The number of gears of the upper transformer, +.>For distribution network branches->Increment of each gear ratio of upper transformer, +.>For optimizing the gear value of the transformer's allowed action during the period,/->For the maximum gear value of the transformer, < >>Is a positive integer;
switchable capacitor operation constraints
（10）
（11）
（12）
In the above formula, the formula (10) is the output reactive power constraint, the formula (11) represents the action times limitation constraint of the capacitor in the operation optimization period, the formula (12) is the input quantity constraint of the capacitor,the number of capacitors put into node i for the period t,reactive power output for node i single capacitor, +.>To optimize the number of allowable actions of the switchable capacitor bank during the time period +.>The maximum number of the capacitors in the capacitor bank can be switched for the node i;
distributed power supply operation constraints
（13）
（14）
（15）
In the above formula, the formula (13) is the active power output by the distributed power supply, the formula (14) is the active power output by the distributed power supply, the formula (15) represents the capacity constraint of the distributed power supply,a predicted value of the active power output of the distributed power supply is distributed for the node i at the time t,for the distributed power factor angle at node i, +.>Is the active capacity of the distributed power supply at node i.
The objective function 1 and the constraint conditions 2-15 form a centralized reactive voltage optimization initial model P1 considering discrete and continuous reactive equipment, which essentially belongs to the mixed integer nonlinear programming (Mixed integer nonlinear programming, MINLP) problem category, comprises a large number of integer variables and nonlinear constraints, is difficult to solve effectively, and needs to perform convex relaxation treatment.
2. Convex relaxation conversion
For power flow constraint of power distribution network, introducing auxiliary variableAnd->Let it be equal to->，/>They are brought into formulas (2) - (4) and (6) to linearize them as follows:
（16）
（17）
（18）
（19）/>
the formula (5) adopts a second order cone technology to carry out relaxation treatment, and the method is as follows:
（20）
for the absolute values in the initial model of the centralized reactive voltage optimization taking into account the discrete and continuous reactive devices, it is also linearized by introducing auxiliary variables, taking formula (11) as an example, the linearization process is as follows:
（21）
（22）
（23）
in the above-mentioned method, the step of,、/>two auxiliary variables are introduced.
For other absolute terms, such as equation (8) and equation (1), the same applies.
For distributed power capacity constraint, a second order cone relaxation process is adopted as follows:
（24）
by the convex relaxation conversion described above, the original mixed integer nonlinear programming model P1 is converted into a mixed integer second order cone programming model P2, i.e. a centralized reactive voltage optimization model taking into account discrete and continuous reactive equipment.
3. The power distribution network is decomposed into a plurality of regional subnetworks through regional decomposition, wherein each subnetwork can directly perform optimal control on local reactive power equipment, as shown in fig. 1. In this embodiment, the distribution network is decomposed into 5 area subnetworks by decomposing the interconnecting lines between adjacent distribution networks, as shown in fig. 2.
Each regional subnetwork can construct its reactive power optimization model, so as to obtain a model P3, and the expression is as follows:
（25）
in the above-mentioned method, the step of,for regional subnetwork->Is>、/>Regional subnetworks->Inequality, equality constraint of (2) to (15), and relaxation treatment using formulas (16) to (24), is carried out>For regional subnetwork->Local variable of->、/>Regional subnetworks->Local discrete variable, local continuous variable,/-for (a)>For regional subnetwork->And its neighboring regional subnetwork->Boundary coupling variable between->For regional subnetwork->And its neighboring regional subnetwork->Global variable between->Is the number of regional subnetworks.
4. And adopting an alternate direction multiplier method to carry out consistency relaxation treatment on boundary coupling variables between adjacent regional subnetworks by adopting a Lagrange function, and then adding the consistency relaxation treatment to an objective function to obtain a distributed reactive power optimization model P3 based on a plurality of regional subnetworks. Wherein the Lagrangian function is as follows:
（26）/>
in the above-mentioned method, the step of,as a Lagrangian function->For regional subnetwork->Global variable of->For regional subnetwork->Sub-network of adjacent area>Is>Is a lagrangian penalty factor.
5. For the reactive voltage optimization model P3, integer variables exist, so that the reactive voltage optimization model P is essentially a non-male model, and if an alternate direction multiplier method is directly used, the problems of poor convergence, poor solvability and the like can occur. To this end, a relaxed iteration framework is constructed as follows:
on the one hand, discrete variables in the model P3Relaxing into continuous variable->The original non-convex mixed integer second order cone planning problem P3 is converted into a distributed reactive power optimization model P4 of the second order cone planning problem:
（27）
the second order cone programming problem essentially belongs to the convex programming category, the optimality of the solution and the computational efficiency can be improved, and the optimal solution can be obtained in polynomial time by utilizing the existing commercial solvers such as Cplex, gurobi, mosek and the like.
On the other hand, on the basis of the model P3, a distributed reactive power optimization model P5 of each regional subnetwork can be constructed based on given boundary variables:
（28）
the independent sub-model P5 is a model in which boundary variables are removed compared to the model P3, and the on-load tap changer gear number and the switchable capacitor input number in the independent sub-model P5 are described by integer variables compared to the model P4.
6. Based on the constructed models P4 and P5, the model solving is carried out by adopting a nested circulation alternating direction multiplier method, as shown in fig. 3, and the method specifically comprises the following steps:
6.1, given an initial value of the number of iterations z=0;
and 6.2, solving a loose distributed reactive power optimization model by adopting an alternate direction multiplier method to obtain an optimal solution of a boundary coupling variable, wherein a variable update formula of the alternate direction multiplier method in an iterative process is as follows:
（29）
（30）
（31）
the convergence criterion of the distributed reactive voltage optimization model of the power distribution network based on the alternating direction multiplier method can be determined by an original residual and a dual residual, wherein the original residual is iterated for the kth timeDual residual error. Given tolerance->The convergence criterion is the original residual and the dual residual, which are small enough, the largest element in the kth iteration, i.e.>Must be less than a given tolerance, expressed as follows:
（32）
6.3, solving a distributed reactive power optimization model of each regional subnetwork based on an optimal solution of the boundary coupling variable to obtain an integer solution of each reactive power device, wherein the integer solution comprises a transformer gear value and the input number of switchable capacitors;
6.4, judging whether convergence conditions are met, if yes, outputting a distributed reactive voltage optimal control strategy, including a gear value of an on-load voltage regulating transformer, wherein the number of switched capacitors, the output of a distributed power supply, node voltage, branch power flow, network loss and the like, otherwise reconstructing a loose distributed reactive power optimal model P4 based on integer solutions of reactive power equipment, enabling z=z+1, and returning to 6.2 for the next iteration, wherein the convergence conditions comprise:
（33）
in the above-mentioned method, the step of,is the sum of the objective functions of all area subnetworks in the z-th iteration, is +.>Is a set convergence criterion.
Fig. 4 shows the convergence performance of the distributed reactive voltage optimization model of the present embodiment at different time periods. It is apparent that as the number of iterations increases, the boundary residuals gradually converge to a given tolerance due to the constraint of consistency conditions. In general, the process of iterative convergence is a process of trade-off between distribution networks in different areas. Finally, after multiple iterations, all reactive voltage optimization problems in different optimization periods are converged. These results indicate that the method provided by the invention has better accuracy and convergence.
In addition, in order to examine the feasibility of the method, a power distribution network comprising three regional subnetworks is constructed, each regional subnetwork is respectively an IEEE 13 node system, an IEEE 33 node system and an IEEE 37 node system, and the following three scenes are set for respectively carrying out reactive voltage control:
scene 1: the distributed reactive voltage control model is characterized by comprising a distributed reactive voltage control model;
scene 2: a centralized reactive voltage control model;
scene 3: and a free-standing reactive voltage control model.
Comparing the optimized results of different scenes, the results are shown in table 1:
table 1 optimization results for three scenarios
As can be seen from table 1, the objective function values (including total power loss and voltage bias) of the distributed scheme are close to those of the centralized scheme, compared to the centralized scheme. Thus, the accuracy of the distributed scheme is satisfactory. Meanwhile, the voltage deviation is not equal to that of the independent scheme, however, the power loss of the independent scheme is larger because the different power distribution networks are not in coordination and optimization (because they are not physically connected). The above conclusion is still maintained in the multi-period test. Therefore, the distributed reactive voltage control method for the power distribution network adopting the relaxation iteration is feasible.
Example 2:
as shown in fig. 5, the distributed reactive voltage control system of the power distribution network adopting relaxation iteration comprises a centralized reactive voltage optimization model building module, a distributed reactive power optimization model building module, a relaxation processing module, a sub-network model building module and an iteration calculation module, wherein the centralized reactive voltage optimization model building module comprises an initial module building unit and a convex relaxation conversion unit, and the distributed reactive power optimization model building module comprises a regional decomposition unit, a consistency relaxation processing unit and a distributed reactive power optimization model building unit.
The initial module construction unit is used for constructing a centralized reactive voltage optimization initial model taking the minimum network loss and voltage deviation into consideration, wherein the centralized reactive voltage optimization initial model is as follows:
；
in the above-mentioned method, the step of,for the purpose of +.>、/>Weight coefficients of active loss and node voltage deviation of power distribution network respectively, < >>For distribution network branches->Resistance value of>For t period distribution network branch->Is>For optimizing the duration of the period>For the voltage amplitude of node i of period t, +.>For the reference voltage value>、/>The distribution network branch sets and the distribution network node sets are respectively +.>To optimize the number of time periods;
constraint conditions:
power distribution network tide constraint:
；
；
；
；
；
in the above-mentioned method, the step of,、/>respectively t timesSection distribution network branch->、/>Active power, < >>、/>Active power and reactive power of a node i are respectively injected into a distributed power supply in a t period, and the power is +.>、/>Active, reactive load of node i at time t respectively,>、/>distribution network branches with t time periods respectively>、/>Reactive power of>Reactive power of node i is injected into the switchable capacitor bank at time t +.>、/>The upper limit and the lower limit of the voltage amplitude are allowed respectively;
on-load tap changing transformer operating constraints:
；
；/>
；
in the above-mentioned method, the step of,for distribution network branches->Initial transformation ratio of upper transformer, +.>For t period distribution network branch->The number of gears of the upper transformer, +.>For distribution network branches->Increment of each gear ratio of upper transformer, +.>For optimizing the gear value of the transformer's allowed action during the period,/->For the maximum gear value of the transformer, < >>Is a positive integer;
switchable capacitor operation constraints:
；
；
；
in the above-mentioned method, the step of,the number of capacitors put into node i for the period t, < >>Reactive power output for node i single capacitor, +.>To optimize the number of allowable actions of the switchable capacitor bank during the time period +.>The maximum number of the capacitors in the capacitor bank can be switched for the node i;
distributed power supply operation constraints:
；
；
；
in the above-mentioned method, the step of,predicted value of active power output of distributed power supply at node i at time t>For distributed power at node iFactor angle->Is the active capacity of the distributed power supply at node i.
The convex relaxation conversion unit is used for carrying out convex relaxation conversion on variables in the initial model of the centralized reactive voltage optimization taking into account the discrete and continuous reactive equipment, so that the centralized reactive voltage optimization model taking into account the discrete and continuous reactive equipment is constructed, and the specific process is shown in the embodiment step 2.
The regional decomposition unit is used for dividing the power distribution network into a plurality of regional subnetworks.
The consistency relaxation processing unit is used for carrying out consistency relaxation processing on boundary coupling variables between adjacent regional subnetworks by adopting a Lagrange method by using an alternate direction multiplier method,
the distributed reactive power optimization model construction unit is used for constructing a distributed reactive power optimization model based on a plurality of regional subnetworks based on the boundary coupling variable after relaxation treatment as follows:
；/>
in the above-mentioned method, the step of,for regional subnetwork->Is>、/>Regional subnetworks->Inequality, equality constraint of->Is a region ofDomain subnetwork->Local variable of->、/>Regional subnetworks->Local discrete variable, local continuous variable,/-for (a)>For regional subnetwork->And its neighboring regional subnetwork->The boundary between the two is coupled with a variable,for regional subnetwork->And its neighboring regional subnetwork->Global variable between.
The relaxation processing module is used for relaxing discrete variables in the distributed reactive power optimization model based on the plurality of regional subnetworks into continuous variables so as to construct a loose distributed reactive power optimization model as follows:
；
in the above-mentioned method, the step of,to +.>Continuous variable after relaxation treatment, +.>Is a->Adjacent regional subnetwork sets.
The sub-network model construction module is used for constructing a distributed reactive power optimization model of each area sub-network according to the distributed reactive power optimization model based on a plurality of area sub-networks and given boundary variables, wherein the distributed reactive power optimization model comprises the following sub-networks:
。
the iterative computation module is used for solving the loose distributed reactive power optimization model by adopting an alternate direction multiplier method to obtain an optimal solution of the boundary coupling variable, then solving the distributed reactive power optimization model of each area subnetwork based on the optimal solution of the boundary coupling variable to obtain an integer solution of each reactive power equipment, judging whether convergence conditions are met, outputting a distributed reactive power voltage optimal control strategy if the convergence conditions are met, otherwise, reconstructing the loose distributed reactive power optimization model based on the integer solution of each reactive power equipment, and performing the next iteration, wherein the specific implementation mode is as shown in the step 6 of the embodiment 1.

Claims (10)

1. A distributed reactive voltage control method for a power distribution network by adopting relaxation iteration is characterized by comprising the following steps of:
the method comprises the following steps:
s1, constructing a centralized reactive voltage optimization model considering discrete and continuous reactive equipment, wherein the discrete reactive equipment comprises an on-load voltage regulating transformer and a switchable capacitor;
s2, splitting the power distribution network into a plurality of regional subnetworks, and converting the centralized reactive voltage optimization model into a distributed reactive power optimization model based on the plurality of regional subnetworks;
s3, loosening discrete variables in the distributed reactive power optimization model based on the multiple regional subnetworks into continuous variables to construct a loose distributed reactive power optimization model; constructing a distributed reactive power optimization model of each regional subnetwork according to the distributed reactive power optimization model based on the multiple regional subnetworks and a given boundary variable;
s4, solving a loose distributed reactive power optimization model by adopting an alternate direction multiplier method to obtain an optimal solution of the boundary coupling variable;
s5, solving a distributed reactive power optimization model of each regional subnetwork based on an optimal solution of the boundary coupling variable to obtain an integer solution of each reactive power device;
and S6, judging whether convergence conditions are met, if so, outputting a distributed reactive voltage optimal control strategy, otherwise, reconstructing a loose distributed reactive optimization model based on integer solutions of all reactive equipment, and returning to S4 for the next iteration.
2. A distributed reactive voltage control method for a power distribution network employing relaxation iteration as claimed in claim 1, wherein:
in the step S2, converting the centralized reactive voltage optimization model into a distributed reactive power optimization model based on a plurality of regional subnetworks includes:
s21, adopting an alternate direction multiplication method to carry out consistency relaxation treatment on boundary coupling variables between adjacent regional subnetworks by adopting a Lagrangian function;
s22, constructing a distributed reactive power optimization model based on a plurality of regional subnetworks based on the boundary coupling variables after relaxation:
；
in the above-mentioned method, the step of,for regional subnetwork->Is>、/>Regional subnetworks->Inequality, equality constraint of->For regional subnetwork->Local variable of->、/>Regional subnetworks->Local discrete variable, local continuous variable,/-for (a)>For regional subnetwork->And its neighboring regional subnetwork->Boundary coupling variable between->For regional subnetwork->And its neighboring regional subnetwork->Global variable between->Is the number of regional subnetworks.
3. A distributed reactive voltage control method for a power distribution network employing relaxation iteration as claimed in claim 2, wherein:
in the step S3, the loose distributed reactive power optimization model is as follows:
；
in the above-mentioned method, the step of,to +.>Continuous variable after relaxation treatment, +.>Is a->A set of adjacent regional subnetworks;
the distributed reactive power optimization model of each regional subnetwork is as follows:
；
in the above-mentioned method, the step of,is a positive integer.
4. A distributed reactive voltage control method for a power distribution network employing relaxation iteration according to claim 1 or 2, wherein:
in S6, the convergence condition includes:
；
in the above-mentioned method, the step of,is the sum of the objective functions of all area subnetworks in the z-th iteration, is +.>Is a set convergence criterion.
5. A distributed reactive voltage control method for a power distribution network employing relaxation iteration according to claim 1 or 2, wherein:
the S1 comprises the following steps:
s11, constructing a centralized reactive voltage optimization initial model considering discrete and continuous reactive equipment by taking network loss and minimum voltage deviation as targets, wherein the objective function of the centralized reactive voltage optimization initial model considering the discrete and continuous reactive equipment is as follows:
；
in the above-mentioned method, the step of,for the purpose of +.>、/>Respectively the active loss and the node electricity of the power distribution networkWeight coefficient of pressure deviation, +.>For distribution network branches->Resistance value of>For t period distribution network branch->Is>In order to optimize the duration of the time period,for the voltage amplitude of node i of period t, +.>For the reference voltage value>、/>The distribution network branch sets and the distribution network node sets are respectively +.>To optimize the number of time periods;
the constraint conditions comprise power flow constraint of the power distribution network, operation constraint of the on-load voltage regulating transformer, operation constraint of the switchable capacitor and operation constraint of the distributed power supply;
s12, performing convex relaxation conversion on variables in the centralized reactive voltage optimization initial model considering the discrete and continuous reactive equipment, so as to construct and obtain the centralized reactive voltage optimization model considering the discrete and continuous reactive equipment.
6. A distributed reactive voltage control method for a power distribution network employing relaxation iteration as claimed in claim 5, wherein:
the power distribution network power flow constraint comprises:
；
；
；
；
；
in the above-mentioned method, the step of,、/>distribution network branches with t time periods respectively>、/>Active power, < >>、/>Active power and reactive power of a node i are respectively injected into a distributed power supply in a t period, and the power is +.>、/>Active, reactive load of node i at time t respectively,>、/>distribution network branches with t time periods respectively>、/>Reactive power of>Reactive power of node i is injected into the switchable capacitor bank at time t +.>、/>The upper limit and the lower limit of the voltage amplitude are allowed respectively;
the on-load tap changer operating constraints include:
；
；
；
in the above-mentioned method, the step of,for distribution network branches->Initial transformation ratio of upper transformer, +.>For t period distribution network branch->The number of gears of the upper transformer, +.>For distribution network branches->Increment of each gear ratio of upper transformer, +.>For optimizing the gear value of the transformer's allowed action during the period,/->For the maximum gear value of the transformer, < >>Is a positive integer;
the switchable capacitor operating constraints include:
；
；
；
in the above-mentioned method, the step of,the number of capacitors put into node i for the period t, < >>Reactive power output for node i single capacitor, +.>To optimize the number of allowable actions of the switchable capacitor bank during the time period +.>The maximum number of the capacitors in the capacitor bank can be switched for the node i;
the distributed power operation constraint includes:
；
；
；
in the above-mentioned method, the step of,predicted value of active power output of distributed power supply at node i at time t>For the distributed power factor angle at node i, +.>Active capacity of the distributed power supply at node i;
in S12, the convex relaxation conversion includes:
linearizing and relaxing power flow constraint of the power distribution network; linearizing the absolute value phase in the centralized reactive voltage optimization initial model; and performing second-order cone relaxation treatment on the operation constraint of the distributed power supply.
7. A distributed reactive voltage control system of a power distribution network adopting relaxation iteration is characterized in that:
the system comprises a centralized reactive voltage optimization model construction module, a distributed reactive power optimization model construction module, a relaxation processing module, a sub-network model construction module and an iterative calculation module;
the centralized reactive voltage optimization model construction module is used for constructing a centralized reactive voltage optimization model considering discrete and continuous reactive equipment, wherein the discrete reactive equipment comprises an on-load voltage regulating transformer and a switchable capacitor;
the distributed reactive power optimization model construction module is used for splitting the power distribution network into a plurality of regional subnetworks and converting the centralized reactive power voltage optimization model into a distributed reactive power optimization model based on the regional subnetworks;
the relaxation processing module is used for relaxing discrete variables in the distributed reactive power optimization model based on the plurality of regional subnetworks into continuous variables so as to construct a relaxed distributed reactive power optimization model;
the sub-network model building module is used for building a distributed reactive power optimization model of each regional sub-network according to the distributed reactive power optimization model based on a plurality of regional sub-networks and given boundary variables;
the iterative computation module is used for solving the loose distributed reactive power optimization model by adopting an alternate direction multiplier method to obtain an optimal solution of the boundary coupling variable, then solving the distributed reactive power optimization model of each regional subnetwork based on the optimal solution of the boundary coupling variable to obtain an integer solution of each reactive power equipment, judging whether convergence conditions are met, outputting a distributed reactive power voltage optimal control strategy if the convergence conditions are met, otherwise, reconstructing the loose distributed reactive power optimization model based on the integer solution of each reactive power equipment, and performing the next iteration.
8. A distributed reactive voltage control system for a power distribution network employing relaxation iteration as recited in claim 7, wherein:
the distributed reactive power optimization model building module comprises an area decomposition unit, a consistency relaxation processing unit and a distributed reactive power optimization model building unit;
the regional decomposition unit is used for dividing the power distribution network into a plurality of regional subnetworks;
the consistency relaxation processing unit is used for carrying out consistency relaxation processing on boundary coupling variables between adjacent regional subnetworks by adopting a Lagrange method by using an alternate direction multiplier method;
the distributed reactive power optimization model construction unit is used for constructing a distributed reactive power optimization model based on a plurality of regional subnetworks based on the boundary coupling variable after relaxation treatment as follows:
；
in the above-mentioned method, the step of,for regional subnetwork->Is>、/>Regional subnetworks->Inequality, equality constraint of->For regional subnetwork->Local variable of->、/>Regional subnetworks->Local discrete variable, local continuous variable,/-for (a)>For regional subnetwork->And its neighboring regional subnetwork->Boundary coupling variable between->For regional subnetwork->And its neighboring regional subnetwork->Global variable between.
9. A distributed reactive voltage control system for a power distribution network employing relaxation iteration as recited in claim 8, wherein:
the relaxation processing module is used for constructing a relaxation distributed reactive power optimization model:
；
in the above-mentioned method, the step of,to +.>Continuous variable after relaxation treatment, +.>Is a->A set of adjacent regional subnetworks;
the sub-network model building module is used for building a distributed reactive power optimization model of each region sub-network as follows:
；
in the above-mentioned method, the step of,is a positive integer.
10. A distributed reactive voltage control system for a power distribution network employing relaxation iteration as recited in claim 7, wherein:
the centralized reactive voltage optimization model building module comprises an initial module building unit and a convex relaxation conversion unit;
the initial module construction unit is used for constructing a centralized reactive voltage optimization initial model taking the minimum network loss and voltage deviation into consideration, wherein the centralized reactive voltage optimization initial model is as follows:
；
in the above-mentioned method, the step of,for the purpose of +.>、/>Weight coefficients of active loss and node voltage deviation of power distribution network respectively, < >>For distribution network branches->Resistance value of>For t period distribution network branch->Is>In order to optimize the duration of the time period,for the voltage amplitude of node i of period t, +.>For the reference voltage value>、/>The distribution network branch sets and the distribution network node sets are respectively +.>To optimize the number of time periods;
the constraint conditions comprise power flow constraint of the power distribution network, operation constraint of the on-load voltage regulating transformer, operation constraint of the switchable capacitor and operation constraint of the distributed power supply;
the convex relaxation conversion unit is used for carrying out convex relaxation conversion on variables in the initial model of the centralized reactive voltage optimization considering the discrete and continuous reactive equipment, so that the centralized reactive voltage optimization model considering the discrete and continuous reactive equipment is constructed.
CN202311677656.2A 2023-12-08 2023-12-08 Distributed reactive voltage control method and system for power distribution network by adopting relaxation iteration Active CN117394380B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202311677656.2A CN117394380B (en) 2023-12-08 2023-12-08 Distributed reactive voltage control method and system for power distribution network by adopting relaxation iteration

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202311677656.2A CN117394380B (en) 2023-12-08 2023-12-08 Distributed reactive voltage control method and system for power distribution network by adopting relaxation iteration

Publications (2)

Publication Number Publication Date
CN117394380A true CN117394380A (en) 2024-01-12
CN117394380B CN117394380B (en) 2024-03-01

Family

ID=89437705

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202311677656.2A Active CN117394380B (en) 2023-12-08 2023-12-08 Distributed reactive voltage control method and system for power distribution network by adopting relaxation iteration

Country Status (1)

Country Link
CN (1) CN117394380B (en)

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107591815A (en) * 2017-09-07 2018-01-16 华南理工大学 It is a kind of to solve the decomposition method containing discrete control reactive power optimization of power system
CN110739725A (en) * 2019-09-27 2020-01-31 上海电力大学 optimal scheduling method for power distribution network
CN115967078A (en) * 2022-09-23 2023-04-14 国网吉林省电力有限公司四平供电公司 Rural power distribution network voltage distributed optimization control method containing distributed photovoltaic
CN115986749A (en) * 2022-12-30 2023-04-18 国网电力科学研究院武汉能效测评有限公司 Power distribution system voltage/reactive power optimization method and device based on alternating direction multiplier method
CN116629461A (en) * 2023-07-25 2023-08-22 山东大学 Distributed optimization method, system, equipment and storage medium for active power distribution network

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107591815A (en) * 2017-09-07 2018-01-16 华南理工大学 It is a kind of to solve the decomposition method containing discrete control reactive power optimization of power system
CN110739725A (en) * 2019-09-27 2020-01-31 上海电力大学 optimal scheduling method for power distribution network
CN115967078A (en) * 2022-09-23 2023-04-14 国网吉林省电力有限公司四平供电公司 Rural power distribution network voltage distributed optimization control method containing distributed photovoltaic
CN115986749A (en) * 2022-12-30 2023-04-18 国网电力科学研究院武汉能效测评有限公司 Power distribution system voltage/reactive power optimization method and device based on alternating direction multiplier method
CN116629461A (en) * 2023-07-25 2023-08-22 山东大学 Distributed optimization method, system, equipment and storage medium for active power distribution network

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
WENTIAN LU等: "Incremental-oriented ADMM for distributed optimal power flow with discrete variables in distribution networks", 《IEEE TRANSACTIONS ON SMART GRID》, vol. 10, no. 6, 28 February 2019 (2019-02-28) *
王斌等: "高比例光伏接入的配电网分布式运行优化技术", 《南方电网技术》, 12 October 2023 (2023-10-12) *
陆文甜: "含连续/离散控制的多区域电力系统分布式优化调度方法研究", 《中国博士学位论文全文数据库 工程科技Ⅱ辑》, 15 December 2018 (2018-12-15) *

Also Published As

Publication number Publication date
CN117394380B (en) 2024-03-01

Similar Documents

Publication Publication Date Title
Chen et al. Aggregate power flexibility in unbalanced distribution systems
CN105023058B (en) Power distribution network intelligence Sofe Switch running optimizatin method that is a kind of while considering switch motion
CN110460036B (en) Distributed optimization method for alternating current-direct current power distribution network considering wind power uncertainty
CN107171341B (en) Integrated reactive power optimization method for power transmission and distribution network based on distributed computation
CN110266038B (en) Distributed coordination regulation and control method for multiple virtual power plants
CN104794541B (en) A kind of power distribution network running optimizatin method based on simulated annealing and cone optimization
Nazaripouya et al. Battery energy storage system control for intermittency smoothing using an optimized two-stage filter
Cai et al. A multi-level control architecture for master-slave organized microgrids with power electronic interfaces
CN108023364A (en) Power distribution network distributed generation resource maximum access capability computational methods based on convex difference planning
CN111725808B (en) Singular perturbation-based distributed convergence control method and system for comprehensive energy system
CN107706939A (en) The distributed control method of time lag and packet loss problem is considered in microgrid under CPS concepts
CN106159955B (en) Electric system distributed optimal power flow method based on continuous punishment Duality Decomposition
Jian et al. Distributed economic dispatch method for power system based on consensus
CN109390930A (en) A kind of active distribution network micro-capacitance sensor partition method considering control autonomy and communications cost
CN110880758B (en) Decomposition coordination optimal power flow control method for power transmission network and power distribution network in electric power system
CN112467748A (en) Double-time-scale distributed voltage control method and system for three-phase unbalanced active power distribution network
Babazadeh et al. Study of centralized and distributed coordination of power injection in multi-TSO HVDC grid with large off-shore wind integration
Ferro et al. A distributed approach to the optimal power flow problem for unbalanced and mesh networks
CN112671047B (en) Active power distribution network reconstruction and reactive power joint robust optimization method considering limit scene
CN117394380B (en) Distributed reactive voltage control method and system for power distribution network by adopting relaxation iteration
CN109494750B (en) Hierarchical distributed voltage optimization control method for high and medium voltage distribution network
CN111834996B (en) Power grid line loss calculation method and device
Wang et al. Distributed finite-time economic dispatch for islanded microgrids
CN112734590B (en) Two-stage regional power grid reactive power optimization method based on interior point method and dynamic programming method of variable domain search
CN114818379A (en) Information physics active power distribution system interactive planning method considering multidimensional uncertainty

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant