CN112054519B - Power distribution network low voltage optimization treatment method, system and equipment - Google Patents

Power distribution network low voltage optimization treatment method, system and equipment Download PDF

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CN112054519B
CN112054519B CN202010929615.8A CN202010929615A CN112054519B CN 112054519 B CN112054519 B CN 112054519B CN 202010929615 A CN202010929615 A CN 202010929615A CN 112054519 B CN112054519 B CN 112054519B
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voltage
low
distribution network
power distribution
treatment
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CN112054519A (en
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陈国炎
王红斌
范旭娟
彭和平
梁国耀
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Guangzhou Power Supply Bureau of Guangdong Power Grid Co Ltd
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Guangzhou Power Supply Bureau of Guangdong Power Grid Co Ltd
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    • 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
    • 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
    • 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
    • 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]
    • 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

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Abstract

The invention discloses a method, a system and equipment for optimizing and managing low voltage of a power distribution network. The power distribution network system is divided into four areas, corresponding low-voltage treatment measures are set for each area, and a plurality of low-voltage treatment means such as wire replacement, voltage regulator addition, reactive compensation and the like are fully considered; the method comprises the steps of performing load flow calculation on a power grid by adopting a Newton-Raphson algorithm according to power grid parameters, judging whether low voltage occurs in a power distribution network system or not according to a load flow calculation result, and having good adaptability because the Newton-Raphson method is not influenced by system topology when performing load flow calculation; and finally, performing optimization solution based on a multi-objective particle swarm optimization algorithm to obtain low-voltage optimization treatment measures of a low-voltage area, and performing optimization treatment on the power distribution network system.

Description

Power distribution network low voltage optimization treatment method, system and equipment
Technical Field
The invention relates to the field of electric power, in particular to a method, a system and equipment for optimizing and managing low voltage of a power distribution network.
Background
With the continuous development and deep reform of the smart power grid, the safe and economic operation of the power distribution network becomes an important part of the current power grid operation. However, due to the fact that the construction of a power grid of a part of power distribution networks cannot meet the change of user requirements, low voltage problems occur occasionally, and the voltage of the power distribution networks is unstable; the stability of voltage is an important content of electric energy quality, and the voltage qualification rate directly influences the stable operation of a power distribution network and the performance of user electric equipment. Frequent occurrence of the low voltage problem seriously affects normal lives of residents, and hinders the development of regional economy.
With the improvement of life quality and the rapid development of industrial industry, people have greater dependence and demand on electric energy and higher requirement on electric energy quality, and at present, research on low-voltage optimization governance is more and more. The low-voltage optimization governing strategy is an important way for solving the low-voltage problem, and reduces power loss, voltage deviation, load power factor and the like on the premise of ensuring that the system voltage can be recovered to a normal operation state.
The low-voltage optimization governing strategy comprises a mathematical analysis method and an artificial intelligence algorithm; the mathematical analysis method has strict requirements on the power distribution network, is poor in applicability, and has the problems of being unsolvable, dimension disaster and the like on a large-scale power distribution network. When the artificial intelligence algorithm is used for low-voltage optimization management, a plurality of management means such as wire replacement, voltage regulator addition, reactive compensation equipment addition and the like are not usually considered, a plurality of optimization targets such as voltage stability and economy are not considered, only individual management measures are selected to optimize a single target on the premise of determining other factors, and discrete control variables such as transformer tap change, wire replacement and the like are not considered, so that the low-voltage management effect is poor.
In conclusion, the low-voltage optimization treatment strategy used in the prior art has the technical problems of poor applicability and poor treatment effect caused by single treatment measure.
Disclosure of Invention
The invention provides a method, a system and equipment for optimizing and treating low voltage of a power distribution network, which are used for solving the technical problems of poor applicability and poor treatment effect caused by single treatment measure in a low voltage optimizing and treating strategy used in the prior art.
The invention provides a power distribution network low voltage optimization treatment method, which comprises the following steps:
s1: dividing the power distribution network system into four areas, and making corresponding low-voltage treatment measures for each area; wherein, four regions include: the system comprises a main transformer area, a medium-voltage terminal area, a distribution transformation area and a user side area; the low voltage treatment measures in the main transformer area comprise: transformation of a power transmission network, transformation of a transformer and reactive compensation; the low voltage treatment measures of the medium voltage end region comprise: replacing a lead, adding a voltage regulator, performing reactive compensation and changing the gear of the voltage regulator; the low voltage treatment measures in the distribution transformation area comprise: reactive compensation and distribution transformation capacity increasing; the low voltage treatment measures of the user side area comprise: reactive compensation, voltage regulator addition, wire replacement and three-phase unbalance management;
s2: acquiring power grid parameters of a power distribution network system in real time, carrying out load flow calculation on the power grid by adopting a Newton-Raphson algorithm according to the power grid parameters, and judging whether low voltage occurs in the power distribution network system according to the load flow calculation result;
s3: if low voltage occurs in the power distribution network system, sequentially judging whether the four areas generate low voltage, determining the areas generating low voltage, and acquiring low voltage treatment measures corresponding to the areas generating low voltage;
s4: and optimizing the corresponding low-voltage treatment measures of the low-voltage areas based on a multi-objective particle swarm optimization algorithm to obtain the low-voltage optimized treatment measures of the low-voltage areas, and performing optimized treatment on the power distribution network system according to the low-voltage optimized treatment measures.
Preferably, the optimization targets of the multi-target particle swarm optimization algorithm comprise system network loss, voltage deviation and low voltage treatment cost; the constraint conditions comprise a power flow equation constraint, a generator reactive power output constraint, a voltage constraint and a voltage regulator transformation ratio constraint.
Preferably, the calculation formula of the system network loss is specifically as follows:
Figure GDA0003516360930000021
in the formula: p loss Is the system network loss, and L is the total number of branches of the power distribution network system; g k Is the conductance of branch k of the distribution network system; u shape i Is the voltage amplitude, U, of the branch k node i of the distribution network system j Is the voltage amplitude value theta of the nodes j at two ends of the branch k of the power distribution network system ij Is the phase angle difference between node i and node j of branch k of the power distribution network system.
Preferably, the calculation formula of the voltage deviation is as follows:
Figure GDA0003516360930000031
in the formula: u shape deviation Is the voltage deviation, n is the total number of nodes in the distribution grid system; u shape j expect Is the expected voltage of the distribution network system node j; u shape jmax And U jmin The voltage upper limit and the voltage lower limit are respectively the voltage upper limit and the voltage lower limit of the power distribution network system node j.
Preferably, the calculation formula of the low voltage treatment cost is as follows:
Figure GDA0003516360930000032
in the formula: f. of invest For low voltage treatment costs, m is the total number of equipment required for low voltage treatment measures, E investj Is the fixed cost of equipment required by low voltage treatment measures; n is the number of reactive power compensation devices, Q cz Is the reactive compensation capacity of the reactive compensation equipment z; c c Is the unit reactive power compensation cost.
Preferably, the specific process of step S4 is:
s41: initializing parameters of the multi-target particle swarm optimization algorithm, and randomly initializing the positions and the speeds of particles in a swarm of the multi-target particle swarm optimization algorithm, wherein the positions of the particles are control variables of reactive power compensation;
s42: setting control variables which do not meet constraint conditions of the multi-target particle swarm optimization algorithm in the particles as the upper limit or the lower limit of the constraint conditions;
s43: calculating the system network loss, the voltage deviation and the low-voltage governing cost of the power distribution network system under the condition of meeting the constraint condition, determining the weight coefficients of the system network loss, the voltage deviation and the low-voltage governing cost, and performing weighted summation on the system network loss, the voltage deviation and the low-voltage governing cost according to the weight coefficients to obtain a fitness function:
s44: calculating the fitness of the population and the fitness of the particles in the population according to a fitness function, taking the population with the minimum fitness as a global optimal solution, and taking the particles with the minimum fitness as a particle optimal solution;
s45: updating the position and the speed of the particles according to the global optimal solution and the particle optimal solution, and judging whether the preset iteration times are reached; if not, increasing the iteration times by 1 time, and re-executing the step S42 to the step S45; and if the preset iteration times are reached, outputting the updated position and speed of the particles to obtain low-voltage optimization treatment measures, and performing optimization treatment on the area of the power distribution network system with low voltage according to the low-voltage optimization treatment measures.
Preferably, in step S41, initializing parameters of the multi-objective particle swarm optimization algorithm specifically includes:
initializing the population scale, the acceleration coefficient, the maximum iteration times, the maximum weight coefficient and the minimum weight coefficient of the target particle swarm algorithm.
Preferably, in step S41, the control variable for reactive compensation comprises a switchable shunt capacitor/reactor Q c Tap K of a tap changer T Length L of replacement wire l 。
A distribution network low voltage optimization treatment system, includes: the low-voltage treatment control system comprises a low-voltage treatment measure formulation module, a low-voltage detection module, a low-voltage region judgment module and a low-voltage optimization treatment module;
the low-voltage treatment measure making module is used for dividing the power distribution network system into four areas and making corresponding low-voltage treatment measures for each area; wherein, four regions include: the system comprises a main transformer area, a medium-voltage terminal area, a distribution transformation area and a user side area; the low voltage treatment measures in the main transformer area comprise: transformation of a power transmission network, transformation of a transformer and reactive compensation; the low voltage treatment measures in the medium voltage terminal area comprise: replacing a lead, adding a voltage regulator, performing reactive compensation and changing the gear of the voltage regulator; the low voltage treatment measures in the distribution transformation area comprise: reactive compensation and distribution transformation capacity increasing; the low voltage treatment measures of the user side area comprise: reactive compensation, voltage regulator addition, wire replacement and three-phase unbalance management;
the low-voltage detection module is used for acquiring power grid parameters of the power distribution network system in real time, carrying out load flow calculation on the power grid by adopting a Newton-Raphson algorithm according to the power grid parameters, and judging whether low voltage occurs in the power distribution network system according to the load flow calculation result;
the low-voltage area judgment module is used for sequentially judging whether the four areas generate low voltage when the low voltage occurs in the power distribution network system, determining the areas generating the low voltage and acquiring low-voltage treatment measures corresponding to the areas generating the low voltage;
the low-voltage optimization treatment module is used for optimizing low-voltage treatment measures corresponding to the low-voltage area based on a multi-objective particle swarm optimization algorithm to obtain the low-voltage optimization treatment measures of the low-voltage area, and performing optimization treatment on the power distribution network system according to the low-voltage optimization treatment measures.
A low-voltage optimization treatment device for a power distribution network comprises a processor and a memory;
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is used for executing the power distribution network low voltage optimization treatment method according to the instructions in the program codes.
According to the technical scheme, the embodiment of the invention has the following advantages:
according to the embodiment of the invention, the power distribution network system is divided into four areas, and corresponding low-voltage treatment measures are set for each area, so that a plurality of low-voltage treatment means such as wire replacement, voltage regulator addition, reactive compensation and the like are fully considered; then, carrying out load flow calculation on the power grid based on a Newton-Raphson algorithm, and judging whether low voltage occurs in the power distribution network system according to the result of the load flow calculation, wherein the Newton-Raphson method is not influenced by system topology in the process of carrying out load flow calculation, is suitable for calculation of a large-scale power grid and has good adaptability; and finally, performing optimization solution based on a multi-target particle swarm optimization algorithm to obtain low-voltage optimization treatment measures of a low-voltage area, and performing optimization treatment on the power distribution network system.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a method flowchart of a method, a system, and an apparatus for power distribution network low-voltage optimization management according to an embodiment of the present invention.
Fig. 2 is a method flowchart of a power distribution network low-voltage optimization management method, system and device provided by the embodiment of the invention.
Fig. 3 is a system framework diagram of a power distribution network low-voltage optimization treatment method, system and device provided by the embodiment of the invention.
Fig. 4 is an equipment framework diagram of a power distribution network low-voltage optimization management method, system and equipment provided by the embodiment of the invention.
Fig. 5 is a schematic structural diagram of a power distribution network system according to an embodiment of the present invention.
Fig. 6 is a schematic voltage curve diagram of the power distribution grid system before and after the low voltage is optimized and treated according to the embodiment of the invention.
Detailed Description
The embodiment of the invention provides a method, a system and equipment for optimizing and treating low voltage of a power distribution network, which are used for solving the technical problems of poor applicability and poor treatment effect caused by single treatment measure in a low voltage optimization and treatment strategy used in the prior art.
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a flowchart of a method, a system and a device for optimizing and managing low voltage of a power distribution network according to an embodiment of the present invention.
Example 1
As shown in fig. 1, the method for optimizing and treating low voltage of a power distribution network provided by the embodiment of the invention includes the following steps:
s1: because when the distribution network system takes place the low voltage, the low voltage treatment measures of each region of distribution network system are different, therefore, in this embodiment, divide the distribution network system into four regions, it is respectively: the system comprises a main transformer area, a medium-voltage terminal area, a distribution transformation area and a user side area; and corresponding low-voltage treatment measures are set for each area; wherein, low-voltage treatment measures to the main transformer area include: transformation of a power transmission network, transformation of a transformer and reactive compensation; the low voltage management measures for the medium voltage terminal region include: replacing a lead, adding a voltage regulator, performing reactive compensation and changing the gear of the voltage regulator; low voltage remediation measures for distribution transformer areas include: reactive compensation and distribution and transformation capacity increasing; the low voltage treatment measures aiming at the user side area comprise the following steps: reactive compensation, voltage regulator addition, wire replacement and three-phase unbalance management; by making corresponding low-voltage treatment measures for each region, a plurality of low-voltage treatment measures such as wire replacement, voltage regulator addition, reactive compensation and the like are fully considered, and the defect of poor treatment effect caused by treatment of low voltage by using a single measure is avoided;
s2: acquiring power grid parameters of a power distribution network system from a background of the power distribution network system in real time, carrying out load flow calculation on the power grid by adopting a Newton-Raphson algorithm according to the power grid parameters, obtaining the distribution of the calculated active power, reactive power and voltage in the power distribution network system through the load flow calculation, and judging whether low voltage occurs in the power distribution network system according to the load flow calculation result;
it should be further noted that the newton-raphson algorithm substantially converts the solving process of the nonlinear equation into a process of repeatedly solving the corresponding linear equation, i.e., a successive linearization process; in the process of carrying out load flow calculation by adopting a Newton-Raphson algorithm, the Newton-Raphson method is not influenced by the topological structure of the power distribution network system when generating the node admittance matrix, so that the Newton-Raphson method has stronger capacity of processing a ring network and better adaptability; secondly, the Newton Raphson algorithm is adopted to carry out the tidal current calculation, and special processing is not needed on the voltage control node, so that the convergence is better when the distributed power supply is processed.
S3: if low voltage occurs in the power distribution network system, sequentially judging whether the main transformer area, the medium-voltage terminal area, the power distribution transformation area and the user side area have low voltage according to the sequence, and determining the area where the low voltage occurs;
s4: after the area where the low voltage occurs is determined, optimizing low voltage treatment measures corresponding to the area where the low voltage occurs based on a multi-objective particle swarm optimization algorithm to obtain low voltage optimization treatment measures of the area where the low voltage occurs, and performing optimization treatment on the power distribution network system according to the low voltage optimization treatment measures; the multi-objective particle swarm optimization algorithm has no cross operation and Mutation operation of a genetic algorithm, a global optimal solution is searched by following the optimal value searched currently, and parameters needing to be adjusted in the process of searching the global solution are few, simple and easy to operate and high in universality; in the embodiment, the specific measures for optimizing and governing the low voltage of each region are obtained through optimization of a multi-objective particle swarm optimization algorithm, and the low voltage in the power distribution network system is eliminated according to the specific measures.
Example 2
As shown in fig. 2, the method for optimizing and treating the low voltage of the power distribution network provided by the embodiment of the invention comprises the following steps:
s1: because when the distribution network system takes place the low voltage, the low voltage treatment measures of each region of distribution network system are different, therefore, in this embodiment, divide the distribution network system into four regions, it is respectively: the system comprises a main transformer area, a medium-voltage terminal area, a distribution transformation area and a user side area; and corresponding low-voltage treatment measures are set for each area; wherein, the low voltage treatment measure to main transformer region includes: transformation of a power transmission network, transformation of a transformer and reactive compensation; the low voltage treatment measures for the medium voltage end region include: replacing a lead, adding a voltage regulator, performing reactive compensation and changing the gear of the voltage regulator; low voltage abatement measures for distribution transformer areas include: reactive compensation and distribution and transformation capacity increasing; the low voltage treatment measures aiming at the user side area comprise the following steps: reactive compensation, voltage regulator addition, wire replacement and three-phase unbalance management; by making corresponding low-voltage treatment measures for each region, a plurality of low-voltage treatment measures such as wire replacement, voltage regulator addition, reactive compensation and the like are fully considered, and the defect of poor treatment effect caused by treatment of low voltage by using a single measure is avoided;
s2: acquiring power grid parameters of a power distribution network system from a background of the power distribution network system in real time, carrying out load flow calculation on the power grid by adopting a Newton-Raphson algorithm according to the power grid parameters, obtaining the distribution of the calculated active power, reactive power and voltage in the power distribution network system through the load flow calculation, and judging whether low voltage occurs in the power distribution network system according to the load flow calculation result;
it should be further explained that the newton-raphson algorithm essentially converts the solving process of the nonlinear equation into a process of repeatedly solving the corresponding linear equation, i.e., a successive linearization process; in the process of carrying out load flow calculation by adopting a Newton-Raphson algorithm, the Newton-Raphson method is not influenced by the topological structure of the power distribution network system when generating the node admittance matrix, so that the Newton-Raphson method has stronger capacity of processing a ring network and better adaptability; secondly, the Newton Raphson algorithm is adopted to carry out the tidal current calculation, and special processing is not needed on the voltage control node, so that the convergence is better when the distributed power supply is processed.
S3: if low voltage occurs in the power distribution network system, sequentially judging whether the main transformer area, the medium-voltage terminal area, the power distribution transformation area and the user side area have low voltage according to the sequence, and determining the area where the low voltage occurs;
s4: after the area with the low voltage is determined, optimizing the corresponding low-voltage treatment measures of the area with the low voltage based on a multi-objective particle swarm optimization algorithm to obtain the low-voltage optimized treatment measures of the area with the low voltage, and performing optimized treatment on the power distribution network system according to the low-voltage optimized treatment measures; the multi-objective particle swarm optimization algorithm has no cross operation and Mutation operation of a genetic algorithm, a global optimal solution is searched by following the optimal value searched currently, and parameters needing to be adjusted in the process of searching the global solution are few, simple and easy to operate and high in universality; in the embodiment, the specific measures for low voltage optimization treatment of each region are obtained through optimization of the multi-objective particle swarm optimization algorithm, and the low voltage in the power distribution network system is eliminated according to the specific measures.
It needs to be further explained that the optimization targets of the multi-target particle swarm optimization algorithm comprise system network loss, voltage deviation and low voltage governing cost; the constraint conditions comprise a power flow equation constraint, a generator reactive power output constraint, a voltage constraint and a voltage regulator transformation ratio constraint;
the system network loss calculation formula is specifically as follows:
Figure GDA0003516360930000081
in the formula: p loss Is the system network loss, and L is the total number of branches of the power distribution network system; g is a radical of formula k Is the conductance of branch k of the distribution network system; u shape i Is the voltage amplitude value, U, of the k node i of the branch of the power distribution network system j Is the voltage amplitude value theta of the nodes j at two ends of the branch k of the power distribution network system ij Is the phase angle difference between node i and node j of branch k of the power distribution network system.
The calculation formula of the voltage deviation is specifically as follows:
Figure GDA0003516360930000091
in the formula: u shape deviation Is a deviation of voltageN is the total number of nodes of the power distribution network system;
Figure GDA0003516360930000092
is the expected voltage of the distribution network system node j; u shape jmax And U jmin The upper voltage limit and the lower voltage limit of the node j of the power distribution network system are respectively.
The calculation formula of the low-voltage treatment cost is as follows:
Figure GDA0003516360930000093
in the formula: f. of invest For low voltage treatment costs, m is the total number of equipment required for low voltage treatment measures, E investj Is the fixed cost of equipment required by low voltage treatment measures; n is the number of reactive power compensation devices, Q cz Is the reactive compensation capacity of the reactive compensation equipment z; c c Is the unit reactive power compensation cost.
The calculation formula of the power flow constraint is concretely as follows
Figure GDA0003516360930000094
In the formula: p Gi And Q Gi Is the active power and the reactive power P generated by a node i generator of a power distribution network system Li And Q Li The active power and the reactive power consumed by the load of a node i of the power distribution network system; q Ci Is the reactive power compensation capacity of node i; g ij And B ij Is the conductance and susceptance between node i and node j.
The calculation formula of the variable constraint is concretely as follows
Figure GDA0003516360930000101
In the formula: u is the bus voltage; q G The generator generates reactive power; q C Is the reactive compensation capacity of the capacitor; t is transformerAnd (4) a ratio.
It should be further explained that, the specific process of step S4 is:
s41: initializing parameters of the multi-objective particle swarm optimization algorithm, wherein the parameters comprise: population size, acceleration coefficient, maximum iteration number, maximum weight coefficient and minimum weight coefficient. Randomly initializing the positions and the speeds of particles in a population of a multi-target particle swarm optimization algorithm according to the equipment types and constraint conditions contained in low-voltage treatment measures, wherein the positions of the particles are control variables of reactive compensation and comprise switchable parallel capacitors/reactors Q c Tap K of a tap changer T Length L of the replacement wire l ；
Figure GDA0003516360930000102
In the formula, X i Is a control variable of reactive compensation.
It should be further noted that, in this embodiment, the value range of the population size is 10 to 40; the value range of the acceleration factor is 1.5-2; the maximum number of iterations is 200; the value range of the maximum weight coefficient is 1.1-1.2; the minimum weight coefficient has a value range of 0.5-0.6.
S42: setting control variables which do not meet constraint conditions of the multi-target particle swarm optimization algorithm in the particles as the upper limit or the lower limit of the constraint conditions; for the discrete random variables, a mapping coding technology is adopted for processing, for example, the transformation ratio of the voltage regulating transformer and the replacement of a lead are the discrete random variables; taking the transformation ratio of the voltage regulating transformer as an example, the transformation ratio of the transformer is only 17 steps, the variable is coded, and the coding range is (-8,8), so that the variable is converted into a continuous variable to be solved.
S43: and calculating the system network loss, the voltage deviation and the low-voltage governing cost of the power distribution network system under the condition of meeting the constraint condition, determining the weight coefficients of the system network loss, the voltage deviation and the low-voltage governing cost according to governing key points, and performing weighted summation on the system network loss, the voltage deviation and the low-voltage governing cost according to the weight coefficients to obtain a fitness function.
S44: calculating the fitness of the population and the fitness of the particles in the population according to a fitness function, taking the population with the minimum fitness as a global optimal solution, and taking the particles with the minimum fitness as a particle optimal solution; it should be further explained that, in the first iteration, the current value is taken as the individual optimal solution.
S45: updating the position and the speed of the particle according to the global optimal solution and the particle optimal solution, which is specifically as follows: a set of particles (assumed to be D-dimensional) in a solution space is randomly initialized in a multi-objective particle swarm optimization algorithm, wherein the position and the velocity of the y-th particle (y =1,2,..., D,..., S) are respectively represented as x = (x) y1 ,...,x yd ,...,x yD ) And v y ＝(v y1 ,...,v yd ,...,v yD ) (ii) a The individual optimal solution of the particle y in the searching process is marked as P best，y Record the population-optimal solution as G best In the (k + 1) th iteration, particle y updates the velocity and position according to equations (6) and (7):
Figure GDA0003516360930000111
Figure GDA0003516360930000112
Figure GDA0003516360930000113
in the formula: k is the number of iterations; c. C 1 And c 2 Is a learning factor; w is a weight coefficient; r is 1 And r 2 Is [0,1 ]]Uniformly distributed random numbers.
Judging whether the maximum iteration times is reached; if not, increasing the iteration times by 1 time, and re-executing the step S32-the step S35; and if the maximum iteration times are reached, outputting the position and the speed of the particles, obtaining low-voltage optimization treatment measures, such as specific transformation ratio of the voltage regulating transformer, length and position of a replacement lead and the like, and performing optimization treatment on the area with low voltage in the power distribution network system according to the low-voltage optimization treatment measures.
As shown in fig. 3, a system for optimizing and treating low voltage of a distribution network comprises: a low voltage treatment measure formulation module 201, a low voltage detection module 202, a low voltage region judgment module 203 and a low voltage optimization treatment module 204;
the low-voltage treatment measure establishing module 201 is used for dividing the power distribution network system into four areas and establishing corresponding low-voltage treatment measures for each area; wherein, four regions include: the system comprises a main transformer area, a medium-voltage terminal area, a distribution transformation area and a user side area; the low voltage treatment measures in the main transformer area comprise: transformation of a power transmission network, transformation of a transformer and reactive compensation; the low voltage treatment measures of the medium voltage end region comprise: replacing a lead, adding a voltage regulator, performing reactive compensation and changing the gear of the voltage regulator; the low voltage treatment measures in the distribution transformation area comprise: reactive compensation and distribution and transformation capacity increasing; the low voltage treatment measures of the user side area comprise: reactive compensation, voltage regulator addition, wire replacement and three-phase unbalance management;
the low-voltage detection module 202 is used for acquiring power grid parameters of the power distribution network system in real time, performing load flow calculation on the power grid parameters by adopting a Newton-Raphson algorithm according to the power grid parameters, and judging whether low voltage occurs in the power distribution network system according to a load flow calculation result;
the low voltage area judgment module 203 is used for sequentially judging whether the four areas generate low voltage when the low voltage occurs in the power distribution network system, determining the areas generating the low voltage, and acquiring low voltage treatment measures corresponding to the areas generating the low voltage;
the low-voltage optimization treatment module 204 is configured to optimize the low-voltage treatment measures corresponding to the low-voltage-generating region based on a multi-objective particle swarm optimization algorithm to obtain the low-voltage optimization treatment measures of the low-voltage-generating region, and perform optimization treatment on the power distribution network system according to the low-voltage optimization treatment measures.
As shown in fig. 4, a power distribution network low voltage optimization abatement device 30 comprises a processor 300 and a memory 301;
the memory 301 is used for storing a program code 302 and transmitting the program code 302 to the processor;
the processor 300 is configured to execute the steps of the power distribution network low voltage optimization management method according to the instructions in the program code 302.
Illustratively, the computer program 302 may be partitioned into one or more modules/units, which are stored in the memory 301 and executed by the processor 300 to accomplish the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program 302 in the terminal device 30.
The terminal device 30 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The terminal device may include, but is not limited to, a processor 300, a memory 301. Those skilled in the art will appreciate that fig. 4 is merely an example of a terminal device 30 and does not constitute a limitation of terminal device 30 and may include more or fewer components than shown, or some components may be combined, or different components, e.g., the terminal device may also include input-output devices, network access devices, buses, etc.
The Processor 300 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-ProgrammaBle gate array (FPGA) or other ProgrammaBle logic device, discrete gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 301 may be an internal storage unit of the terminal device 30, such as a hard disk or a memory of the terminal device 30. The memory 301 may also be an external storage device of the terminal device 30, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, provided on the terminal device 30. Further, the memory 301 may also include both an internal storage unit and an external storage device of the terminal device 30. The memory 301 is used for storing the computer program and other programs and data required by the terminal device. The memory 301 may also be used to temporarily store data that has been output or is to be output.
Example 3
In this embodiment, the low-voltage optimization control simulation is performed on an actual distribution network system in a certain city by using the low-voltage optimization control of the distribution network provided by the invention, the structure of the distribution network system is shown in fig. 5, and part of bus voltages of the distribution network system before the low-voltage optimization control are shown in table 1:
TABLE 1
Figure GDA0003516360930000131
As shown in table 1, the voltage at power distribution grid system node 29 is 0.8591, which is 0.9 below the minimum operating voltage; therefore, the power distribution network system has the problem of low voltage, and after the low voltage is judged to occur at the user side, the power distribution network system is subjected to low voltage optimization treatment.
The parameters of the multi-objective particle swarm optimization algorithm are shown in table 2:
TABLE 2
Figure GDA0003516360930000141
After low-voltage optimization treatment, the specific treatment scheme is obtained as follows:
and the compensation positions and capacities are shown in table 3:
TABLE 3
Figure GDA0003516360930000142
The series compensation position and impedance are shown in table 4:
TABLE 4
Figure GDA0003516360930000143
The voltage curves before and after the low-voltage optimization treatment are shown in fig. 6, and it can be seen from fig. 6 that after the low-voltage optimization treatment, the voltage of the distribution grid system is increased to be above 0.9p.u, and the low-voltage problem is solved.
The power loss and voltage deviation of the distribution grid system before and after low voltage governance are shown in table 5:
TABLE 5
Figure GDA0003516360930000144
According to the simulation result, the low-voltage problem of the power distribution network system is solved, and the network loss and the voltage deviation of the power distribution network system are greatly improved.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (10)

1. A power distribution network low voltage optimization treatment method is characterized by comprising the following steps:
s1: dividing the power distribution network system into four areas, and making corresponding low-voltage treatment measures for each area; wherein, four regions include: the system comprises a main transformer area, a medium-voltage terminal area, a distribution transformation area and a user side area; the low voltage treatment measures in the main transformer area comprise: transformation of a power transmission network, transformation of a transformer and reactive compensation; the low voltage treatment measures of the medium voltage end region comprise: replacing a lead, adding a voltage regulator, performing reactive compensation and changing the gear of the voltage regulator; low voltage treatment measures for distribution transformer areas include: reactive compensation and distribution and transformation capacity increasing; the low voltage treatment measures of the user side area comprise: reactive compensation, voltage regulator addition, wire replacement and three-phase unbalance management;
s2: acquiring power grid parameters of a power distribution network system in real time, carrying out load flow calculation on the power grid by adopting a Newton-Raphson method according to the power grid parameters, and judging whether low voltage occurs in the power distribution network system according to the load flow calculation result;
s3: if low voltage occurs in the power distribution network system, sequentially judging whether the four areas generate low voltage, determining the areas generating the low voltage, and acquiring low voltage treatment measures corresponding to the areas generating the low voltage;
s4: and optimizing the corresponding low-voltage treatment measures of the low-voltage area based on a multi-objective particle swarm optimization algorithm to obtain the low-voltage optimized treatment measures of the low-voltage area, and performing optimized treatment on the power distribution network system according to the low-voltage optimized treatment measures.
2. The power distribution network low-voltage optimization governance method according to claim 1, wherein optimization objectives of the multi-objective particle swarm optimization algorithm include system grid loss, voltage deviation and low-voltage governance cost; the constraint conditions comprise power flow equation constraint, generator reactive power output constraint, voltage constraint and voltage regulator transformation ratio constraint.
3. The power distribution network low-voltage optimization treatment method according to claim 2, wherein a calculation formula of system network loss is specifically as follows:
Figure FDA0003728229050000011
in the formula: p is loss Is the system network loss, and L is the total number of branches of the power distribution network system; g k Is the conductance of branch k of the distribution network system; u shape i Is the voltage amplitude, U, of the branch k node i of the distribution network system j Is the voltage amplitude value theta of the nodes j at two ends of the branch k of the power distribution network system ij Is the phase angle difference between node i and node j of branch k of the power distribution network system.
4. The power distribution network low-voltage optimization treatment method according to claim 3, wherein a calculation formula of the voltage deviation is as follows:
Figure FDA0003728229050000021
in the formula: u shape deviation Is the voltage deviation, n is the total number of nodes in the power distribution grid system;
Figure FDA0003728229050000022
is the expected voltage of the distribution network system node j; u shape jmax And U jmin The upper voltage limit and the lower voltage limit of the node j of the power distribution network system are respectively.
5. The power distribution network low-voltage optimization treatment method according to claim 2, wherein a calculation formula of the low-voltage treatment cost is as follows:
Figure FDA0003728229050000023
in the formula: f. of invest For low voltage treatment costs, m is the total number of equipment required for low voltage treatment measures, E investj Is the fixed cost of equipment required by low voltage treatment measures; n is the number of reactive power compensation devices, Q cz Is the reactive compensation capacity of the reactive power compensation device z; c c Is the unit reactive power compensation cost.
6. The power distribution network low-voltage optimization treatment method according to claim 2, wherein the specific process of the step S4 is as follows:
s41: initializing parameters of the multi-target particle swarm optimization algorithm, and randomly initializing the positions and the speeds of particles in a swarm of the multi-target particle swarm optimization algorithm, wherein the positions of the particles are control variables of reactive power compensation;
s42: setting control variables which do not meet constraint conditions of the multi-target particle swarm optimization algorithm in the particles as the upper limit or the lower limit of the constraint conditions;
s43: calculating the system network loss, the voltage deviation and the low-voltage governing cost of the power distribution network system under the condition of meeting the constraint condition, determining the weight coefficients of the system network loss, the voltage deviation and the low-voltage governing cost, and performing weighted summation on the system network loss, the voltage deviation and the low-voltage governing cost according to the weight coefficients to obtain a fitness function:
s44: calculating the fitness of the population and the fitness of particles in the population according to a fitness function, taking the population with the minimum fitness as a global optimal solution, and taking the particles with the minimum fitness as a particle optimal solution;
s45: updating the position and the speed of the particles according to the global optimal solution and the particle optimal solution, and judging whether the preset iteration times are reached; if not, increasing the iteration times by 1 time, and re-executing the step S42 to the step S45; and if the preset iteration times are reached, outputting the updated position and speed of the particles to obtain low-voltage optimization treatment measures, and performing optimization treatment on the area of the power distribution network system with low voltage according to the low-voltage optimization treatment measures.
7. The power distribution network low voltage optimization treatment method according to claim 6, wherein in step S41, initializing parameters of a multi-objective particle swarm optimization algorithm specifically comprises:
initializing the population scale, the acceleration coefficient, the maximum iteration times, the maximum weight coefficient and the minimum weight coefficient of the target particle swarm algorithm.
8. The method as claimed in claim 6, wherein in step S41, the control variables for reactive compensation include switchable parallel capacitors/reactors Q c Tap K of a tap changer T Length L of the replacement wire l 。
9. The utility model provides a power distribution network low voltage optimizes treatment system which characterized in that includes: the device comprises a low voltage treatment measure formulation module, a low voltage detection module, a low voltage region judgment module and a low voltage optimization treatment module;
the low-voltage treatment measure making module is used for dividing the power distribution network system into four areas and making corresponding low-voltage treatment measures for each area; wherein, four regions include: the system comprises a main transformer area, a medium-voltage terminal area, a distribution transformation area and a user side area; the low voltage treatment measures in the main transformer area comprise: transformation of a power transmission network, transformation of a transformer and reactive compensation; the low voltage treatment measures of the medium voltage end region comprise: replacing a lead, adding a voltage regulator, performing reactive compensation and changing the gear of the voltage regulator; the low voltage treatment measures in the distribution transformation area comprise: reactive compensation and distribution and transformation capacity increasing; the low voltage treatment measures of the user side area comprise: reactive compensation, voltage regulator addition, wire replacement and three-phase unbalance management;
the low-voltage detection module is used for acquiring power grid parameters of the power distribution network system in real time, carrying out load flow calculation on the power grid by adopting a Newton-Raphson algorithm according to the power grid parameters, and judging whether low voltage occurs in the power distribution network system according to the load flow calculation result;
the low-voltage area judgment module is used for sequentially judging whether the four areas generate low voltage when the low voltage occurs in the power distribution network system, determining the areas generating the low voltage and acquiring low-voltage treatment measures corresponding to the areas generating the low voltage;
the low-voltage optimization treatment module is used for optimizing low-voltage treatment measures corresponding to the low-voltage area based on a multi-objective particle swarm optimization algorithm to obtain the low-voltage optimization treatment measures of the low-voltage area, and performing optimization treatment on the power distribution network system according to the low-voltage optimization treatment measures.
10. The low-voltage optimization treatment equipment for the power distribution network is characterized by comprising a processor and a memory;
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is used for executing the power distribution network low voltage optimization treatment method in any one of claims 1 to 8 according to the instructions in the program code.
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