CN111222649A - Self-healing capacity improvement planning method for power distribution network - Google Patents
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Abstract
The invention relates to a self-healing capacity improving and planning method for a power distribution network, which comprises the following steps: s1, determining measures for reinforcing weak lines, combining the line reinforcing measures in the power distribution network, optimizing the line reinforcing measure combination in the power distribution network by utilizing a particle swarm optimization algorithm within limited cost, obtaining a power distribution network reinforcing measure combination scheme with the minimum weighted fault probability, and implementing the reinforcing measures on the lines in the power distribution network according to the scheme; s2, increasing connection paths between nodes and power supply points by adding tie lines in the power distribution network, and enhancing the net rack stiffness and power supply guarantee capability of the power distribution network; s3, performing site selection optimization on the emergency mobile power supply and the emergency repair resources by using a particle swarm optimization algorithm to obtain an optimal configuration position, so that the emergency mobile power supply support degree and the emergency repair resource distribution degree are maximized. According to the invention, the self-healing capability of the power distribution network is improved from three aspects of net rack strength, emergency mobile power supply and emergency repair resources.
Description
Technical Field
The invention belongs to the technical field of urban network planning management, and particularly relates to a self-healing capacity improvement planning method for a power distribution network.
Background
The construction of a first-class power distribution network is an important component for implementing a strong smart power grid, and the construction of the first-class power distribution network also takes the electric power requirement for people to pursue a beautiful life as a starting point and a footfall point of all work. An important characteristic of the first-class power distribution network is that the first-class power distribution network has self-healing capability after a fault, can quickly recover power supply after the power system has the fault, ensures the reliability of power supply, ensures that the reliability index of the first-class power distribution network can meet the requirement, and reaches or approaches the standard of the first-class power distribution network in the world.
By means of a flexible topological structure and energy storage of a first-class power distribution network, a mobile power supply, an electric automobile and the like, the power distribution network can be used as an emergency power supply for fault recovery, and by means of intelligent power distribution technologies such as a power distribution automation technology, a power distribution network energy management technology and a microgrid energy management technology, rapid online power supply recovery of the power distribution network after a fault, uninterrupted power supply of critical loads and system safety and economy adapting to operating environment changes can be achieved. Therefore, the optimal configuration of the emergency power supply of the first-class power distribution network has great theoretical and practical application value for improving the self-healing capacity. Based on the problems, the method for improving and planning the self-healing capacity of the power distribution network from three aspects of net rack strength, emergency mobile power supplies and emergency repair resources is provided, and the method has important practical significance.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a method for improving and planning the self-healing capacity of a power distribution network from three aspects of net rack strength, emergency mobile power supply and emergency repair resources.
The technical problem to be solved by the invention is realized by adopting the following technical scheme:
a self-healing capacity improvement planning method for a power distribution network comprises the following steps:
s1, determining measures for reinforcing weak lines, combining the line reinforcing measures in the power distribution network, optimizing the line reinforcing measure combination in the power distribution network by utilizing a particle swarm optimization algorithm within limited cost, obtaining a power distribution network reinforcing measure combination scheme with the minimum weighted fault probability, and implementing the reinforcing measures on the lines in the power distribution network according to the scheme;
s2, increasing connection paths between nodes and power supply points by adding tie lines in the power distribution network, and enhancing the net rack stiffness and power supply guarantee capability of the power distribution network;
s3, performing site selection optimization on the emergency mobile power supply and the emergency repair resources by using a particle swarm optimization algorithm to obtain an optimal configuration position, so that the emergency mobile power supply support degree and the emergency repair resource distribution degree are maximized.
Further, the method for optimizing the location of the emergency mobile power supply or the emergency repair resource by using the particle swarm optimization algorithm in the step S3 includes the following steps:
s301, inputting a power distribution network structure parameter and a load parameter;
s302, initializing particle swarm parameters including the number of the swarm, the position of an emergency mobile power supply or a first-aid repair resource and the iteration times;
s303, carrying out power distribution network load flow calculation to generate a reasonable original population;
s304, calculating the adaptive value of each particle according to the objective function, and updating the speed and the position of the particle;
s305, obtaining a global optimal solution;
s306, judging whether the power flow constraint is met, if so, turning to S307, and if not, turning to S304;
s307, judging whether the maximum iteration times is reached, if so, turning to S308, and if not, turning to S304;
and S308, outputting the position of the emergency power supply or the optimal solution of the emergency repair resource position, and ending.
Further, the measures for reinforcing the weak line in the step S1 include insulation modification of an overhead bare conductor C1, cabling modification of an overhead line C2, and replacement of an aged overload line C3, and the measures for reinforcing each line in the distribution network are combined to optimize a plurality of combinations, and the optimization method includes the following steps:
s101, acquiring fault probability statistical data and operation data of each line of the power distribution network and unit transformation investment cost of C1, C2 and C3;
s102, calculating statistical weighted fault probability of the power distribution network lines, and sequencing the statistical weighted fault probability according to a sequence from large to small;
s103, under the constraint of investment scale, optimizing each line reinforcing measure in the power distribution network by adopting a particle swarm optimization algorithm;
and S104, obtaining a power distribution network line reinforcement measure combination scheme with the minimum statistical weighted fault probability.
Further, the method for calculating the statistical weighted fault probability of the line in step S102 is as follows:
dividing the load of the power distribution network line into three grades, and sequentially giving weights a1, a2 and a3, wherein the statistical weighted fault probability of the line is as follows:
in the formula (I), the compound is shown in the specification,
the failure rate of the primary load node i,
the failure rate of the secondary load node j,
failure rate of tertiary load node k.
Furthermore, the line load of the power distribution network is classified according to the classification principle of 'design code of power supply and distribution system' GB 50052-2009.
Further, the method for adding the tie line to the power distribution network in step S2 includes the following steps:
s201, acquiring the power distribution network line structure data and parameters after the reinforcement measures of the step S1 are implemented, and increasing the planning number M of the tie lines;
s202, simulating N-1 faults of the power distribution network, and obtaining a planning set of possible connecting lines by an exhaustion method;
s203, sequencing repeated junctor lines in the planning set from large to small according to the repetition times, and selecting the first M junctor lines;
s204, performing N-1 verification, if yes, determining the current M tie lines, and if not, executing S205;
s205, deleting the Mth junctor, selecting the (M + 1) th junctor, determining the current M junctors if the M +1 th junctor is met, deleting the (M + 1) th junctor if the M +1 th junctor is not met, and sequentially verifying until verification is met.
Furthermore, the emergency repair resources comprise on-site detection equipment, emergency communication equipment, emergency transportation guarantee facilities, energy and power guarantee facilities, traffic and geotechnical engineering emergency repair facilities, electric power engineering emergency repair facilities and communication engineering emergency repair facilities.
The invention has the advantages and positive effects that:
according to the invention, the self-healing capacity of the power distribution network is improved by reinforcing weak lines, adding tie lines into the power distribution network, maximizing the emergency mobile power supply support degree and the emergency repair resource distribution degree, and combining the emergency power supply, the emergency repair resources and the network strength, so that the advantages of various measures in the aspect of improving the self-healing capacity of the power distribution network can be fully played, and the self-healing capacity of the power distribution network is enhanced.
Drawings
The technical solutions of the present invention will be described in further detail below with reference to the accompanying drawings and examples, but it should be understood that these drawings are designed for illustrative purposes only and thus do not limit the scope of the present invention. Furthermore, unless otherwise indicated, the drawings are intended to be illustrative of the structural configurations described herein and are not necessarily drawn to scale.
Fig. 1 is a schematic structural diagram of an initial power distribution network according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of the power distribution network optimized by using the power distribution network self-healing capacity improvement planning method according to the embodiment of the present invention;
in the figure, the mobile represents an emergency power supply, and the squad represents emergency repair resources;
Detailed Description
First, it should be noted that the specific structures, features, advantages, etc. of the present invention will be specifically described below by way of example, but all the descriptions are for illustrative purposes only and should not be construed as limiting the present invention in any way. Furthermore, any individual technical features described or implicit in the embodiments mentioned herein may still be continued in any combination or subtraction between these technical features (or their equivalents) to obtain still further embodiments of the invention that may not be mentioned directly herein.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
Examples
In this embodiment, a 33-bus system in fig. 1 is taken as an example, assuming that all lines are bare conductor overhead lines, and the failure probability adopts a failure probability distribution result within five years. The load grades in the system are shown in table 1, the emergency power supplies are respectively positioned at nodes 5, 14 and 28, the capacities are respectively 4000kWh, 3000kWh and 4000kWh, and the maximum output powers are respectively 500kW, 400kW and 500 kW. Emergency repair resources are respectively distributed at a node 2 and a node 10, and partial equipment is lost in on-site detection equipment, emergency communication equipment, emergency transportation guarantee equipment, energy and power guarantee equipment, traffic and geotechnical engineering emergency repair equipment, electric power engineering emergency repair equipment and communication engineering emergency repair equipment, and the statistical probability of emergency repair capacity of emergency repair group personnel is 95%;
the method for planning self-healing capacity improvement of the power distribution network in the figure 1 comprises the following steps:
s1, determining measures for reinforcing weak lines, combining the line reinforcing measures in the power distribution network, optimizing the line reinforcing measure combination in the power distribution network by utilizing a particle swarm optimization algorithm within limited cost, obtaining a power distribution network reinforcing measure combination scheme with the minimum weighted fault probability, and implementing the reinforcing measures on the lines in the power distribution network according to the scheme; the measure for reinforcing the weak line comprises insulation transformation of an overhead bare conductor C1, cabling transformation of an overhead line C2 and replacement of an aged overload line C3, wherein the insulation transformation of the overhead bare conductor refers to insulation treatment of the bare conductor, the cabling transformation of the overhead line refers to replacement of the line into a cable, and the replacement of the aged overload line refers to replacement of the aged line; the method comprises the following steps of combining strengthening measures of all lines in the power distribution network, and optimizing a plurality of combinations, wherein the optimization method comprises the following steps:
s101, acquiring fault probability statistical data and line operation data (including operation years and overload duration and frequency in statistical years) of each line of the power distribution network and unit transformation investment costs of C1, C2 and C3;
the fault probability of the line is calculated within five years in a certain city on the coast, the fault probability of the bare conductor is 15.64 percent, the fault probability of the insulated conductor is 8.56 percent, the fault probability of the cable line is 3.65 percent, and the fault probability distribution obeys normal distribution.
S102, calculating statistical weighted fault probability of the power distribution network lines, and sequencing the statistical weighted fault probability according to a sequence from large to small;
the load of the power distribution network line is classified according to the classification principle of ' design specification for power supply and distribution system ' GB50052-2009 ', the load of the power distribution network is divided into three grades, and as shown in Table 1, weights a1, a2 and a3 are sequentially given, so that the statistical weighted fault probability of the line is as follows:
in the formula (I), the compound is shown in the specification,
the failure rate of the primary load node i,
the failure rate of the secondary load node j,
the failure rate of the tertiary load node k;
TABLE 1 load rating
| Load rating | Weight of | Node point |
| First stage | 100 | 1,3,6,7,13,17,19,23,24,29,30,31 |
| |
10 | 2,4,5,10,11,12,18,20,25,27 |
| Three-stage | 1 | 8,9,14,15,16,21,22,26,28,32 |
The statistical weighted fault probability of the line is calculated by using the above formula, and is L7, L6(L8), L5, L9, L10, L26, L27, L4, L29, L11, L30, L19, L31, L12, L20, L3, L13, L2, L14, L17, L21(L24), L15, L1, 1L8(L22, L23), L25, L16, L28 and L32 in sequence from large to small.
S103, under the constraint of investment scale, optimizing each line reinforcing measure in the power distribution network by adopting a particle swarm optimization algorithm;
and S104, obtaining a power distribution network line reinforcement measure combination scheme with the minimum statistical weighted fault probability.
Through optimization of a particle swarm optimization algorithm, in the investment cost, the optimization result is a reinforcing mode of insulating and transforming the overhead bare conductor C1.
S2, increasing connection paths between nodes and power supply points by adding tie lines in the power distribution network, and enhancing the net rack stiffness and power supply guarantee capability of the power distribution network; the method for adding the junctor to the power distribution network comprises the following steps:
s201, acquiring the power distribution network line structure data and parameters after the reinforcement measures of the step S1 are implemented, and increasing the planning number M of the tie lines;
s202, simulating N-1 faults of the power distribution network, and obtaining a planning set of possible connecting lines by an exhaustion method;
s203, sequencing repeated junctor lines in the planning set from large to small according to the repetition times, and selecting the first M junctor lines;
s204, performing N-1 verification, if yes, determining the current M tie lines, and if not, executing S205;
s205, deleting the Mth junctor, selecting the (M + 1) th junctor, determining the current M junctors if the M +1 th junctor is met, deleting the (M + 1) th junctor if the M +1 th junctor is not met, and sequentially verifying until verification is met.
Specifically, the method comprises the following steps: and 5 interconnection switches are added, namely S7-20, S8-14, S11-21, S17-32 and S24-28, so that the connection path among any nodes can be effectively increased, and the power supply capacity of a power point to a load is improved.
And S3, maximizing emergency mobile power supply support degree and emergency repair resource distribution degree, and performing site selection by using a particle swarm optimization algorithm to finally obtain an optimal configuration position.
The positions of emergency power supplies and emergency repair resources are planned, the specific content of an optimized configuration result is shown in fig. 2, the positions of the emergency power supplies are calculated to be 7, 17 and 30 in sequence, at the moment, all primary loads and newly added emergency power supplies in the power distribution network cover all primary loads, when a fault occurs, important unit loads are quickly restored to a normal operation state under the action of the emergency power supplies, and the loads are merged into the power distribution network again after the line is repaired. Therefore, the coverage rate of the emergency power supply and the power supply capacity of the emergency power supply are greatly improved. In addition, when the positions of the emergency repair resources are 1 and 8 respectively, the trunk line is covered, the peripheral branch lines are radiated, and once the line is damaged, the repair can be rapidly carried out on site.
And by filling up the lost emergency repair equipment and developing regular training on physical ability and knowledge of personnel of the emergency repair group, the comprehensive quality of the emergency repair group is required to reach 98% or more, and the emergency repair process can be effectively accelerated.
Adopt distribution network self-healing ability evaluation index to calculate the distribution network self-healing ability after optimizing, wherein, the evaluation index contains the three one-level index of rack intensity, emergent portable power source support degree, emergent team service degree, has set up three second grade index again under the one-level index respectively, and is specific:
1. strength of net frame
The net rack firmness is defined as that the distribution network passes through the spatial grid structure and strengthens first-class distribution network self-healing ability, ensures that the distribution network after the distribution network reply trouble calamity maintains the reliability of load power supply, and the net rack firmness includes following three second grade indexs:
1) communication switch occupancy (SC11)
The contact switch has extremely important effect in the distribution network, especially in the self-healing ability after the trouble, through the operation of intelligence contact switch, can in time carry out the transfer of load and change the confession to realize the self-healing of first-class distribution network fast:
in the formula, NconNumber of intelligent interconnection switches of first-class distribution network, NlineIs the total number of lines in a first-class distribution network;
2) effective guarantee capability of net rack (SC12)
The effective guarantee capability of the net rack represents the ratio of the number of the effective possible power supply paths connected with the load nodes to the total number of the lines, and the redundancy of the power supply paths of the load nodes of the first-class power distribution network is indicated;
in the formula (I), the compound is shown in the specification,
is the number of possible supply paths, N, of node iloadIs the number of load nodes of a first-class distribution network.
3) Line statistical weighted fault rate
Line statistics weighting fault rate has represented the fault probability of the different grade type load power supply of first-class distribution network, and the more effective weak link of differentiation distribution network rack, this index consider load importance degree and fault probability simultaneously, divide into three grades with the distribution network load, give weight a1, a2, a3 in proper order:
in the formula (I), the compound is shown in the specification,
the failure rate of a class of load nodes i,
the failure rate of the class two load node j,
the failure rate of the class III load node k;
2. mobile power supply support degree
The mobile power supply is used as an important form of emergency resources, the reasonable configuration of the mobile power supply has positive effects on the stable and reliable operation of the self-healing load of a first-class power distribution network, the mobile power supply has the transferability of space and time, can be dispatched to a reasonable position in time according to the demand of the load, and has great advantages compared with a fixed standby power supply, and the emergency power supply comprises the following three secondary indexes:
1) mobile power supply ratio (SC21)
The occupation ratio of the mobile power supply is the ratio of the capacity of the mobile power supply configured in a first-class power distribution network to the load of the power distribution network. After the distribution network breaks down, especially multiple spot trouble, if the load can't pass through network reconsitution or stand-by power supply when supplying power, will optimize dispatch distribution portable power source and provide the power for the load, portable power source's occupation of area is bigger, and is stronger to the operational capability of whole distribution network:
in the formula (I), the compound is shown in the specification,
representing the capacity, P, of a mobile emergency power supply configured by node iloadThe total load of all nodes of the power distribution network.
2) Efficiency of mobile power supply
The emergency power supply can supply power for loads within the coverage range of the power supply radius, so that the larger the power supply radius is, the wider the coverage range is, and the better the effective rate of the mobile power supply is. Since the emergency power supply is mainly used for supplying power to the first-stage load, the more the first-stage load in the coverage range represents the larger the value of the first-stage load. The mobile power supply efficiency can be expressed as:
in the formula (I), the compound is shown in the specification,
the power supply radius of the i-node emergency mobile power supply and the j-node key load,
is the critical load power of node j.
3) Power supply radius of mobile power supply
The power supply radius of the mobile power supply is the maximum power supply path of the emergency mobile power supply. The power supply radius indicates the farthest load node path that the mobile power supply can reach within the allowed rush repair time.
3. Degree of service for emergency squad
The emergency repair after the fault is an important means for effectively improving the self-healing capacity of the first-class power distribution network, and the number of emergency repair teams, the personnel capacity, field resources and other conditions are closely related. Wherein the resource kind includes field detection equipment, emergency communication equipment, urgent transportation guarantee group, energy power guarantee group, traffic and geotechnical engineering salvagees the group, electric power engineering salvagees the group, communication engineering salvagees the group, includes following three second grade index:
1) degree of distribution of first-aid repair group
The distribution degree representation of the emergency repair group is compared with the distribution characteristics of a high-fault-rate line in the power distribution network, the emergency repair group can rapidly reach the emergency repair site, and the self-healing speed and level of a first-class power distribution network are accelerated:
in the formula (I), the compound is shown in the specification,
represents the shortest path of the emergency repair team to each load node,
representing the shortest path of the load node.
2) Statistical probability of repair capacity
The statistical probability of the emergency repair capacity indicates the statistical condition of the emergency repair efficiency and the completion condition of the group, the factors influencing the capacity of the emergency repair team comprise the number of people in the team, professional knowledge and emergency repair speed, the emergency repair capacity of the group can be effectively reflected, and the influence on the self-healing force of the first-class power distribution network is reflected from the side surface.
This data can be characterized by statistical data over a five year period.
3) First-aid repair resource man-average rate
The unbalance phenomenon of rush-repair resources can be avoided by the man-average rate of the rush-repair resources, and rush-repair personnel can be guaranteed to quickly reach a repair point.
In the formula, MgroupFor first-aid repair of a small group of people, NresoThe number of the first-aid repair resources is.
The self-healing capability calculation results after the optimized configuration are shown in table 2. After measures are taken, the network robustness and the emergency resource configuration index are obviously improved.
TABLE 2 lifting results
| SC11 | SC12 | SC13 | SC21 | SC22 | SC23 | SC31 | SC32 | SC33 | |
| Before planning | 0％ | 1 | 160.98 | 36.8 | 56.3％ | 5％ | 9％ | 95％ | 1 |
| After planning | 13.5％ | 2.2 | 106.63 | 36.8 | 86.5％ | 8％ | 6％ | 98％ | 1 |
The present invention has been described in detail with reference to the above examples, but the description is only for the preferred examples of the present invention and should not be construed as limiting the scope of the present invention. All equivalent changes and modifications made within the scope of the present invention shall fall within the scope of the present invention.
Claims (7)
1. A self-healing capacity improving and planning method for a power distribution network is characterized by comprising the following steps: the method comprises the following steps:
s1, determining measures for reinforcing weak lines, combining the line reinforcing measures in the power distribution network, optimizing the line reinforcing measure combination in the power distribution network by utilizing a particle swarm optimization algorithm within limited cost, obtaining a power distribution network reinforcing measure combination scheme with the minimum weighted fault probability, and implementing the reinforcing measures on the lines in the power distribution network according to the scheme;
s2, increasing connection paths between nodes and power supply points by adding tie lines in the power distribution network, and enhancing the net rack stiffness and power supply guarantee capability of the power distribution network;
s3, performing site selection optimization on the emergency mobile power supply and the emergency repair resources by using a particle swarm optimization algorithm to obtain an optimal configuration position, so that the emergency mobile power supply support degree and the emergency repair resource distribution degree are maximized.
2. The self-healing capacity improvement planning method for the power distribution network according to claim 1, characterized in that: the method for optimizing the position of the emergency mobile power supply or the emergency repair resource by using the particle swarm optimization algorithm in the step S3 comprises the following steps:
s301, inputting a power distribution network structure parameter and a load parameter;
s302, initializing particle swarm parameters including the number of the swarm, the position of an emergency mobile power supply or a first-aid repair resource and the iteration times;
s303, carrying out power distribution network load flow calculation to generate a reasonable original population;
s304, calculating the adaptive value of each particle according to the objective function, and updating the speed and the position of the particle;
s305, obtaining a global optimal solution;
s306, judging whether the power flow constraint is met, if so, turning to S307, and if not, turning to S304;
s307, judging whether the maximum iteration times is reached, if so, turning to S308, and if not, turning to S304;
and S308, outputting the position of the emergency power supply or the optimal solution of the emergency repair resource position, and ending.
3. The self-healing capacity improvement planning method for the power distribution network according to claim 1, characterized in that: the measures for reinforcing the weak line in the step S1 include insulation modification of an overhead bare conductor C1, cabling modification of an overhead line C2 and replacement of an aged overload line C3, the measures for reinforcing each line in the power distribution network are combined, and a plurality of combinations are optimized, wherein the optimization method comprises the following steps:
s101, acquiring fault probability statistical data and operation data of each line of the power distribution network and unit transformation investment cost of C1, C2 and C3;
s102, calculating statistical weighted fault probability of the power distribution network lines, and sequencing the statistical weighted fault probability according to a sequence from large to small;
s103, under the constraint of investment scale, optimizing each line reinforcing measure in the power distribution network by adopting a particle swarm optimization algorithm;
and S104, obtaining a power distribution network line reinforcement measure combination scheme with the minimum statistical weighted fault probability.
4. The power distribution network self-healing capacity improvement planning method according to claim 3, characterized in that: the method for calculating the statistical weighted fault probability of the line in the step S102 is as follows:
dividing the load of the power distribution network line into three grades, and sequentially giving weights a1, a2 and a3, wherein the statistical weighted fault probability of the line is as follows:
in the formula (I), the compound is shown in the specification,
the failure rate of the primary load node i,
the failure rate of the secondary load node j,
failure rate of tertiary load node k.
5. The power distribution network self-healing capacity improvement planning method according to claim 4, characterized in that: and the line load of the power distribution network is classified according to the classification principle of 'design specification of power supply and distribution system' GB 50052-2009.
6. The self-healing capacity improvement planning method for the power distribution network according to claim 1, characterized in that: the method for adding the tie line to the power distribution network in the step S2 includes the following steps:
s201, acquiring the power distribution network line structure data and parameters after the reinforcement measures of the step S1 are implemented, and increasing the planning number M of the tie lines;
s202, simulating N-1 faults of the power distribution network, and obtaining a planning set of possible connecting lines by an exhaustion method;
s203, sequencing repeated junctor lines in the planning set from large to small according to the repetition times, and selecting the first M junctor lines;
s204, performing N-1 verification, if yes, determining the current M tie lines, and if not, executing S205;
s205, deleting the Mth junctor, selecting the (M + 1) th junctor, determining the current M junctors if the M +1 th junctor is met, deleting the (M + 1) th junctor if the M +1 th junctor is not met, and sequentially verifying until verification is met.
7. The self-healing capacity improvement planning method for the power distribution network according to any one of claims 1 to 6, characterized in that: the emergency repair resources comprise on-site detection equipment, emergency communication equipment, emergency transportation guarantee facilities, energy power guarantee facilities, traffic and geotechnical engineering emergency repair facilities, electric power engineering emergency repair facilities and communication engineering emergency repair facilities.
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