基于改进遗传算法的配电网无功优化研究

doi:10.16180/j.cnki.issn1007-7820.2019.05.003

Abstract

Abstract:

Effectively reducing the loss of distribution network active power has been an important issue in the safe and economic operation of distribution networks. In order to solve the problem of large network loss in local areas,an improved genetic algorithm was proposed for reactive power compensation optimization. While considering the topological structure of distribution network, an adaptive genetic operator was designed and an exponential fitness function was constructed to promote the convergence speed and precision of genetic algorithm. In this way, the global random search capability of genetic algorithm could be fully utilized. The results of optimizing a 16-node study showed that the active network loss of the distribution network dropped from 6.76% to 5.16%,and the voltage qualification rate increased from 70.61% to 92.86%,indicating both the global optimization accuracy and the voltage quality of the regional network were improved. In addition, it also proved that this improved genetic algorithm is feasible for reactive power optimization.

Key words: distribution network, multi objective reactive power optimization, reduction of net loss, improved genetic algorithm, adaptive operator

CLC Number:

TP714

CHEN Qiang,LIU Jin,YANG Haima,LIU Haishan,WEI Yu. Research on Reactive Power Optimization of Power Distribution Network Based on Improved Genetic Algorithm[J].Electronic Science and Technology, 2019, 32(5): 11-16.

Figures/Tables 10

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References 16

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节点号	电压等级/kV	有功负荷	无功负荷
1	110	0	0
2	110	0.183 8	0.112 5
3	110	0.183 8	0.112 5
4	110	0	0
5	10	0.335 0	0.178 3
6	110	0	0
7	10	0.229 3	0.106 8
节点号	电压等级/kV	有功负荷	无功负荷
8	110	0	0
9	110	0	0
10	10	0.2	0.1
11	110	0	0
12	110	0	0
13	35	0.235 8	0.114 0
14	10	0.122 8	0.059 5
15	35	0.051 8	0.031 8
16	35	0	0

最大迭代数	350	允许电压偏差	±7%
最小交叉率	0.3	最大交叉率	0.8
最小变异率	0.001	最大变异率	0.3
网损权重系数	0.6	罚函数权重系数	0.4

补偿节点	补偿容量	补偿节点	补偿容量
5	124	12	106
6	27	13	15
7	167	14	52
10	68	16	11

变压器号	变压器变比	档位调节范围
T01	1.040	-1
T02	1.045	0
T03	1.040	1
T04	1.035	-2
T05	1.003	3
T06	1.052	-1

算法对比	网损率(I%)	电压达标率(I%)	总补偿容量/kVar
无功补偿前	0.067 6	70.61	480
传统遗传算法优化	0.053 3	85.42	680
改进遗传算法优化	0.051 6	92.86	570

Research on Reactive Power Optimization of Power Distribution Network Based on Improved Genetic Algorithm

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