Synergistic Optimization of Harmonic Suppression and Loss Reduction in Distribution Networks Based on PSO

doi:10.11930/j.issn.1004-9649.202503008

Abstract

Abstract:

With the increasing complexity of distribution networks and the growing demand for power quality, harmonic pollution and network losses have become key factors affecting system stability and operational efficiency. This paper proposes an innovative approach based on the particle swarm optimization (PSO) algorithm, aimed at simultaneously optimizing the configuration of capacitors and active power filter (APF) to achieve the dual objectives of harmonic suppression and network loss minimization. First, a harmonic power flow analysis model is used to assess harmonics, with frequency-domain modeling based on the harmonic penetration method. Then, the simultaneous configuration of capacitors and APF in the distorted distribution network is modeled, and the mixed-integer nonlinear programming problem of optimizing the simultaneous configuration of capacitors and APF is solved using the PSO algorithm. Experimental results show that proper configuration of capacitors and APF significantly improves the network's voltage quality, the proposed synergistic optimization method not only reduces system costs but also significantly improves the network's power quality and operational efficiency.

Key words: harmonic power flow, distribution network quality, network loss

LI Zhipeng, LIU Shaobo, YANG Hao, DONG Rui, QI Chenfeng, SHEN Shuo, ZHAO Peng. Synergistic Optimization of Harmonic Suppression and Loss Reduction in Distribution Networks Based on PSO[J]. Electric Power, 2025, 58(8): 50-59.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202503008

https://www.electricpower.com.cn/EN/Y2025/V58/I8/50

Figures/Tables 14

Fig.1 The flowchart of the proposed optimization procedure

Fig.2 The IEEE 14-node test network

Fig.3 The harmonic content of a six-pulse rectifier

Fig.4 Network voltage profiles before and after optimizing capacitor placement in the first study

Fig.5 THD factor of network voltages before and after optimizing capacitor allocation in the first study.

Table 1 Results of optimal APF configuration in the first study

位置（总线）	规格大小/%	电流有效值	APF 成本	最大 THD/%	最大 IHD/%	总成本/元
7	4	3.55	27400	5	3	66600
13	8	7.25	36900	5	3	66600

Fig.6 Harmonic content of APF injection currents in the first study

Fig.7 Network voltage THD factor before and after optimal configuration of APF in the first study

Table 2 Results of optimal APF configuration in the second study

位置（总线）		规格大小/%		电流有效值		APF 成本		最大 THD/%		最大 IHD/%		总成本/ 元
7		7		6.4		32,400		4.99		3		35100

Table 3 Comparison of research cost results

研究	电容器成本/元	APF成本/元	损耗/kW	总成本/元
1	13896	66600	961	241983
2	14999	35100	1279	264942
3	13779	44100	997	225417

Table 4 Performance comparison of different optimization algorithms

指标	PSO	GA	DE	GWO	最优算法
网络损耗/kW	997	1085	1023	1055	PSO
最大THD/%	3.0	3.8	3.2	3.5	PSO
总成本/万元	22.54	24.17	23.41	23.89	PSO
平均迭代次数	250	400	300	350	PSO
单次耗时/s	45.2	72.1	58.6	63.4	PSO
重复实验方差	0.12	0.36	0.25	0.31	PSO

Table 5 Differences in equipment configuration schemes

算法	电容器容量/(kV·A)	APF位置与规格	谐波抑制策略缺陷
PSO	750（节点7）	节点7: 3.5%	无
GA	1000（节点7）	节点7: 4%，节点13: 8%	APF过配置导致成本上升
DE	750（节点7）	节点7: 3.8%	电流谐波相位优化不足
GWO	1000（节点7）	节点7: 4.2%	局部最优导致损耗偏高

Fig.8 Comparison of harmonic suppression effects under different algorithms

Fig.9 Comparison of algorithm convergence curves

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