Multi-objective Reactive Power Optimization of Distribution Network Considering the Uncertainty of DG Power

doi:10.11985/2020.03.009

Abstract

Abstract:

Distributed generation (DG) connects to the electricity grid, changes the trend of the distribution of the original system, and the output of the distributed generation has a strong randomness, this adversely affects system losses and node voltages, so the research of DG distribution network reactive power optimization to improve power quality and economy has important practical significance. The multi-objective probabilistic reactive power optimization model of distribution network is established in view of the influence of the output randomness of distributed power supply and load uncertainty on the system network loss and node voltage. In order to deal with the influence of the uncertain factors in the established output model on the reactive power optimization results, the probabilistic power flow is calculated by the two-point estimation method. At the same time, in order to overcome the defect of particle swarm optimization (PSO), the improved particle swarm optimization (IPSO) is used to solve the reactive power optimization model. Finally, the improved IEEE33 node system is simulated and tested. The results show that the proposed model can reduce the loss, improve the quality of node voltage, it also verifies the feasibility and fast effectiveness of IPSO algorithm.

Key words: Distributed generation, randomness, multi-objective optimization, IPSO

CLC Number:

TM715

ZHAO Jinhuan,MA Ping. Multi-objective Reactive Power Optimization of Distribution Network Considering the Uncertainty of DG Power[J]. Journal of Electrical Engineering, 2020, 15(3): 65-71.

Figures/Tables 5

References 21

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项目		T	C3	C6	C15	C29
未接DG		0	0	0	0	0
接入DG	优化前优化后	+2	8	6	3	10
接入DG	优化前优化后	+2	6	5	2	8

项目		有功网损/kW	减少率(%)	电压偏移/p.u.	减少率(%)
未接DG		160.72	—	1.287 2	—
接入DG	优化前优化后	130.08	19.06	1.130 3	12.19
接入DG	优化前优化后	70.59	52.97	0.624 3	51.50