计及DG功率不确定性的配电网多目标无功优化*

doi:10.11985/2020.03.009

摘要/Abstract

摘要：

分布式电源(Distributed generation,DG)接入电网后,改变了原系统的潮流分布,并且分布式发电具有很强的出力随机性,这对系统损耗和节点电压产生不利影响,因此研究含DG的配电网无功优化对于提升电能质量和经济性具有重要的实际意义。针对分布式电源出力随机性以及负荷不确定性对系统损耗和节点电压的影响,建立了配电网的多目标概率无功优化模型。利用两点估计法对概率潮流进行确定性潮流计算,以处理所建出力模型中的不确定因素对无功优化结果的影响。同时,为克服粒子群算法(Particle swarm optimization,PSO)易陷入局部最优的缺陷,采用改进的粒子群算法(Improved particle swarm optimization,IPSO)对无功优化模型进行求解。最后对改进的IEEE33节点系统进行算例仿真测试。结果表明,所建模型可以达到降低损耗、改善节点电压质量的目的,也验证了IPSO算法的可行性及快速有效性。

关键词: 分布式电源, 随机性, 多目标优化, 改进粒子群优化算法

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

中图分类号:

TM715

赵金焕,马平. 计及DG功率不确定性的配电网多目标无功优化^*[J]. 电气工程学报, 2020, 15(3): 65-71.

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.

图/表 5

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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