An approach to mitigate the risk of voltage collapse accounting uncertainties using improved particle swarm optimization

作者：Arya L D; Titare L S^*; Kothari D P

来源：Applied Soft Computing, 2009, 9(4): 1197-1207.

DOI：10.1016/j.asoc.2009.02.005

• Voltage stability
• Reactive power reserve
• Probabilistic risk
• Monte-Carlo simulation
• Radial Basis Function network
• Particle swarm optimization

This paper describes a new viewpoint for static voltage stability enhancement based on an improved particle swarm optimization technique. The objective function is selected for maximization of reactive power reserve subjected to usual operating constraints at an operating point. Probabilistic risk of voltage collapse has been used for maintaining desired level of voltage stability margin. This risk of voltage collapse is calculated accounting uncertainties in system parameters and control variables. Probabilistic risk of voltage collapse has been obtained by a trained Radial Basis Function network. Developed algorithm has been implemented on 6-bus, 14-bus and 25-bus IEEE test systems. Results have been compared with those obtained using Davidon-Fletcher-Powell's (DFP) method.

• 出版日期2009-9