An Optimal Strategy to Maximise Voltage Stability Using Memetic Algorithms Based on Swarm Trajectory Movements

Abstract

Many power systems in the world today are operating closer to their stability boundaries, and thus it is critical for independent system operators (ISOs) to ensure that systems have adequate stability margins during operation in case of unexpected losses of system components. Failure to do so may result in a catastrophic widespread blackout, ie. system voltage collapses. This paper presents a novel memetic algorithm (MA)-based strategy to effectively maximise system voltage stability margins, through the optimum control of automatic voltage regulator (AVR) of generators, on-load tap changer (OLTC) of transformers and the sizes of shunt capacitors (SCs) etc, given any system operating conditions. The proposed strategy can assist ISOs to perform corrective actions to increase stability margins when the system operates too close to the stability boundaries. A mix-integer non-linear programming (MINLP) problem is formulated here using a MA based on the trajectory movement rule of particle swarm optimisation (PSO). By using the MA-based approach, system voltage collapse margins can be improved and these enhancements can then be verified using a continuation power flow (CPF) technique. The feasibility and practicality of this approach has been tested on a 3-machine 9-bus and the IEEE 118-bus power systems.

Key Words:

• Voltage stability
• memetic algorithms
• particle swarm optimisation

Additional information

Notes on contributors

S.H. Goh

Sheng How Goh received his BEng honours and PhD degrees in electrical engineering from the University of Queensland in 2001 and 2008, respectively. Currently, he is an engineer in the System Operations Planning and Performance team at NEMMCO. His research interests include available transfer capability, applications of optimisation and evolutionary computation in power systems, and power system stability and security.

Z.Y. Dong

Zhao Yang Dong received his PhD degree in Electrical and Information Engineering from The University of Sydney in 1999. He is now an associate professor at the School of Information Technology and Electrical Engineering, The University of Queensland. His research interests include power system security, electricity market, artificial intelligence and its application in power engineering, power system planning, and power system stability and control.

T.K. Saha

Tapan Kumar Saha was born in Bangladesh and immigrated to Australia in 1989. Currently he is a professor of electrical engineering in the School of Information Technology and Electrical Engineering, The University of Queensland. Before joining the University of Queensland, he taught at the Bangladesh University of Engineering and Technology, Dhaka, for three and a half years; and then at James Cook University, Queensland, for two and a half years. His research interests include power systems, power quality, and condition monitoring of electrical plants. Tapan is a Fellow of the Engineers Australia.