Title: Multi-phase search optimisation algorithm for constrained optimal power flow problem

Authors: Ragab A. El-Sehiemy; Muhammad B. Shafiq; Ahmed M. Azmy

Addresses: Electrical Engineering Department, Faculty of Engineering, Kafrelsehiekh University, Kafrelsehiekh, Egypt ' Electrical Engineering Department, Faculty of Engineering, Kafrelsehiekh University, Kafrelsehiekh, Egypt ' Electrical Engineering Department, Faculty of Engineering, Tanta University, Tanta, Egypt

Abstract: This paper proposes an enhanced solution for security constrained optimal power flow (SC-OPF) problem based on multi-phase search optimisation algorithm (MSOA). The objective is to minimise the generation costs by optimising the control variables, such as generator power, and satisfying system constraints. MSOA simulates the performance of humans' intelligent search with memory, experience and uncertainty reasoning. The proposed algorithm is integrated with Lagrangian relaxation factors to deal with network constrains. The proposed technique is carried out on the IEEE 30-bus, 57-bus test systems and a real power system at West Delta Network as part of the Unified Egyptian Network. The space reduction strategy succeeded to decrease the search space in each generation causing fast convergence to the optimal solution. The obtained results are compared with particle swarm optimisation technique to prove the effectiveness of MSOA in solving SC-OPF problems in normal and emergency conditions.

Keywords: emergency conditions; genetic algorithms; optimal power flow; particle swarm optimisation; PSO; seeker optimisation algorithm; SOA; multiphase search optimisation; constrained optimisation; security; power generation costs.

DOI: 10.1504/IJBIC.2014.065007

International Journal of Bio-Inspired Computation, 2014 Vol.6 No.4, pp.275 - 289

Received: 03 Mar 2013
Accepted: 22 Feb 2014
Published online: 21 Oct 2014 *

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