Scope of Biogeography Based Optimization for Economic Load Dispatch and Multi-Objective Unit Commitment Problem

Abstract

Biogeography Based Optimization (BBO) algorithm is a population-based algorithm based on biogeography concept, which uses the idea of the migration strategy of animals or other spices for solving optimization problems. Biogeography Based Optimization algorithm has a simple procedure to find the optimal solution for the non-smooth and non-convex problems through the steps of migration and mutation. This research paper presents the solution to Economic Load Dispatch Problem for IEEE 3, 4, 6 and 10-unit generating model using Biogeography Based Optimization algorithm. It also presents the mathematical formulation of scalar and multi-objective unit commitment problem, which is a further extension of economic load dispatch problem.

Optimal Allocation of Static Synchronous Series Compensator Controllers using Chemical Reaction Optimization for Reactive Power Dispatch

“…Therefore, these approaches are not appropriate for solving ORPD. To overcome these limitations, the robust and flexible evolutionary optimization techniques such as, simple genetic algorithms " Iba (1994)", evolutionary strategies " Bhagwan, and Patvardhan (2003)", evolutionary programming "Liang, Chung, Wong and Duan(2006) ", particle swarm optimization " Yoshida, Fukuyama, Kawata, Takayama and Nakanishi (2000)", differential evolution " Liang, Chung, Wong, Duzn, and Tse (2007)", real coded genetic algorithms (RGA) " Subbaraj and Rajnaryanan(2009)", tabu search (TS) " Khalid, Kumar, Mishra & (2014)" simulated annealing (SA) " Dao, Zelinka, & Duy, H. (2012)", teaching learning based optimization (TLBO) " Mukherjee, Paul, & Roy, (2015)", cultural algorithm (CA) "Som., & Chakraborty, (2012)", improved particle swarm optimization (IPSO) "Polprasert, Ongsakul, & Dieu, (2013)", biogeography based optimization (BBO) " Kamboj, & Bath, (2014)" and firefly algorithm (FA) " have been applied. These evolutionary algorithms have shown success in solving the ORPD problems since they do not need the objective and constraints as differentiable and continuous functions.…”