Hybridization of particle swarm optimization with biogeography based optimization to solve economic load dispatch considering spinning reserve and other non-linerarities

This paper presents the combination of particle swarm optimization (PSO) and biogeography-based optimization (BBO) algorithm to solve constrained economic load dispatch (ELD) problems in power system, considering valve point nonlinearities of generators, prohibited operating zones, ramp rate and spinning reserve. PSO is a well popular and robust evolutionary algorithm for solving global optimization problems, whereas BBO is a relatively new biogeography inspired algorithm. In this paper, the hybridization of PSO and BBO (HPSOBBO) is proposed to improve the convergence speed and solution quality. In this paper, two ELD problems have been adopted to investigate the effectiveness of the proposed algorithm A comparison of simulation results reveals that the proposed algorithm is better than, other well established algorithms in terms of the quality of the solution.

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