Abstract
This paper proposes a novel and efficient hybrid algorithm based on combining particle swarm optimization (PSO) and gravitational search algorithm (GSA) techniques, called PSO-GSA. The core of this algorithm is to combine the ability of social thinking in PSO with the local search capability of GSA. Many practical constraints of generators, such as power loss, ramp rate limits, prohibited operating zones and valve point effect, are considered. The new algorithm is implemented to solve combined environmental economic dispatch (CEED) problem in power systems considering the power limits. The CEED is to minimize both the operating fuel cost and emission level simultaneously while satisfying the load demand and operational constraints. The effectiveness of the proposed algorithm has been tested on 10-unit system and the results were compared with other methods reported in recent literature. The simulation results show that the proposed algorithm outperforms previous optimization methods.
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