A Bacterial foraging PSO-DE algorithm for solving dynamic economic dispatch problem with security constraints

This paper presents a heuristic optimization methodology, Bacterial foraging and PSO-DE (BPSO-DE) algorithm by integrating Bacterial foraging optimization Algorithm (BFOA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) for solving Non-Convex Dynamic Economic Dispatch problem (DED). The DED problem exhibits non-convex nature due to valve-point loading effects, ramp rate limits, spinning reserve capacity and security constraints. Even though PSO and DE algorithms are proven excellent, they face solution stagnation problem due to premature convergence and stop to proceed towards global optimal solutions. The proposed method achieves global cost by selecting the bacterium with good foraging strategies. The bacteria with good foraging strategies are obtained in the updating process of every chemo-tactic step by the PSO operator and the DE operator fine tunes the solution obtained through bacterial foraging and PSO algorithm. An IEEE 39-bus, 10 unit New-England test system is considered to show the effectiveness of the proposed method over other existing methods.