Hybrid bare-bones PSO for dynamic economic dispatch with valve-point effects

•A new PSO-based hybrid algorithm is presented to solve dynamic economic dispatch problems with valve-point effects.•An improved bare-bones PSO and a directionally chaotic search are well combined to achieve better performance.•An adaptive disturbance factor and a new genetic operator are incorporated into the improved BBPSO.•An effective constraint handing mechanism is introduced to solve complicated equality and inequality constraints.•The proposed algorithm shows good performance to solve the DED problem.

This paper presents an efficient hybrid particle swarm optimization algorithm to solve dynamic economic dispatch problems with valve-point effects, by integrating an improved bare-bones particle swarm optimization (BBPSO) with a local searcher called directionally chaotic search (DCS). The improved BBPSO is designed as a basic level search, which can give a good direction to optimal regions, while DCS is used as a fine-tuning operator to locate optimal solution. And an adaptive disturbance factor and a new genetic operator are also incorporated into the improved BBPSO to enhance its search capability. Moreover, a heuristic handing mechanism for constraints is introduced to modify infeasible particles. Finally, the proposed algorithm is applied to the 5-, 10-, 30-unit-test power systems and several numerical functions, and a comparative study is carried out with other existing methods. Results clarify the significance of the proposed algorithm and verify its performance.

Graphical abstractA new genetic operator by integrating the mutation and the crossover operators, called the M+C operator, where a genetic probability pe is used to control the recombination speed among particles. In the 8-th line, when G  (0, 1) takes a small value, like the crossover operator in an evolutionary algorithm, crossing with random Pbestlk can help a particle to construct good schemas rapidly; when G(0, 1) takes a big value, like the mutation operator, the value of G(0, 1) × rang can help the particle to escape from local optima.Figure optionsDownload full-size imageDownload as PowerPoint slide