An Enhanced hybrid particle swarm optimization and simulated annealing for practical economic dispatch

作者：Niknam Taher^*; Azizipanah Abarghooee Rasoul; Sedaghati Reza; Kavousi Fard Abdollah

来源：Energy Education Science and Technology Part A: Energy Science and Research , 2012, 30(1): 553-564.

• Economic dispatch
• Hybrid evolutionary algorithm
• PSO
• SA
• Prohibited operating zones
• Multi-fuel options
• Valve-point effects

This paper presents an effective evolutionary method for solving Economic Dispatch (ED). ED has been widely used in power system operation and planning for determination of electricity prices. In this study, some restrictions such as prohibited operating zones and valve point effects beside the multi fuel type of generation units should be taken into account in order to getting closer to the real condition of power systems. Furthermore, to ensure secure real-time power system operations, the system operator must schedule sufficient resources to meet energy demand. This problem is a complex optimization problem spontaneously which its complexity is increased with considering all above constraints. This paper presents Particle Swarm Optimization (PSO) to solve ED problem, furthermore in attempt to reduce processing time and improve the quality of solutions, particularly to avoid being trapped in local optima, PSO algorithm is mixed with Simulated Annealing (SA) algorithm. In addition, a new self adaptive mutation strategy is presented to expand the search ability of the proposed hybrid algorithm. The performance of the hybrid PSO-SA has been tested on three typical systems and compared with others in literatures. The comparison results show that the efficiency of proposed approach can reach higher quality solution and faster computational time than the conventional methods.

• 出版日期2012-10