Control particle swarm optimization for unit commitment problem under emissions reduction

Xin Ma, Fuxiaoxuan Liang, Wenbin Wang

School of Management and Economic, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China

The control particle swarm optimization (CPSO) algorithm is introduced to solve the unit commitment problem under the background of emissions reduction. Because the standard particle swarm optimization algorithm is easy to fall into local optimal solution. The closed loop control concept and feedback mechanism of classical control theory are posited, each particle is considered as controlled object to meet the changing needs in searching process, while dynamically adjust the inertia weight by proportion-Integra-derivative (PID) controllers according to the adaptation value of each step. These strategies greatly ensure the diversity of particles and improve the global search ability of the algorithm. The simulation results show that CPSO algorithm can reduce the dimension of the problem and ensure the feasibility of the particle in the optimization process, while it also has good convergence characteristics and global search ability.