The unit commitment problem based on an improved firefly and particle swarm optimization hybrid algorithm

In this paper, to solve the unit commitment problem economically and quickly, an improved firefly algorithm (FA) and particle swarm optimization (PSO) algorithm including both discrete and continuous parts was proposed. The starting and shutdown state of units were optimized according to using discrete binary real coded firefly algorithm. The inheritance from earlier state and constraints to later period of time for running time and shutdown time were considered in repair strategy. The continuous PSO was used in units' load dispatch after the process of deciding starting-stopping states, where constraints of power balance, unit ramp, spinning reserve and lower and upper limits were considered. Deal with the upper limits using Penalty function. To solve the constraints of power balance, zooming in the particles of each dimension variables same proportionally, and through sharing the penalty terms among particle swarms the constraints of units' ramping rates are settled. Simulation results of 10-unit and 24-hour system show that the proposed method is correct, effective and predominant.