A novel imperialistic competitive algorithm for unit commitment with wind generation

Abstract

The integration of wind power to the grid is essential to meet the growing power demand and possess a challenge to unit commitment to meet the load demand at low cost for scheduling the generating units. A new imperialistic competitive algorithm (ICA) has been developed for the above mentioned unit commitment problem for solving deterministic and stochastic condition. This imperialistic competitive algorithm has been developed with constraints, including generation limits, start up and shut down cost, minimum up and downtime along with ramp constraint. The ICA has been studied initially on the 10 units 24 hour system and 40 units 24 hour system for the deterministic load. Later, a wind generator has been added to the 10 units 24 hour system with wind data for 24 hours and the results are compared with genetic algorithm (GA), particle swarm optimization (PSO), hybrid particle swarm optimisation (HPSO), shuffled frog leaping algorithm (SFLA), invasive weed optimization (IWO). The comparison result is presented in this paper and it shows that the ICA gives optimized fuel cost of $482246.2 which is less than the LR, GA, BFOA, SFLA, IWO for stochastic unit commitment.