Solving Optimal Unit Commitment by Improved Honey Bee Mating Optimization

Improved version of Honey Bee Mating Optimization (IHBMO) algorithm is developed and applied for Unit Commitment Problem (UCP) in this paper. Actually, the optimal solution of the nonlinear scheduling problem is important and it has complex computational optimization process. This problem is a challenging undertaking to accommodate variations in the power system, especially when several thermal units are employed. IHBMO technique is a hybrid evolutionary algorithm which combines the power of genetic algorithms and simulated annealing with a fast problem specific local search heuristic to obtain the best possible solution. To demonstrate the effectiveness and robustness of the proposed algorithm a system with ten thermal units in various conditions is considered. The simulation results are compared with those obtained from traditional unit commitment and heuristic algorithms.