Short-Term Hydrothermal Scheduling via Honey-Bee Mating Optimization Algorithm

In the present paper, a new approach for solving short-term hydrothermal scheduling problem is introduced which results in minimizing the final production cost and optimizing power generation, via honey-bee mating optimization (HBMO) algorithm. Considering the fact that in hydrothermal scheduling, a large number of constraints are involved, power balance, water balance, delay time, reservoir volume limits, and also operation limits of hydro and thermal plants; therefore, the solution for hydrothermal scheduling has turned optimization into a very complex and nonlinear problem. In this paper, the honey-bee mating optimization algorithm has been tested and analyzed on a sample system. With regard to the simulation result, it is apparent that the honey-bee mating optimization has far higher convergence speed and takes less time, and less total cost in comparison with other optimization methods such as, genetic algorithm(GA), and particle swarm optimization(PSO).