DOI: 10.36347/sjet

Pages: 244-251

This paper presents a sinusoidal migration of biogeography based optimization for solving short term hydrothermal scheduling (STHTS) problem. This is one of the complex and hard to solve problems in power system field due to its nonlinear, dynamic, non-separable and nonconvex nature. Biogeography based optimization (BBO) is a powerful optimization technique, originated on the subject of biological species distribution. A mathematical formulation of the sinusoidal model of biogeography based optimization (SMBBO) is described and how biological species survive from one habitat to another habitat and gets annihilated. The proposed SMBBO approach is found to be accurate, robust, reliable and has ability to circumvent from local optima. This SMBBO approach is validated on a test system consisting of cascaded nine hydroelectric plants and an equivalent thermal plant with and without valve point loading effect. The simulation results show that the proposed approach is providing better results in terms of minimum cost and computational time as compared to linear migration model of BBO, particle swarm optimization (PSO), differential evolution (DE) and genetic algorithm (GA).