Power flow based hydro-thermal-wind scheduling of hybrid power system using sine cosine algorithm

Abstract

Different types of optimization techniques are being applied in hydrothermal scheduling (HTS) problem for optimizing fuel cost, emission and combined cost emission. Usage of fossil fuel for thermal power generation increases global warming and environment pollution. In this work, environment friendly, clean energy such as wind energy, has been integrated with the HTS problem to overcome the effect of thermal pollution and to reduce generation cost. A novel sine cosine algorithm (SCA) has been implemented to minimize generation cost and fuel emission. The different control parameters of the SCA have been properly utilized to balance the exploration and the exploitation phases leading to find out near global optimal solution. To study its performance and efficiency, SCA has been applied to solve different cases (i.e., economic load scheduling, economic emission scheduling, combined economic emission scheduling) of HTS and hydrothermal wind scheduling (HTWS) problems. Furthermore, optimal power flow (OPF) based HTWS is studied for a standard 9-bus system. Results offered by some newly surfaced algorithms (like teaching learning-based optimization, gravitational search algorithm, real-coded genetic algorithm etc.) have been compared with those offered by the SCA to establish its effectiveness. Utility of wind energy in scheduling problem has been proposed in this work.