The study of reducing the cost of investment in wind energy based on the cat swarm optimization with high reliability

Abstract

Wind and solar are the most important source of renewable energy for power supply in remote locations involves serious consideration of the reliability of these unconventional energy sources. We apply the cat swarm meta-heuristic optimization method to solve the problem of wind power system design optimization. The electrical power components of the system are characterized by their cost, capacity and reliability. This study seeks to optimize the design of parallel power systems in which multiple choices of generators wind, transformers and lines. Our plan has the advantage of allowing electrical components with different parameters to be customized in electrical power systems. The UMGF method is applied to allow rapid reliability estimation. A computer program is developed for the UMGF application and CS algorithm. An example is provided to explain.