Grey Wolf Optimizer for RES Capacity Factor Maximization at the Placement Planning Stage

At the current stage of integration renewable energy sources into power systems many countries, requirements for compliance with established technical characteristics are being applied to generation. One such requirement is installed capacity utilization factor, which extremely important optimally placing facilities based on and successful development energy. Efficient placement maximizes factor a facility, increasing efficiency payback period. The depends assumed meteorological factors relating geographical location However, cannot be accurately predicted, since it necessary know volume electricity produced by facility. A novel approach optimization source plants their forecasting was proposed in this article. This combines machine learning algorithm (random forest regressor) metaheuristic (grey wolf optimizer). Although assumes use only open-source data, simulations show better results than commonly used algorithms, as random search, particle swarm optimizer, firefly algorithm.