Multi-Objective Optimal Power Flow of Integrated Renewable Systems Using a Novel Evolutionary Algorithm

This chapter introduces an approach to explain optimal power flow (OPF) for stochastic wind and conventional thermal power generators-based system. In this chapter, grasshopper optimization algorithm (GOA) is implemented to efficiently prove its superiority for solving wind-based OPF problem. Diminishing carbon emissions is a significant goal for the entire world; a tremendous penetration of unpredictable wind energy can assist in reducing emissions. In the previous decade, the access of renewable energy opening for energy production has improved significantly. WE has become an important source that has begun to be used for energy all over the world in recent years. The optimal dispatch between thermal and wind units to minimize the total generating costs and emission are considered as multi-objective (MO) model. In MO optimization, whole electrical energy generation costs and burning emissions are concurrently minimized. The performance of aforesaid approach is exercised and it proves itself as a superior technique as compared to other algorithms revealed in the literature.