Application of Differential Evolution Algorithm and Its Variants for Solving Energy Storage Technologies Integrated Generation Expansion Planning

Generation expansion planning (GEP) should consider the integration of renewable energy sources (RES) and energy storage technologies (EST), along with conventional generating units so as to overcome the challenges such as uncertainties in future load growth forecasting, restrictions on investment for power generation, the type and availability of source for the generating units, environmental policy based on emission constraints and the reliability level to guarantee a continuous power. The proposed coordinated GEP-EST planning aims at minimizing the overall generation cost and environmental pollution, and at the same time, it considers large-scale ESTs. In this paper, the promising intelligent techniques such as differential evolution and self-adaptive differential evolution algorithms are applied to solve GEP-EST problem, where the power generating system of Tamil Nadu, an Indian state is taken as study system. Simulation results show that the integration of ESTs significantly reduces the overall cost and the pollutant emission. Graphical Abstract