Cost optimization of a hybrid energy storage system using GAMS

By using two different energy storage systems the technical merits of both of them are exploited mostly in terms of their specific power and energy densities differences. The energy density of a battery is high but its power density is less which is opposite in the case of supercapacitor (SC). Thus, combining battery and supercapacitor the battery lifespan is prolonged which makes the system more reliable and efficient. In this paper, the battery and supercapacitor hybrid energy storage system (HESS) model is presented. The optimization of the HESS by reducing the operation costs and investment costs is necessary so that the wind/solar energy are fully utilized. The objective of the optimization is the minimization of operation and capital costs in the complete lifespan considering the constraints. In this paper, nonlinear programming (NLP) is used in General Algebraic Modelling Software (GAMS) to solve the optimization problem. The GAMS which is an effective and simple platform for optimization computations consists of a number of solvers with different algorithms. The CONOPT solver is used for solving the optimization model in this paper. The results obtained henceforth are studied and then compared with the results obtained by optimizing the HESS system with particle swarm optimization (PSO) technique. The results obtained by solving with GAMS are optimized, better and showed lesser computation time.