A multiobjective evolutionary algorithm approach for the optimum economic and environmental performance of an off-grid power system containing renewable energy sources

The optimum performance of an off-grid power system depends on economic and environmental criteria, and it belongs to the field of non-linear combinatorial multiobjective optimization. In this paper, the economic objective refers to the minimization of the total net present cost, while the environmental objective refers to the minimization of the total CO2 equivalent emissions during the life cycle of system's components, which can be wind turbines, photovoltaics, diesel generator and batteries. A binary evolutionary algorithm is proposed for the solution of the problem. The results show that in order to satisfy constraints related with system's initial cost and reliability performance, the energy supply has to be provided mainly by the diesel generator and secondarily by the wind turbines. The contribution of photovoltaics is negligible, but it can be improved significantly in the future through the evolution of their manufacturing procedure, which is expected to cause reduction in their cost and their total CO2 emissions.