Optimized hybrid microgrid of gas generators-wind farm using crow search algorithm

In this paper, the crow search algorithm (CSA), a novel metaheuristic method for solving constrained engineering optimization problems, is used to solve the economic dispatch (ED) and economic emission dispatch (EED) problems for Abu-Rudeis Field Power Plant (ARFPP) in Egypt, while fulfilling the local energy demand. The existing ARFPP microgrid, consisting of eleven gas generator sets, is extensively tested to evaluate the annual fuel cost and emissions with/without unit commitment. Incorporating wind farm (WF) as a renewable energy resource is proposed for upgrading ARFPP microgrid to minimize fuel consumption and reduce released oxides of nitrogen emissions (NOx) to permissible value. Taking into account the capital cost of offshore wind power systems and the average wind speed at each month of the year at Egypt's Red Sea Coast region, where ARFPP is located, the WF size is optimally estimated using CSA.