الفهرس 
Optimized hybrid microgrid of gas generators-wind farm using crow search algorithm
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Abstract
The objectives of presented thesis are to solve the economic dispatch (ED) and economic emission dispatch (EED) problems to optimize the fuel consumption rate of the existing isolated microgrid of AbuRudeis field power plant (ARFPP) located in Egypt’s red sea coast region using the crow search algorithm (CSA). CSA is a novel meta-heuristic method for solving constrained engineering optimization problems while constraining it to fulfill 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, the WF size is optimally estimated using CSA. To highlight the superiority of applying CSA, the function (fmincon) via MATLAB environment is used to extensively validate all results obtained using CSA. Based on such comparative results, it is evident that CSA gives promising results compared with fmincon