الفهرس 
1. INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
Electrification of rural or isolated areas, where the extension of the electrical grid is too expensive, usually relies on a diesel generator as a single electric source, however fossil fuel has many drawbacks such as greenhouse gas emissions, unavailability, and price fluctuations. Moreover, due to the advantage of clean nature and sustainability of renewable energy source, it is usually used side by side with batteries and Diesel generator leading to technical and economic challenges in designing a hybrid microgrid. Therefore, this thesis discusses the optimal sizing of isolated hybrid microgrid, which consists of distributed renewable energy resources (photovoltaics and wind turbines), diesel generation, and energy storage system (batteries), to obtain the best economic, technical and environmental indices.
The mathematical modeling and control strategy of the proposed isolated hybrid microgrid components have been implemented using MATLAB. Furthermore, our case study is based on the Zafrana area, a site located on the eastern coast of Egypt. Two topologies with different renewable sources have been considered in this study where the area is once supplied by PV/Diesel/Battery and another time is supplied by PV/WIND/Diesel/Battery. Moreover, a multi objective function based on Annual System Cost (ASC), Fuel cost, CO2 emissions and technical penalty functions such as Loss of Power Supply Probability, and Excess Energy Ratio and Fraction renewable has been incorporated. In this thesis, a new optimization algorithm, namely Turbulence Flow of Water Optimizer (TFWO), claimed to be used for the first time in sizing the hybrid renewable isolated microgrid. Results are compared to four well-known optimizers, namely Harris Hawks Optimization Algorithm (HHO), Whale Optimization Algorithm (WOA), Jellyfish Search Optimizer (JSO), and Equilibrium Optimizer (EO), to validate the superiority of the proposed algorithm.
Case study 1 (PV/Diesel/Battery) results show that TFWO has better convergence and accuracy than other algorithms, while adhering to the required technical and environmental constraint values. The Fuel cost is reduced by 71.6% compared to the case where the whole load is supplied by a single Diesel generator and consequently, the CO2 emissions are reduced as well. The carried sensitivity analysis shows that the obtained optimized microgrid guarantees that LPSP is maintained less than 1.1% in all the sensitivity cases, even with load increase by 25%. Although the ASC and fuel cost increase to compensate for load increase, irradiation decrease, or Diesel generator efficiency decrease, the FR% in all cases is maintained higher than 59.7% (the optimized FR% is 73.77%).
Moreover, in case study 2 (PV/WIND/Diesel/Battery), the TFWO results still have the best convergence and accuracy compared to the other used optimization algorithms. Here the Fuel cost is reduced by 70.9% compared to the case where the whole load is supplied by a single Diesel generator and consequently, the CO2 emissions are reduced. Although the fuel cost in this case is slightly higher than case study 1 (2.3% increase), the ASC of case study 2 is 3.9 % less than Case study 1. The sensitivity analysis carried out shows that the obtained optimized microgrid guarantees that LPSP is maintained less than 1.32% in all the sensitivity cases, even with load increase by 25%. The ASC and fuel cost may increase to compensate for load increase, wind speed decrease, irradiation decrease, or Diesel generator efficiency decrease, but the FR% in all cases is maintained higher than 59.3% (the optimized FR% is 73.09%).