الفهرس 
chapter One: introductionOnly 14 pages are availabe for public view
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Abstract
Achieving sustainable energy and ending of energy poverty for everyone in 2030 is a global challenge facing mankind. Three billion people deprived of energy and 2.8 billion people utilize non-renewable solid fuels for heating and cooking. In accordance with the “Sustainable Energy for All”, it is estimated that US$1 trillion will be invested to confirm universal supply of energy by 2030. The isolated off-grid and mini-grid systems will get nearly 60% of the investment, and the corresponding goal is to double renewable energy sources.
This study presents a research in Hybrid Renewable Energy Systems (HRES) and associated issues that are conducive to this necessary investment for autonomous systems. HRES compose of more than one energy resources, at least one of them sustainable, incorporated to give more system efficiency and improve balance of power supply.
This thesis is aimed to develop a simulation program to optimize the size of a stand-alone hybrid photovoltaic/wind/battery/diesel energy system in order to minimize the levelized energy cost (LEC) and dummy energy (Edummy) supplied by the system with the maximum reliability. The model includes a wind energy model, photovoltaic (PV) model, battery storage model and a model of diesel generator (DG). An innovative computer program (CP) has been implemented utilizing real time meteorological data, like solar radiation, wind speeds, ambient temperature and the required load for 8,760 hours per year. A precise methodology for a stand-alone site in the New Valley Governorate of Egypt and many wind turbine generators (WTG) from various manufacturers in order to achieve the highest energy generation and the lowest price of the supplied energy has been presented. The wind/PV penetration ratio is changed with specific steps to supply the required load. An economic analysis model has been designed to acquire the lowest cost of the produced energy is presented.
The proposed CP has been carried out in flexibly manner using MATLAB code that is not able to be done with commercially widely used software, like HOMER. The results achieved via the proposed CP are compared with HOMER software and also that obtained via Grey Wolf Optimizer (GWO), which is one of the effective swarm intelligence algorithms inspired by the grey wolves in the nature to validate the proposed CP. Results showed the effectiveness of CP in determining the optimal size of system, in addition to the GWO is one of the most promising algorithms to achieve the optimum size for HRES due to its ability to find the optimal solution with relative simple computational requirements.