الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
Recently, renewable energy sources have great significance and contracted to be more and more interesting for the numerous reasons. Among these reasons, they are considered environment friendly, green, safe and sustainable power sources. The main obstacle of fossil fuel is its negative effect on the environment; therefore alternative clean resources are used, renewable energy sources (RESs) gained great attention in the last years. The renewable energy is expected to open a new avenue to overcome the lack of fossil fuels availability. Solar energy is one of the suggested solutions to overcome these problems due to its wide availability and its cleanliness. The air pollution is a situation that affects all the countries in the world. As a result, many nations put more attention to renewable energies (solar energy). But research in this area face two challenges: finding a beneficial model to distinguish the solar cells and the lack of data about photovoltaic cells. various methods have been offered to estimate the parameters of the photovoltaic (PV) cells. Most of them try to find the optimal solutions, but their results are inaccurate in some cases. This thesis proposes two techniques for efficiently and accurately estimating the parameters of solar cells and PV modules: The Improve Equilibrium optimizer Algorithm (IEO) and Manta ray foraging optimization (MRFO) algorithm. And the results that obtained by proposes two technique show that the obtained parameters are the optimal values and with the least difference between the measured and the calculated data compared with other algorithms.