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A secure and reliable supply of energy is important for economic stability and even in social life. Increasing human population, industrialization, and rising living standards lead to increased electrical energy demand. Uncertainties in oil prices, shortage of fossil fuel reserves, and environmental pollution from conventional fuels leads solar energy as an alternative resource for electricity production. The share of installed photovoltaic (PV) capacity as a percent of total installed power generating capacity is increasing every year. In this study, an improved methodology to design large-scale PV power plant is proposed. The proposed methodology is performed for designing optimal configurations of PV power plants. The design methodology is performed using commercially available PV modules and inverters. In addition, solar radiation, ambient temperature, wind speed, shadow effect, and location and shape of plant field are taken into consideration as input parameters. The alternatives and parameters are evaluated with the purpose of minimizing the levelized cost of generated electricity (LCOE). The methodology includes the use of a genetic algorithm (GA) for determining the optimal number of PV modules and inverters, optimum tilt angle of PV modules, required installation area for the plant and optimum cable cross section and lengths. In the paper, the methodology is implemented, and case studies and results using pvsyst software for the same case studies are compared with each other.

In recent years, sustainable and clean renewable energy resources are widely used instead of fossil fuel energy resources in electrical energy generation systems. Especially, wind and solar energy conversion systems are utilized together in stand-alone systems. In this study, reliability analysis of a hybrid system installed in Davutpasa Campus of Yildiz Technical University is investigated. The system includes a wind turbine, PV panels, a hybrid charge regulator, a MPPT charge controller, an inverter, battery group and loads. Reliability indexes are calculated for analyzed system. The obtained results are examined and presented in this paper.

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This study presents a numerical approach to calculate the optimum photovoltaic (PV) tilt angle by considering the three different PV technologies (monocrystalline, polycrystalline, and thin film). This analysis focuses on determination of optimum tilt angle considering seasonal and yearly solar radiation on a plane (Wh/m2) and seasonal and yearly energy production (Wh) of PVs. The angle at maximum global radiation and maximum energy output is considered as the optimum tilt angle. It is found that optimum tilt angles obtained by total radiation and total energy output are different from each other considering seasonal and yearly base. Total radiation-based tilt angle results show that the optimum tilt angle is 13 deg in spring, 9 deg in summer, 17 deg in autumn, 12 deg in winter, and 12 deg as yearly. Energy production-based optimum tilt angles vary from 5 deg to 13 deg for monocrystalline, from 11 deg to 15 deg for polycrystalline, and from 12 deg to 25 deg for thin film technology according to seasonal and yearly tilt angle results.