As the spread of new and renewable power generation facilities, the fixed investment cost CAPEX(Capital Expenditure) of solar power generation facilities decreases due to continuous technological development, and the impact of O&M costs that determine investment success has increased. For this reason, the importance of technologies such as accuracy of O&M cost calculation through ICT, failure prediction, and predictive maintenance have emerged. In the above paper, based on the cost-breakdown structure design and failure rate model design of the solar power generation facility using engineering estimation method, the maintenance cost of the solar power generation facility, which is a renewable power generation facility, is predicted and the maintenance cost used was compared and confirmed. In addition, the cost-breakdown structure and failure rate model of solar power generation facilities were designed and developed by incorporating them into a new program of economic evaluation of new and renewable power generation facilities.

Solar energy has been known as a successful alternative energy source, however it requires a large area to build power generation facilities compared to other energy sources such as nuclear power. Weather factors such as rainy weather or night time impact on solar power generation because of lack of insolation and sunshine. In addition, solar power generation is vulnerable to external elements such as changes in temperature and fine dust. There are four seasons in the Republic of Korea hereby variations of temperature, insolation and sunshine are broad. Currently factors that cause find dust are continuously flowing in to Korea from abroad. In order to build a solar power plant, a large area is required for a limited domestic land hereby selecting the optimal location for the plant that maximizes the efficiency of power generation is necessary. Therefore, this research analyze the optimal site for solar power generation plant by implementing analytic hierarchy process based on weather factors such as fine dust. In order to extract weather factors that impact on solar power generation, this work conducts a case study which includes a correlation analysis between weather information and power generation.

We studied the warming effect induced by Photovoltaic(PV) power plants in rural areas during summer daytime using a simple analytical urban meteorological model. This analysis was based on observed meteorological elements and the capacity of the PV power plant was 10 MWp. The major axis length of the PV power plant was assumed to be 1km. Data of the necessary meteorological elements were obtained from a special meteorological observation campaign established for a over a PV power plant. We assumed that the wind flowed along the major axis of the PV power plant(1 km). As a result, the air temperature on the downwind side of the PV power plant was estimated to invrease by about 0.47 °C.