The production of solar power plants has impact on the power system operations more and more nowadays. According to predictions, the number of PV systems will increase in the future, and the costs of solar power plants will continue to decrease.
Because of the stochastic behavior it is important to monitor the electricity generation, and to analyze data of production, irradiance and other weather conditions. Factors which influence the production, for example global irradiance and temperature, are also appropriate to be used for solar forecasting. The PV prediction is extremely important, it can provide useful information for power system operators, and increase the efficiency of power regulation for customers.
Although exceptionally high gradient values are currently only experienced during solar eclipse, it will change in the future: the same gradient values will be measured at normal weather conditions.
The thesis is about the impact of global, direct, diffuse irradiances and the temperature on solar production, introduction and use of forecasting methods, and the effect of the partial solar eclipse on 20 March, 2015. The most important result is the intraday prediction using multiple linear regression method. The RMS error of the estimation of the two power plants was very low, 5,12% and 1,48%. Comparison of the solar eclipse day with a cloudy day in March, whose large scale change of production occurred in the similar part of the day, was also performed. Gradient values, the delay of the production, and the global, direct and diffuse irradiance were compared to highlight the relevant differences.