Power Distribution Laws Modeling of Wind Power and Solar Stations

Abstract

Despite the obvious advantages of renewable and alternative energy sources (RAES) the main unresolved problem is the issue of the variability of the generated capacity of these power plants. It is difficult for energy system operators to determine how much per unit of time RAES are ready to provide capacity and energy. It does not allow considering such sources as full-fledged participants in power and electricity market. It is a big obstacle to investment in renewable energy projects. At the same time, the generated power of these stations depends on the natural conditions at a particular geographic point, the level of wind speed and solar insolation. The patterns of these parameters depend on the time of year, locality and are purely probabilistic in nature. The research purpose is to build distribution law models that can describe not only the data of solar insolation and wind speed, but also the RAES generated power. This goal has been achieved by methods of estimating the distribution law parameters and testing statistical hypotheses. The most important result is the identification of the basic distribution laws describing the probabilities of solar insolation and wind speed. For the considering area the laws of the 3rd kind beta distributions family and their mixtures better describe these data than the widespread Weibull's law. The same laws are applicable to RAES generated power. It allows to estimate the share of renewable energy in the total energy systems more accurately and helps system operators to predict output power of RAES.

Keywords

• probability distribution laws
• a
• output power probability distribution