A probabilistic forecasting model for accurate estimation of PV solar and wind power generation

Wind and Solar power are the most promising and rapidly developing renewable energy technologies that exist in our world today. They are also termed variable energy resources since their natural resources, wind speed and solar irradiance, are intermittent in nature. This variability is a critical factor when estimating the annual energy of wind and solar sources. Capital and operational costs associated with their implementation are highly affected when inaccurate estimations are carried out. This paper presents a new forecasting model for solar irradiance and wind speed by utilizing historical hourly data to outline an annual eight-segment probabilistic model of wind and solar. The proposed methodology employs a probabilistic approach to estimate the hourly wind speeds and solar irradiance for a year. The model is used to estimate the annual energy produced by a 42.5 MW wind farm and a 1.5 MW PV array. The results are compared with a four-season estimation approach, which have shown a substantial improvement in the estimation accuracy of the total energy produced.