Advances in long-term solar energy prediction and project risk assessment methodology

In this article, we present a state-of-the-art longtern energy prediction methodology to minimize risk in the project investment. We applied the algorithm to the SolarAnywhere data over 19 years period. he algorithm systematically creates synthetic years from the period of dataset to draw distribution that best describes the data. We conducted the experiment for projects under different climatic conditions. We compared the result with several theoretical distribution models. The results show that the method is so robust that it can predict the real production data at a site with high level of accuracy and provide confidence in the investment.