Forecast of photovoltaic generation in isolated rural areas of Ecuador using Holt-Winters and seasonal variation methods

Due to the shortage of electric power in isolated rural areas of Ecuador, implementing a photovoltaic power generation system is an optimal, viable, and sustainable alternative that can reduce the gap in electric power coverage in the nation. However, since the geographical location of a possible PV system implementation directly affects its optimal performance, it is essential to propose generation forecasting algorithms that use actual data from the place under study. For this reason, this paper compares Holt-Winters and Seasonal Variation forecasting methods applied to two rural locations in Ecuador. These methods use historical records of meteorological conditions such as solar irradiation and ambient temperature to achieve a short-term forecast of photovoltaic generation. Percentage errors obtained in the forecast power and the Pearson correlation coefficient are calculated as performance measures. The results show that although both algorithms have similar characteristics when getting the photovoltaic generation prediction, the Holt-Winters method presents improved behavior.