Spatio-temporal Correlation Analysis of Wind Speed and Sunlight for Predicting Power Generation in Jeju

Due to the oil crisis and the insecurity of nuclear energy, the exploitation of renewable energy has attracted researchers’ attentions recently. In particular, to charge electric power in smart grid cities, it is important to integrate multiple renewable energy sources efficiently. Unlike the existing energy sources, the renewable energy sources such as wind and solar have low availability because they are uncontrollable. Thus, in order to make stable and predictable electric power generation, many forecasting models have been proposed. This paper examines whether there is any spatio-temporal correlation between wind speed and sunlight, which is not considered by the existing forecasting models for predicting power generation. To achieve this research objective, we categorize and analyze Jeju weather data by regions and seasons. Through the analysis, we show how wind and solar can complement each other. We expect that our analysis scheme can be used as a basis for predicting power generation in smart grid cities where multiple renewable energy sources are combined together.