Classification of Regions by Climatic Characteristics for the Use of Renewable Energy Sources

The transition from fossil fuels to "green" energy involves increasing energy efficiency from existing energy systems and reducing harmful emissions into the atmosphere. Currently, renewable energy sources (RESs) are a priority way of generating energy for Smart Grid systems that meet the requirements of efficiency and safety. Classification of regions by similar climatic characteristics helps as an effective tool for avoiding various risks when implementing a Smart Grid based on RES. In this paper, the clustering method is considered by the authors as a tool to achieve the goal of the study: the division of regions into clusters with similar climatic characteristics, which will allow to choose the most efficient RES for each specific region. The authors considered the selected climatic characteristics based on certain factors after a review of existing sources, for example, the level of solar insolation, average annual wind speed, average annual temperature, and average annual precipitation for 84 subjects of the Russian Federation. As a result, five clusters were identified by the k-means method using the Stata software. For each cluster, the characteristics and the most preferred type of RES for the implementation of Smart Grid are described. Cluster analysis based on climatic characteristics is the first stage of a comprehensive methodology for selecting the most favorable regions for the development of both a particular type of RES and Smart Grid systems in general, as proposed by the authors.