A novel Geo-spatial Clustering Tool applied to Power System Strategic Planning

Nowadays, power system strategic planning plays a significant role due to long-term ambitious goals imposed by many countries and regions. These objectives involve, amongst others, the inclusion of renewable energies in the electrical power system. Furthermore, spatial clustering methods are widely used in geography-related analyses to identify relevant areas for business decision making, especially in advanced analyses based on Geographic Information Systems (GIS). In this regard, these tools are today widely used to estimate potentials of renewable energy sources by using georeferenced information, such as solar radiation or wind speed. However, current planners consider political or electrical boundaries to perform the planning of the power system. In most cases this view seems inadequate due to the disregard and loss of geo-spatial information. This encourages the application of GIS tools to perform a regional analysis within the planning of the power system. In this paper, a new spatial distance measure is proposed to work with common spatial clustering algorithms to solve the geo-spatial clustering problem with non-spatial attributes and geographic nonoverlapping constraints. The clustering is used to achieve the optimal regional division of the power system in terms of renewable energy sources considering GIS. On this basis, the European power system is chosen to evaluate the performance of the developed tool. Results are compared with existing manually selected regions used by other strategic planning methodologies in Europe and the functional benefit is pointed out.