Identification and assessment of sites for solar farms development using GIS and density based clustering technique- A case of Pakistan

Abstract

Site selection plays a vital role in the entire life cycle of solar farm and merits further consideration. Current studies for the site selection have several limitations. First, application of criteria related to infrastructure in the initial phase can screen out prospective solar farms or make them less desirable. Second, infrastructure criteria are less significant in circumstances where new cities and town are to be planned. Lastly, clustering is often ignored in site selection problem to classify farms and determine their sizes. To overcome these limitations, this study proposes a methodology that focuses primarily on areas that has maximum energy potential and excludes the infrastructure requirements initially from the analysis. The methodology uses Geographical Information System (GIS) for data acquisition and mapping, whereas a novel density-based clustering approach is employed to identify and group sites with high solar potential. The methodology is applied to the geographic boundaries of Pakistan. However, the methodology can be applied to any spatial context subject to the availability of similar data. The paper concludes with recommendations to energy policy makers by providing a list of potential clusters, with their sizes ranging between 10−289km2 located in the Baluchistan province of Pakistan.