Development of Decision Support System for Solar Farm Location on CPEC using GIS and Forecasting

Abstract

Due to the increasing expansion of renewable energy sources, it is essential to use effective decision-making techniques when picking ideal places for solar farms. This research uses geographic information systems (GIS) and forecasting methods to offer a decision support system (DSS) for identifying solar farm locations along the China-Pakistan Economic Corridor (CPEC). Helping stakeholders, decisionmakers, and investors locate the best locations for solar farm projects inside the CPEC region is the goal. In order to examine numerous spatial and non-spatial elements that affect the feasibility of solar farms, the proposed DSS uses GIS technology. The DSS also uses forecasting techniques to determine the potential for future solar energy production. It is possible to anticipate sun irradiation levels using historical weather data and meteorological projections, which enables precise estimation of solar farm output. By incorporating forecasting methods, decision-making is improved, resulting in the selection of sites with high solar energy potential and a decreased chance of underperformance. Stakeholders can effectively interact with the proposed DSS thanks to its user-friendly interface. It simplifies data entry, analysis, and visualization, enabling users to explore multiple scenarios and assess the influence of various factors on the choice of solar farm placement. The use of the decision support system for identifying solar farm locations
on the CPEC will aid in the region's continued sustainable development of renewable energy sources.