Development of a Data-Driven Techno-Economic and Environmental Framework for Solar Energy Deployment in the Energy Mix: A Case Study of Pakistan

Abstract

Numerous countries have outlined their renewable energy objectives for 2030 and 2050; however, the strategy for attaining these targets poses significant challenges. While solar energy is considered a promising solution to address the energy crisis as well as the climate change, it is essential to conduct a comprehensive evaluation of various factors before formulating any national energy policy. This study aims to utilize data-driven techno-economic and environmental optimization models to (1) analyze multiple locations simultaneously to identify the most suitable sites for solar plant deployment based on solar resources; (2) conduct a detailed techno-economic analysis (TEA) to evaluate parameters such as payback period and rate of return on investment (ROROI); and (3) formulate the country’s energy mix to meet multiple objectives and constraints. A comprehensive case study for a developing country is employed to evaluate the proposed models. Optimal sites based on solar resources are identified from a pool of 150 locations that are examined simultaneously. A 40%–70% reduction in electricity costs can be achieved by using solar energy instead of conventional grid sources. A life cycle analysis (LCA) comparing the current grid to a solar-dominant grid reveals a 41% reduction in global warming potential (GWP) when solar energy is utilized to meet national renewable energy targets for 2030. These developed models provide an efficient tool for any country, offering valuable insights to policymakers and stakeholders and facilitating the creation of sustainable energy strategies that prioritize accessibility and environmental friendliness.