Muhammad Kamran Lodhi , Yumin Tan , Agus Suprijanto , Shahid Naeem , Isiaka Lukman Alage
{"title":"Rooftop and floating PV potential for sustainable energy in Pakistan: A national-scale assessment","authors":"Muhammad Kamran Lodhi , Yumin Tan , Agus Suprijanto , Shahid Naeem , Isiaka Lukman Alage","doi":"10.1016/j.esd.2025.101748","DOIUrl":null,"url":null,"abstract":"<div><div>Rooftop and Floating Photovoltaics (RPV and FPV) are critical renewable energy technologies for achieving net-zero societies. Understanding the exact photovoltaic potential and determining the percentage of rooftop space required to achieve solar sufficiency at a national scale are vital yet underexplored areas of research. This study evaluates the photovoltaic potential of building rooftops and inland water bodies in Pakistan, focusing on their contribution to national solar sufficiency. The research encompasses the estimation of annual rooftop solar energy potential, analysis of electricity consumption patterns, determination of the required rooftop area to achieve solar sufficiency, multicriteria decision analysis for floating PV systems, and an assessment of carbon mitigation benefits. While achieving complete self-sufficiency through rooftop PV alone may be challenging, this study provides critical data to assess its feasibility and contribution to Pakistan's energy mix. Utilizing machine learning regression and geospatial techniques, the study evaluated electricity consumption, total rooftop PV potential, the required rooftop area for solar sufficiency, and the associated carbon reduction potential at a 1 km<sup>2</sup> grid resolution. Additionally, the FPV potential was assessed at a 30-m pixel resolution. Among the evaluated models, Random Forest demonstrated the highest predictive accuracy, achieving an R-squared value of 0.92. The results reveal that Pakistan's annual electricity consumption is 132.6 TWh, while its maximum RPV and FPV potentials are 310.1 TWh and 59.23 TWh, respectively. These potentials could reduce emissions by 192.3 MtCO₂e and 36.7 MtCO₂e annually. This study further evaluates the Levelized Cost of Electricity (LCOE) for rooftop solar PV systems (1–100 kW) in Pakistan, demonstrating their economic viability. This study offers valuable insights for policymakers, investors, and researchers working to advance sustainable energy development in Pakistan.</div></div>","PeriodicalId":49209,"journal":{"name":"Energy for Sustainable Development","volume":"87 ","pages":"Article 101748"},"PeriodicalIF":4.4000,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy for Sustainable Development","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0973082625000985","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
Rooftop and Floating Photovoltaics (RPV and FPV) are critical renewable energy technologies for achieving net-zero societies. Understanding the exact photovoltaic potential and determining the percentage of rooftop space required to achieve solar sufficiency at a national scale are vital yet underexplored areas of research. This study evaluates the photovoltaic potential of building rooftops and inland water bodies in Pakistan, focusing on their contribution to national solar sufficiency. The research encompasses the estimation of annual rooftop solar energy potential, analysis of electricity consumption patterns, determination of the required rooftop area to achieve solar sufficiency, multicriteria decision analysis for floating PV systems, and an assessment of carbon mitigation benefits. While achieving complete self-sufficiency through rooftop PV alone may be challenging, this study provides critical data to assess its feasibility and contribution to Pakistan's energy mix. Utilizing machine learning regression and geospatial techniques, the study evaluated electricity consumption, total rooftop PV potential, the required rooftop area for solar sufficiency, and the associated carbon reduction potential at a 1 km2 grid resolution. Additionally, the FPV potential was assessed at a 30-m pixel resolution. Among the evaluated models, Random Forest demonstrated the highest predictive accuracy, achieving an R-squared value of 0.92. The results reveal that Pakistan's annual electricity consumption is 132.6 TWh, while its maximum RPV and FPV potentials are 310.1 TWh and 59.23 TWh, respectively. These potentials could reduce emissions by 192.3 MtCO₂e and 36.7 MtCO₂e annually. This study further evaluates the Levelized Cost of Electricity (LCOE) for rooftop solar PV systems (1–100 kW) in Pakistan, demonstrating their economic viability. This study offers valuable insights for policymakers, investors, and researchers working to advance sustainable energy development in Pakistan.
期刊介绍:
Published on behalf of the International Energy Initiative, Energy for Sustainable Development is the journal for decision makers, managers, consultants, policy makers, planners and researchers in both government and non-government organizations. It publishes original research and reviews about energy in developing countries, sustainable development, energy resources, technologies, policies and interactions.