巴基斯坦可持续能源的屋顶和浮动光伏潜力:全国范围的评估

IF 4.4 2区 工程技术 Q2 ENERGY & FUELS
Muhammad Kamran Lodhi , Yumin Tan , Agus Suprijanto , Shahid Naeem , Isiaka Lukman Alage
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引用次数: 0

摘要

屋顶和浮动光伏(RPV和FPV)是实现净零社会的关键可再生能源技术。了解确切的光伏潜力和确定在全国范围内实现太阳能充足所需的屋顶空间百分比是至关重要的,但尚未开发的研究领域。本研究评估了巴基斯坦建筑屋顶和内陆水体的光伏潜力,重点是它们对国家太阳能充足的贡献。这项研究包括每年屋顶太阳能潜力的估计、电力消耗模式的分析、实现太阳能充足所需的屋顶面积的确定、浮动光伏系统的多标准决策分析以及碳减排效益的评估。虽然仅通过屋顶光伏实现完全自给自足可能具有挑战性,但本研究为评估其可行性及其对巴基斯坦能源结构的贡献提供了关键数据。利用机器学习回归和地理空间技术,该研究评估了1平方公里网格分辨率下的电力消耗、屋顶光伏发电潜力、太阳能充足所需的屋顶面积以及相关的碳减排潜力。此外,在30米像素分辨率下评估了FPV电位。在被评估的模型中,Random Forest的预测精度最高,r平方值为0.92。结果表明,巴基斯坦年用电量为132.6 TWh,最大RPV和FPV潜力分别为310.1 TWh和59.23 TWh。这些潜力每年可减少1.923亿吨二氧化碳排放量和36.7亿吨二氧化碳排放量。本研究进一步评估了巴基斯坦屋顶太阳能光伏系统(1-100千瓦)的平电成本(LCOE),证明了其经济可行性。这项研究为致力于推动巴基斯坦可持续能源发展的政策制定者、投资者和研究人员提供了宝贵的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rooftop and floating PV potential for sustainable energy in Pakistan: A national-scale assessment
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.
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来源期刊
Energy for Sustainable Development
Energy for Sustainable Development ENERGY & FUELS-ENERGY & FUELS
CiteScore
8.10
自引率
9.10%
发文量
187
审稿时长
6-12 weeks
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.
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