Comprehensive Assessment of Technological Challenges In Photovoltaic Waste Recovery In India Using Principal Component Analysis and Analytic Hierarchy Process Models

IF 4.4 4区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Dinesh Yadav, Sanjeev Kumar, Prabhu Paramasivam, Praveen Kumar Kanti, Rupesh Gupta, Mohamed Yusuf
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Abstract

The rapid expansion of photovoltaic (PV) technology has raised concerns about sustainable PV waste management, particularly in India, where inadequate infrastructure and technical limitations hinder effective recycling. Addressing these challenges is crucial for minimizing environmental risks and promoting a circular economy in the renewable energy sector. This study presents a smart multi-criteria decision-making (MCDM) approach that integrates Principal Component Analysis (PCA) and the Analytic Hierarchy Process (AHP) to assess technological challenges in PV waste management. PCA is applied to prioritize key challenges, while AHP evaluated their interrelationships through criteria weights. Despite the effectiveness of PCA and AHP, their combined application in PV waste recovery remains underexplored, particularly in the Indian context. Eight key challenges are identified, with hazardous recycling methods (83.2%) and low recycling potential (83.4%) ranking highest in PCA. AHP results highlighted the lack of advanced recycling technology (0.2298) and hazardous recycling methods (0.2084) as the most critical barriers. A multi-criteria utility function is developed to illustrate these interdependencies. This research bridges critical knowledge gaps by offering data-driven insights into PV waste recovery in India, contributing to sustainable waste management strategies and the development of an efficient recycling framework.

Abstract Image

利用主成分分析和层次分析法模型全面评估印度光伏废物回收的技术挑战
光伏(PV)技术的迅速发展引起了人们对可持续光伏废物管理的关注,特别是在基础设施不足和技术限制阻碍有效回收的印度。解决这些挑战对于最大限度地降低环境风险和促进可再生能源领域的循环经济至关重要。本研究提出了一种智能多标准决策(MCDM)方法,该方法集成了主成分分析(PCA)和层次分析法(AHP),以评估光伏废弃物管理中的技术挑战。PCA被应用于确定关键挑战的优先级,而AHP通过标准权重评估它们之间的相互关系。尽管PCA和AHP有效,但它们在光伏废弃物回收中的联合应用仍未得到充分探索,特别是在印度的情况下。确定了八个关键挑战,其中危险回收方法(83.2%)和低回收潜力(83.4%)在PCA中排名最高。AHP结果显示,先进回收技术的缺乏(0.2298)和危险回收方法(0.2084)是最关键的障碍。开发了一个多标准实用程序函数来说明这些相互依赖关系。这项研究通过提供数据驱动的见解来了解印度的光伏废物回收,为可持续废物管理战略和高效回收框架的发展做出贡献,从而弥合了关键的知识差距。
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来源期刊
Global Challenges
Global Challenges MULTIDISCIPLINARY SCIENCES-
CiteScore
8.70
自引率
0.00%
发文量
79
审稿时长
16 weeks
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