一种集成的DEA-fuzzy AHP方法,用于优先考虑印度的可再生能源
Jyoti Luhaniwal1, Shivi Agarwal2, Trilok Mathur2
1Department of Mathematics, Birla Institute of Technology and Science Pilani, Pilani Campus, Pilani, Rajasthan, 333031, India. p20200065@pilani.bits-pilani.ac.in.
Scientific reports
|January 4, 2025
概括
印度需要可再生能源 (RES) 来满足不断增长的需求和应对气候变化. 海上风力,水力和陆上风力是最有效的可再生能源,而地热是最不有效的.
科学领域:
- 能源政策与可持续发展
- 环境科学与气候变化缓解
- 运营研究和决策分析.
背景情况:
- 由于人口增长和城市化,印度面临着不断增长的能源需求,使传统能源供应受到压力.
- 可再生能源 (RES) 对印度来说至关重要,以应对能源短缺和气候变化挑战.
- 印度拥有丰富的可再生能源潜力,对其发电燃料组合的多样化至关重要.
研究的目的:
- 通过使用综合方法来评估和排名印度的各种可再生能源.
- 为印度的能源转型确定最有效的可再生能源.
- 为决策者提供一个框架来采用可再生能源.
主要方法:
- 这是一种综合方法,结合了数据包裹分析 (DEA) 和模糊分析层次过程 (Fuzzy AHP).
- 分析多个可再生能源,包括太阳能,地热,水力,生物质,波浪和风能 (陆上和海上).
- 评估基于四个关键参数:技术,经济,环境和社会政治,有19个支持标准.
主要成果:
- 海上风能表现出最高的效率,其次是水力和陆上风能.
- 在分析的可再生能源中,地热能源被列为效率最低的能源.
- 敏感性分析证实了所获得的排名的稳定性和意义.
结论:
- 综合的DEA和模糊的AHP方法提供了一个强大的框架来评估可再生能源效率.
- 海上风力,水力和陆上风力被推作为印度优先的可再生能源.
- 该方法为发展中国家和决策者提供了有价值的见解,旨在加速可再生能源的采用.
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