机器学习为可持续发展的能源未来提供了帮助
Burcu Oral1, Ahmet Coşgun1, Aysegul Kilic1
1Department of Chemical Engineering, Boğaziçi University, 34342, Bebek-Istanbul, Turkey. yildirra@bogazici.edu.tr.
Chemical communications (Cambridge, England)
|December 20, 2024
概括
机器学习 (ML) 可以显著推进可持续能源努力和联合国可持续发展目标 (SDGs). 尽管存在诸如高能耗等挑战,但机器学习为能源生产,储存和规划提供了解决方案.
科学领域:
- 可持续能源及其与全球发展目标的交叉关系.
- 机器学习 (ML) 作为一种变革性技术的应用.
背景情况:
- 能源生产对人类活动至关重要,但也是全球变暖的主要驱动因素.
- 可持续能源对于实现大多数联合国可持续发展目标 (SDGs),特别是SDG7至关重要.
研究的目的:
- 分析机器学习 (ML) 在推动可持续能源方面的潜在作用.
- 探索ML对实现联合国可持续发展目标的贡献.
主要方法:
- 审查ML在能源生产和储存中的当前应用.
- 检查ML在能源预测和规划中的应用.
- 确定可持续能源中ML的挑战和机会.
主要成果:
- 机器学习可以通过通过监测和遥感收集数据来促进可持续能源.
- ML有助于规划全球可持续能源倡议.
- ML可以提高新型可持续能源技术的性能.
结论:
- 尽管存在诸如高能耗和可能增加的不平等等挑战,但ML为可持续能源提供了重大机会.
- 机器学习是实现可持续能源目标和更广泛的联合国可持续发展目标的关键推动因素.
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