人工智能驱动生物质加工的进步:对转换技术,优化策略和智能能源整合的审查
Riddhi Garg1, Prachi Rajput1, Jayesh Vibhandik1
1Department of Chemical Engineering, Birla Institute of Technology and Science, Pilani, Hyderabad Campus, Jawahar Nagar, Kapra Mandal, Medchal District, Hyderabad 500078, Telangana, India.
ACS omega
|November 3, 2025
概括
人工智能 (AI) 优化了燃料效率和生物质转化为可持续能源. 在能源交易中整合人工智能也提供了经济和生态的好处,尽管数据隐私等挑战.
科学领域:
- 能源科学 能源科学
- 人工智能的人工智能
- 生物质转化技术生物质转化技术
背景情况:
- 人们越来越担心环境退化和对化石燃料的依赖.
- 需要可持续的能源解决方案来减轻气候变化影响.
研究的目的:
- 探索人工智能 (AI) 在提高燃油效率和生物质转化方面的革命性潜力.
- 总结人工智能在优化生物质转换参数的应用,以增加能源生产和减少排放.
主要方法:
- 对应于燃料电池和生物质系统的AI模型 (例如,支向量机,神经网络) 的审查.
- 分析人工智能在优化各种生物质转化技术 (无氧消化,气化,热解,酶性水解,化) 中的作用.
主要成果:
- 人工智能优化了生物质转换的参数,增强了能源输出并最大限度地减少了排放.
- 人工智能工具在能源交易市场中促进了高效的物流和分散的能源生产.
- 人工智能集成带来了诸多挑战,包括数据隐私,算法偏见和合规问题.
结论:
- 人工智能增强型能源系统为应对全球可持续性挑战提供了一个有希望的途径.
- 整体的人工智能框架可以带来强大的,高效的能源基础设施,减少资源效率低下.
- 人工智能在能源领域的整合需要仔细考虑道德和实际挑战.
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