对基于人工智能的可解释的包装工业能源管理的支持技术的观点
Daniel Gutierrez-Rojas1, Arun Narayanan1, Cássia R Santos Nunes Almeida1,2
1School of Energy Systems, Lappeenranta-Lahti University of Technology, Yliopistonkatu 34, 53850 Lappeenranta, South Karelia, Finland.
iScience
|December 11, 2023
概括
本研究探讨了工业能源管理系统的信息和通信技术. 它的重点是利用人工智能和智能电网优化可再生能源的使用,以提高效率和可持续性.
科学领域:
- 工业能源管理 工业能源管理
- 信息和通信技术信息和通信技术
- 可再生能源系统可再生能源系统
背景情况:
- 由于风能和太阳能等可再生能源的间歇性,工业能源管理面临着挑战.
- 可再生能源的有效整合需要先进的信息和通信技术 (ICT) 来实现最佳的资源配置和电网稳定性.
- 网络物理系统为开发复杂的工业能源管理解决方案提供了一个框架.
研究的目的:
- 审查建立强大的工业能源管理系统所必需的关键ICT.
- 引入软件定义的能源网络,以优化工业网络物理系统中的能源配置.
- 为在工业环境中高效,可持续地管理可再生能源提供框架.
主要方法:
- 制定能源管理作为一个动态调度问题,以分钟级的时间尺度来匹配供需.
- 将储能单元纳入调度模型.
- 详细探索人工智能 (AI),网络数据,需求侧管理,机器类型通信和能源意识的调度.
主要成果:
- 确定有效的工业能源管理系统的关键ICT组件.
- 展示人工智能和智能电网技术,以实现最佳的能源资源配置.
- 提出了一个框架,以平衡工业能源需求与可再生能源的变化和环境目标.
结论:
- 有效的工业能源管理依赖于集成先进的ICT,包括AI和软件定义网络.
- 动态调度和需求侧管理对于处理间歇性可再生能源至关重要.
- 拟议的框架支持工业能源实践中提高效率和环境可持续性.
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