Catalysing energy access in Africa through smarter energy storage management

通过更智能的能源存储管理促进非洲的能源获取

• 批准号: EP/R035822/1
• 负责人: David Howey
• 金额: $ 12.54万
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FR035822%2F1
• 关键词: Catalysing; energy; access; Africa; through

This project enables the remote, automated management of distributed off-grid batteries powering solar home systems throughout sub-Saharan Africa. The research has two objectives: to examine solar home system (SHS) usage data to design smarter appliances for off-grid customers; and to optimise lithium ion battery (LIB) lifetime. M-KOPA collects daily usage data from >500,000 households in sub-Saharan Africa (SSA), however, there is a gap in effective use of the data for product management and design excellence. Using data science tools and machine learning algorithms, M-KOPA will develop approaches to maximise product battery life, and design smarter appliances. These tools will decrease the premature LIB failure rate (one of M-KOPA's greatest challenges). Oxford University will design battery failure prediction algorithms to increase the longevity, effectiveness, and reliability of future LIBs for off-grid customers. Thus, this project targets all three aspects of the energy trilemma: reducing emissions through increased life of LIBs in SSA, cost savings through optimal product design, and security of energy supply from more reliable SHS.

该项目实现了对整个撒哈拉以南非洲地区为太阳能家庭系统供电的分布式离网电池的远程、自动化管理。这项研究有两个目标：检查太阳能家用系统(SHS)的使用数据，为离网客户设计更智能的电器；以及优化锂离子电池(LIB)的使用寿命。M-KOPA收集撒哈拉以南非洲(SSA)50万个家庭的日常使用数据，但在有效利用这些数据进行产品管理和卓越设计方面存在差距。M-KOPA将利用数据科学工具和机器学习算法，开发最大化产品电池寿命的方法，并设计更智能的家电。这些工具将降低LIB过早失败率(M-KOPA面临的最大挑战之一)。牛津大学将为离网客户设计电池故障预测算法，以提高未来LIBS的寿命、有效性和可靠性。因此，该项目针对能源三难困境的所有三个方面：通过延长SSA中LIB的寿命来减少排放，通过优化产品设计来节省成本，以及更可靠的SHS提供的能源供应的安全性。