Catalysing energy access in Africa through smarter energy storage management

该项目实现了对撒哈拉以南非洲地区家用太阳能系统分布式离网电池的远程自动化管理。这项研究有两个目标：检查太阳能家庭系统（SHS）的使用数据，为离网用户设计更智能的家电；优化锂离子电池（LIB）寿命。M-KOPA收集撒哈拉以南非洲（SSA） 50万户家庭的日常使用数据，然而，在有效利用数据进行产品管理和卓越设计方面存在差距。利用数据科学工具和机器学习算法，M-KOPA将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过早故障率（M-KOPA面临的最大挑战之一）。牛津大学将设计电池故障预测算法，为离网用户增加未来lib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，以及通过更可靠的SHS来保证能源供应的安全性。

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.