For a large and recently increasing number of households, affordability is a major hurdle in accessing sufficient electricity and avoiding service disconnections. For such households, in-home energy rationing, i.e. the need to actively prioritize how to use a limited amount of electricity, is an everyday reality. In this project, we consider a particularly vulnerable group of customers, namely prepaid electricity customers, who are required to pay for their electricity a-priori. With this group of customers in mind, we propose an optimization-based energy management framework to effectively use a limited budget and avoid the disruptions and fees associated with disconnections.
The framework considers forecasts of future use and knowledge of appliance power ratings and user-defined load priorities, to solve an optimization problem to find a threshold in terms of $ for each load. When the balance goes below the threshold, the corresponding load is disabled preserving the remaining balance for higher priority loads. This helps customers prioritize and limit use of low-priority loads, with the goal of extending access to their critical loads. The proposed management system has minimal requirements in terms of in-home hardware and remote communication, and can lend itself well to adoption across different regions and utility programs.
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