Abstract
One of the criteria for measuring household energy poverty is the percentage of the
household’s income spent on energy expenses. In this work, an autonomous income-based energy
scheduling Demand Side Management (DSM) technique called Energy Expenditure Affordability Algorithm
(EEAA) is proposed to ensure that household energy expenditure is below nation’s approved energy
expenditure threshold. The EEAA problem was formulated as a Mixed Integer Linear Programming (MILP)
problem and verified with real household data. Consumer preferences and satisfaction were enhanced
by using Dynamic Time Warping (DTW) technique to minimize the distance between nominal and EEAA
load profiles. Furthermore, the effect of Distributed Energy Generation (DEG) and Distributed
Energy Storage (DES) were also investigated in the light of energy expenditure affordability for
improved consumer-friendly and satisfying DSM. The EEAA- DSM technique is shown to reduce household
energy expenditure below the energy expenditure threshold, offer energy expenditure affordability
and utility grid Peak Demand Reduction (PDR). Also, grid reliability and sustainability,
environmental preservation and gendered energy poverty are consequential benefits of the EEAA. It
also offered the households considered an average financial savings from 12% to 82% depending on
the level of implementation of distributed storage and generation to the consumer’s local energy
mix.