The paper considers a modelling framework for a set of households in residential areas; using electricity as a form of energy for domestic consumption. Considering the demand and availability of units for electricity consumption, optimal decisions for electricity load allocation are paramount to sustain energy management. We formulate this problem as a stochastic decision-making process model where electricity demand is characterized by Markovian demand. The loading and operational framework is governed by the demand and supply phenomena; where shortage costs are realized when demand exceeds supply. Empirical data for electricity consumption was collected from fifty households in two residential areas within the suburbs of Kampala in Uganda. Data collection was made at hourly intervals over a period of four months. The major problem focussed on determining an optimal electricity loading decision in order to minimize consumption costs as demand changes from one state to another. Considering a multi-period planning horizon, an optimal decision was determined for loading or not loading additional electricity units using the Markov decision process approach. The model was tested; whose results demonstrated the existence of an optimal state-dependent decision and consumption costs considering the case study used in this study. The proposed model can be cost-effective for managers in the electricity industry. Improved efficiency and utilization of resources for the distribution systems of electricity to residential areas was realized; with subsequent enhanced reliability of service to essential customers of the energy market.