Enabling electricity access in developing countries: A probabilistic weather driven house based approach

Meeting the growing electricity demand in many developing countries is a major challenge as there is a shortage in power generation. This paper proposes a novel strategy for mitigating the effect of weather intermittency on the scheduling power interruption of residential houses. The proposed method involves optimal scheduling strategy for the electricity supply of these houses in a distribution grid and weather temperature prediction using a probability paper plot is deployed. Data training is achieved through the Monte-Carlo Simulation, and the prediction model is validated through error analysis. Using this method, novel power interruption schedules, based on maximizing houses’ accessibility to electricity and considering consumers’ fairness of accessing electricity services on hourly basis, have been designed. The design considers two optimization problems, scheduling electricity supply and validating the schedule in the power distribution grid by ensuring no violations of grid operational requirements. Moreover, a sensitivity analysis has been conducted to investigate the effect of scaling up the demand from the house context on enabling electricity access to such houses. The effect of conservative voltage reduction schemes on energy consumption reduction has also been explored. The studied results demonstrate the effectiveness of the proposed method in enabling electricity access of new regions accommodated in the grid by up to 47.6% which increases the profit of the power utility from residential electricity bill payments.