Towards Sustainable Rural Electrification: Techno-Economic Feasibility Analysis & ML-Driven Distributed Energy Resource Planning

In the pursuit of achieving the world’s net zero emissions goal, we need to increase the dependency on renewable energy sources. With the rapid increase in urbanization, the gap between energy consumption and generation from rural to urban areas widens. Consequently, there is a need to set up an optimal infrastructure focusing on Distributed Energy Resources (DER) in rural areas. This study conducts a case analysis of energy consumption patterns in a representative rural village, estimating the total costs associated with generating a specified percentage of energy from DERs. The analysis also includes a payback period assessment to evaluate the economic feasibility of implementing DERs. Following the case study, we use machine learning techniques for infrastructure deployment planning. This analysis is a novel approach to identifying the optimal mix and location of DER, contributing to better policy development, rural prosperity, and increasing reliance on renewable sources.