license.txt

Abstract

Amidst the backdrop of climate change, rural electrification requires a balance between economic development, social welfare, and environmental consideration. Understanding how to optimally introduce and improve electricity coverage in under-electrified regions is a complex problem crucial to regional advancement and the climate future. This thesis applies existing machine learning and simulation techniques to model and optimize regional mini-grid development over multi-decade time frames, considering social, financial and environmental factors. The model developed is then applied to an existing under-electrified region of India to generate an optimal 30-year mini-grid development plan and analyze its dynamics.