This project focuses on applying artificial intelligence to level up an existing optimization model used for electrification planning. By training a neural network with solutions generated from this model, the project aims to provide rapid, on-demand solutions for energy access planning. The process involves identifying and analyzing key variables that significantly impact universal energy access, such as geographic location, population density, energy demand, and infrastructure availability. The trained AI model will enable efficient and scalable planning, ensuring quick adaptation to varying conditions and accelerating the deployment of sustainable energy solutions.
