African Journal of GIS and Spatial Analysis (Environmental/Earth Science | 10 November 2013

Bayesian Hierarchical Models for Evaluating Off-Grid Communities Systems in Rwanda: A Methodological Framework

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DOI: https://doi.org/10.5281/zenodo.18992936

Abstract

Rwanda aims to reduce off-grid communities' reliance on fossil fuels for energy by promoting renewable energy systems. This study focuses on evaluating and optimising such systems. The approach involves constructing a Bayesian hierarchical model to account for spatial variability and heterogeneity among different communities. This model will incorporate data from multiple sources including weather patterns, socio-economic factors, and energy consumption habits. The framework provides robust tools for policymakers and practitioners to optimise off-grid community solar projects, thereby enhancing energy access and sustainability. Implementing the Bayesian hierarchical model can lead to more efficient resource allocation and risk management strategies in off-grid communities across Rwanda. Model estimation used $\hat{\theta}=argmin<em>{\theta}\sum</em>i\ell(y<em>i,f</em>\theta(x<em>i))+\lambda\lVert\theta\rVert</em>2^2$, with performance evaluated using out-of-sample error.