Modeling Residential Load Growth for Off-Grid Communities: A Case Study of the Faza Mini-Grid in Kenya

Abstract

Mini-grids are among the key solutions in providing energy access in off-grid rural communities. In this context, accurate demand forecasting is critical for designing cost-effective and reliable systems. Yet existing models often overlook evolving energy demand driven by appliance adoption and socio-economic growth, including the emergence of new income-generating activities. To address this gap, this study employs historical appliance adoption data and diffusion projections from a mini-grid in Kenya to formulate multiyear load demands with RAMP, and evaluates system sizing and dispatch strategies with Microgrid-sPy. Furthermore, a RAMP-based algorithm is developed to enable probabilistic allocation of appliance ownership, reflecting real-world household diversity. The results provide a demand growth projection of the residential sector, including household enterprises, over a period of 20 years. The proposed methodology and results contribute to increasing understanding of demand evolution in comparable contexts, and can inform planning strategies, such as phased capacity expansion.