Long-term energy planning and demand forecast in remote areas of developing countries: Classification of case studies and insights from a modelling perspective

Abstract

More than half a billion people will still lack reliable and affordable electricity in 2040 and around 1.8 billion may remain reliant on traditional solid biomass for cooking. Long-term energy planning could help to achieve the energy access targets in developing countries, especially in remote rural areas.Different studies exist on long-term rural electricity and thermal energy planning, but the different foci, terminology and methodologies make it difficult to track their similarities, weaknesses and strengths. With this work, we aim at providing a critical analysis of peer-reviewed studies on long-term rural energy planning, to help researchers in the field move across the diverse know-how developed in the last decades.The work resulted in the analysis of 130 studies and categorisation of 85 of them that focus on electricity, thermal energy, and oil supply in rural areas, under a number of rules clearly defined in the first part of the paper. We classify the studies in two consecutive steps, first according to their type and afterwards according to the methodology they employ to forecast the energy demand, which is one the most critical aspects when dealing with long-term rural energy planning.The work also provides specific insights, useful to researchers interested in rural energy modelling. Few studies assume a dynamic demand over the years and most of them do not consider any evolution of the future energy load, or forecast its growth through arbitrary trends and scenarios. This however undermines the relevance of the results for the purpose of long-term planning and highlights the necessity of further developing the forecasting methodologies. We conclude that bottom-up approaches, system-dynamics and agent-based models seem appropriate approaches to forecast the evolution of the demand for energy in the long-term; we analyse their potential capability to tackle the context-specific complexities of rural areas and the nexus causalities among energy and socio-economic dynamics.