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 are expected to still lack reliable and affordable electric energy 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 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 126 studies and categorisation of 84 of them, under a number of rules clearly defined in the first part of the paper. The studies are then classified 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 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 and system-dynamics 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 socioeconomic dynamics.

A high-resolution gridded dataset to assess electrification in sub-Saharan Africa

“…This is of particular relevance if the dataset is combined with gridded information on income and population to produce future scenarios of energy access and demand. As discussed in 68 , there is a need for improved data and representation of future energy demand in developing countries. The elaboration of such information in Integrated Assessment Models could substantially improve the understanding of the drivers, impacts, synergies and trade-offs between different development goals.…”

Stochastic load profile construction for the multi-tier framework for household electricity access using off-grid DC appliances

“…Limited knowledge of electricity demand can negatively impact off-grid system dimensioning. Similarly, Riva et al (2017) say that most studies do not assume a dynamic demand over the years and do not consider the evolution of the future load demand, which severely undermines long-term planning. As seen in Riva et al (2017), 74.4% of energy demand forecasting approaches adopted in the reported case studies consider no evolution in the energy demand.…”

A two-stage linear programming optimization framework for isolated hybrid microgrids in a rural context: The case study of the “El Espino” community

“…The uncertainty associated with these parameters is indeed typically referred to as "parametric uncertainty", as models are typically fed with these data in the form of exogenous parameters [9]. Riva et al [10] stress the need to introduce an appropriate modeling framework for assessing long-term projections of electricity demand within rural energy planning. In [11], the same authors conceptualize the nexus between evolution of electricity demand and local rural development, suggesting that system-dynamics can represent an appropriate method to investigate this issue from a quantitative point of view.…”