Abstract for:Investigating and modelling endogenous socio-economic dynamics in long-term electricity demand forecasts for rural contexts of developing countries
Long-term energy planning based on reliable electricity demand models could help to achieve the electricity access targets in rural areas of developing countries. Due to the endogenous socio-economic dynamics characterising this issue, a SD-based model to investigate such complexities and to generate long-term projections of rural electricity demand is here presented. In the conceptualisation phase, the main feedback loops of the system are captured from the literature to understand the causal and time-dependent relations between electricity demand and the multiple dimensions of socio-economic development. The structure of the model is then formulated iteratively by consulting the CEFA’s experts, an NGO which has been dealing with rural electrification in Tanzania since the 80s. The estimation of the parameters is carried out through local interviews and a calibration procedure with historical data gathered from a hydroelectric plant managed by CEFA. The result of this process is a model of 433 variables and 153 constants, which computes long-term projections of electricity demand for rural communities. The testing and validation phase is conducted by performing direct structure, structure-oriented behaviour, and behaviour pattern tests. The Theil-analysis shows that the model replicates historical data with the same trend and very low bias in the mean.