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Soft-linking energy demand and optimisation models for local long-term electricity planning: An application to rural India


  • Riva, Fabio
  • Gardumi, Francesco
  • Tognollo, Annalisa
  • Colombo, Emanuela


Rural electricity plans are usually designed by relying on top-down rough and aggregated estimations of the electricity demand, which may fail to capture the real dynamics of local contexts. This study aims at soft-linking a bottom-up approach for short- and long-term forecasts of load profiles with an energy optimisation model in a more comprehensive rural energy planning procedure. The procedure is applied to a small Indian community, and it is based on three blocks: (i) a bottom-up model to project households' electrical appliances, which adopts socio-economic indicators to make long-term projections; (ii) a stochastic load profile generator, which employs correlations and users’ habits for assessing the coincidence and load factors; (ii) an energy optimisation model based on OSeMOSYS to find the economic optimum. The simulations show that demand models based on socio-economic indicators lead to more structured and less arbitrary scenarios. The soft-link with the energy optimisation model confirms that when accounting for short- and long-term variabilities of electricity demand together, the optimal capacities and costs can vary up to 144% and 50% respectively. Integrating optimisation tools to bottom-up models based on socio-economic indicators for forecasting electricity demand is therefore pivotal to set more reliable investments plans in rural electrification.

Suggested Citation

  • Riva, Fabio & Gardumi, Francesco & Tognollo, Annalisa & Colombo, Emanuela, 2019. "Soft-linking energy demand and optimisation models for local long-term electricity planning: An application to rural India," Energy, Elsevier, vol. 166(C), pages 32-46.
  • Handle: RePEc:eee:energy:v:166:y:2019:i:c:p:32-46
    DOI: 10.1016/

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