Planning Decentralized Electricity Systems under Uncertain Central Grid Conditions

Electricity is forecasted to play a leading role in the final energy consumption of the future. Yet, many developing countries suffer from limited access to electricity and poor reliability of fragmented national grid infrastructure. In this context, a large body of research has investigated the development and optimization of household-level and microgrid off-grid and on-grid systems powered by a combination of various renewable and non-renewable electricity generation sources. Yet, from the perspective of the households and communities without access to a reliable central grid, investments in decentralized solutions happen under major uncertainties related to the grid existence year and the tariffs (central grid tariff and feed-in tariff). A mathematical linear programming model is formulated to model the context taking into consideration the central grid conditions. We illustrate our methodology by applying it using four scenarios to a case from Lebanon: a country that witnessed a quick drop in the centralized electricity generation due to the ongoing economic crisis accompanied by the development of various distributed improvised solutions at household and community levels. We discuss the implications of the grid uncertainties on the optimal planning for decentralized systems as witnessed in the case study from Lebanon.