Modelling financing schemes for energy system planning: a mini-grid case study

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Abstract

Energy modeling has been playing a crucial role in defining solutions for effective energy planning. Bottom-up energy system planning models, namely those models characterized by high technological detail, typically present exogenous techno-economic parameters which rely on data gathered by the user, from specific costs to efficiencies. However, poor to no attention has been given to the date to the financial parameters of energy models, which are often assumed and barely justified (e.g., “discount rate equal to 10%”, full stop). Still, model outputs are drastically sensitive to variations of finance-related parameters and must provide the financing structure that a decision-maker should implement for funding the advised energy planning strategies. This results particularly crucial for mini-grid sizing in sub-Saharan African countries, where the challenge of the energy transition entails the construction of massive new capacities to improve energy access rates and tiers of service, demanding an enhanced collaboration between private and public sectors. The case study, applied on an off-grid mini-grid in Mozambique, proposes a comparison between scenarios with increasing financial detail and a possible conceptualization of the hard link between detailed financial modelling and a bottom-up energy model for mini-grid optimization. Different financing schemes are modelled and their impact on the energy modelling outputs assessed. Project finance hence emerges as a useful approach that could upgrade the financing structure of domestic power projects in African countries. This may lead to many benefits: more sustainable and affordable interest rates where corporate finance is missing, improved risk management, diversified funding mix, and facilitated financial support from international institutions.

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APA

Crevani, G., Soares, C., & Colombo, E. (2023). Modelling financing schemes for energy system planning: a mini-grid case study. In 36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, ECOS 2023 (pp. 1958–1969). International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems. https://doi.org/10.52202/069564-0178

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