Two-stage stochastic sizing of a rural micro-grid based on stochastic load generation

Conference paper (2019)

Authors

Nicolo Stevanato Politecnico di Milano
F. Lombardi Politecnico di Milano
Emanuela Colombo Politecnico di Milano
Sergio Balderrama Sart Tilman B52
Sylvain Quoilin Katholieke Universiteit Leuven
Affiliation
External organisation
Microgrid Rural electrification Off-grid Stochastic loads Two-stage stochastic optimisation
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Published Date

2019

Language

English

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Abstract

Robust sizing of rural micro-grids is hindered by uncertainty associated with the expected load demand and its potential evolution over time. This study couples a stochastic load generation model with a two-stage stochastic micro-grid sizing model to take into account multiple probabilistic load scenarios within a single optimisation problem. As a result, the stochastic-optimal sizing of the system ensures an increased robustness to shocks in the expected load compared to a best-case (lowest-demand) sizing, though with a lower cost and better dispatch flexibility compared to a worst-case (highest-demand) sizing. What is more, allowing just a 1% unmet demand enables to significantly improve the cost-competitiveness and the renewables penetration as all the not supplied energy is located in a negligible fraction of the unlikeliest highest demand scenarios.