Optimizing the economic dispatch of weakly-connected mini-grids under uncertainty using joint chance constraints

Submission Status:under review
  • In this paper, we deal with a renewable-powered mini-grid, connected to an unreliable main grid, in a Joint Chance Constrained (JCC) programming setting. In many countries with low energy access rates, grid-connected mini-grid system operators contend with four different types of uncertainties: stochastic solar power and demand forecast errors; absolute uncertain national grid outage onset times; and outages duration subjected to statistical analysis. These uncertainties pose new challenges to the classical power system’s operation tasks. Two alternatives to the JCC problem are presented. In particular, we present an Individual Chance Constraint (ICC) and a purely deterministic dispatch model. The JCC model has the capability to address all four uncertainties, while the ICC covers only three of them, overlooking the uncertainty about the outage duration. In contrast, the purely deterministic model completely ignores any uncertain parameters. We illustrate the three models through a comparison of outcomes attained from a real mini-grid in Lake Victoria, Tanzania. Results show how the dispatch is modified across the models to plan the battery and diesel reserves in the chance-constrained models, with the reserves in the JCC being larger than in the ICC model. In comparison between all models, we prove that the JCC model offers the most robust results, since it can handle uncertainties about forecasting errors, on the one hand, and grid outages, on the other. The results also show that the decrease in profits due to the hedging with reserves kept in the MG is significantly small compared to the high level of reliability reached and the potential load shedding that could be avoided in the case of an outage.

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Metadaten
Author:Nesrine Ouanes, Tatiana González Grandón, Holger Heitsch, René Henrion
Document Type:Article
Language:English
Date of Publication (online):2023/09/01
Date of first Publication:2023/09/01
Release Date:2023/09/04
Institutes:Weierstraß-Institut für Angewandte Analysis und Stochastik
Subprojects:B04
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International
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