LAPSE:2023.17182
Published Article

LAPSE:2023.17182
A Market-Driven Management Model for Renewable-Powered Undergrid Mini-Grids
March 6, 2023
Abstract
Renewable-powered “undergrid mini-grids” (UMGs) are instrumental for electrification in developing countries. An UMG can be installed under a—possibly unreliable— main grid to improve the local reliability or the main grid may “arrive” and connect to a previously isolated mini-grid. Minimising costs is key to reducing risks associated with UMG development. This article presents a novel market-logic strategy for the optimal operation of UMGs that can incorporate multiple types of controllable loads, customer smart curtailment based on reliability requirements, storage management, and exports to and imports from a main grid, which is subject to failure. The formulation results in a mixed-integer linear programming model (MILP) and assumes accurate predictions of the following uncertain parameters: grid spot prices, outages of the main grid, solar availability and demand profiles. An AC hybrid solar-battery-diesel UMG configuration from Nigeria is used as a case example, and numerical simulations are presented. The load-following (LF) and cycle-charging (CC) strategies are compared with our predictive strategy and HOMER Pro’s Predictive dispatch. Results prove the generality and adequacy of the market-logic dispatch model and help assess the relevance of outages of the main grid and of spot prices above the other uncertain input factors. Comparison results show that the proposed market-logic operation approach performs better in terms of cost minimisation, higher renewable fraction and lower diesel use with respect to the conventional LF and CC operating strategies.
Renewable-powered “undergrid mini-grids” (UMGs) are instrumental for electrification in developing countries. An UMG can be installed under a—possibly unreliable— main grid to improve the local reliability or the main grid may “arrive” and connect to a previously isolated mini-grid. Minimising costs is key to reducing risks associated with UMG development. This article presents a novel market-logic strategy for the optimal operation of UMGs that can incorporate multiple types of controllable loads, customer smart curtailment based on reliability requirements, storage management, and exports to and imports from a main grid, which is subject to failure. The formulation results in a mixed-integer linear programming model (MILP) and assumes accurate predictions of the following uncertain parameters: grid spot prices, outages of the main grid, solar availability and demand profiles. An AC hybrid solar-battery-diesel UMG configuration from Nigeria is used as a case example, and numerical simulations are presented. The load-following (LF) and cycle-charging (CC) strategies are compared with our predictive strategy and HOMER Pro’s Predictive dispatch. Results prove the generality and adequacy of the market-logic dispatch model and help assess the relevance of outages of the main grid and of spot prices above the other uncertain input factors. Comparison results show that the proposed market-logic operation approach performs better in terms of cost minimisation, higher renewable fraction and lower diesel use with respect to the conventional LF and CC operating strategies.
Record ID
Keywords
cycle charging, grid-connected micro-grids, load following, market-logic unit commitment, optimisation, predictive strategy, reliability, renewable energy sources (RES), smart curtailment, unreliable grid
Subject
Suggested Citation
González Grandón T, de Cuadra García F, Pérez-Arriaga I. A Market-Driven Management Model for Renewable-Powered Undergrid Mini-Grids. (2023). LAPSE:2023.17182
Author Affiliations
González Grandón T: Faculty of Economics, Humboldt Universität Berlin (HU), Spandauerstr. 1, 10178 Berlin, Germany [ORCID]
de Cuadra García F: Institute for Research in Technology (IIT), Comillas Pontifical University, 26 Calle de Santa Cruz de Marcenado, 28015 Madrid, Spain [ORCID]
Pérez-Arriaga I: MIT Energy Initiative, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA [ORCID]
de Cuadra García F: Institute for Research in Technology (IIT), Comillas Pontifical University, 26 Calle de Santa Cruz de Marcenado, 28015 Madrid, Spain [ORCID]
Pérez-Arriaga I: MIT Energy Initiative, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA [ORCID]
Journal Name
Energies
Volume
14
Issue
23
First Page
7881
Year
2021
Publication Date
2021-11-24
ISSN
1996-1073
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Original Submission
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PII: en14237881, Publication Type: Journal Article
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LAPSE:2023.17182
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https://doi.org/10.3390/en14237881
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Mar 6, 2023
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