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Dimensioning Microgrids for Productive Use of Energy in the Global South — Considering Demand Side Flexibility to Reduce the Cost of Energy (Data & Software)

Kraft, Johann ORCID iD icon 1; Luh, Matthias ORCID iD icon 2
1 Institut für Programmstrukturen und Datenorganisation (IPD), Karlsruher Institut für Technologie (KIT)
2 Institut für Prozessdatenverarbeitung und Elektronik (IPE), Karlsruher Institut für Technologie (KIT)

Abstract:

Microgrids using renewable energy sources play an important role in providing universal electricity access in rural areas in the Global South. Current methods of system dimensioning rely on stochastic load profile modeling, which has limitations in microgrids with industrial consumers due to high demand side uncertainties. In this paper, we propose an alternative approach considering demand side management during system design which we implemented using a genetic scheduling algorithm. The developed method is applied to a test case system on Idjwi Island, Democratic Republic of the Congo (DRC), which is to be powered by a micro hydropower plant (MHP) in combination with a photovoltaic (PV) system and a battery energy storage system (BESS). The results show that the increased flexibility of industrial consumers can significantly reduce the cost of electricity. Most importantly, the presented method quantifies the trade-off between electricity cost and consumer flexibility. This gives local stakeholders the ability to make an informed compromise and design an off-grid system that covers their electricity needs in the most cost-efficient way.


Zugehörige Institution(en) am KIT Institut für Programmstrukturen und Datenorganisation (IPD)
Institut für Prozessdatenverarbeitung und Elektronik (IPE)
Publikationstyp Forschungsdaten
Publikationsdatum 10.10.2022
Erstellungsdatum 20.07.2022
Identifikator KITopen-ID: 1000151341
HGF-Programm 37.12.02 (POF IV, LK 01) Design,Operation & Digitalization of the Future Energy Grids
Projektinformation GRK 2153/2 (DFG, DFG KOORD, GRK 2153/2)
Schlagwörter microgrid, off-grid system, rural electrification, optimal design, optimal dimensioning, demand side management, demand side flexibility, genetic algorithm, resource-constrained scheduling, SDG 7
Liesmich

This dataset was published as part of a paper submitted to the Special Issue "Optimal Design of Off-Grid Power Systems" MDPI Energies with the title "Dimensioning Microgrids for Productive Use of Energy in the Global South – Considering Demand Side Flexibility to Reduce the Cost of Energy".

Relationen in KITopen
URL https://git.scc.kit.edu/ipe-avt/dsm_mg_energies
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