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Rule-based real-time energy management system for curative congestion management in low-voltage distribution grids
Citation Link: https://doi.org/10.15480/882.18084
Publikationstyp
Journal Article
Date Issued
2026-07-27
Sprache
English
TORE-DOI
Journal
Volume
7
Issue
4
Article Number
116
Citation
Automation 7 (4): 116 (2026)
Publisher DOI
Scopus ID
Publisher
Multidisciplinary Digital Publishing Institute (MDPI)
Peer Reviewed
true
The electrification of residential demand through electric vehicles (EVs), heat pumps (HPs), photovoltaic (PV) systems, and battery energy storage systems (BESSs) creates new congestion challenges in low-voltage (LV) grids. This study evaluates a transparent, deterministic, and real-time-capable rule-based energy management system (EMS) for curative thermal congestion management within a §14a EnWG-oriented setting. The EMS is implemented in MATLAB/Simulink and tested on a representative four-feeder LV network supplying 56 households. Congestion is detected from maximum phase root-mean-square currents using conservative transformer and feeder thresholds. After a threshold is reached, the EMS first activates available BESS support and then applies simultaneous feeder-wide EV limitation, batched round-robin curtailment, or staged feeder-wide reduction toward 4.2kW. In the uncontrolled case, the Feeder 3 and transformer overload areas are 62.84Ah and 48.50Ah, respectively. All controlled scenarios remove at least 98.70% of the feeder overload and eliminate the transformer overload within the reported numerical precision. The batched strategy requires 328.54Ah of cumulative feeder-current reduction, compared with 977.34Ah for simultaneous control and 816.00Ah for staged control, and achieves the highest feeder-relief efficiency. It therefore provides a balanced trade-off between congestion relief and intervention intensity for the investigated deterministic case.
Subjects
battery energy storage systems
rule-based control
congestion management
curative congestion management
distributed energy resources
electric vehicles
low-voltage distribution networks
real-time energy management
DDC Class
621.3: Electrical Engineering, Electronic Engineering
Publication version
publishedVersion
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automation-07-00116-v2.pdf
Type
Main Article
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