Rule-based real-time energy management system for curative congestion management in low-voltage distribution grids

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.

Content

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

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https://creativecommons.org/licenses/by/4.0/

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publishedVersion

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automation-07-00116-v2.pdf

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Main Article

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2.01 MB

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