Behind the Meter: End-User Flexibility for Congestion Mitigation

An Agent-Based Exploration of Residential Behavior and Measures for Low-Voltage Congestion Relief

Master Thesis (2025)
Author(s)

P.J. Treanor (TU Delft - Technology, Policy and Management)

Contributor(s)

C.N. Van Der Wal – Mentor (TU Delft - System Engineering)

I Bouwmans – Mentor (TU Delft - Energy and Industry)

Faculty
Technology, Policy and Management
More Info
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Publication Year
2025
Language
English
Graduation Date
07-07-2025
Awarding Institution
Delft University of Technology
Programme
['Complex Systems Engineering and Management (CoSEM)']
Faculty
Technology, Policy and Management
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Abstract

The energy transition is creating congestion on the low-voltage electricity grid, threatening reliability and slowing sustainable development. To address this, Distribution System Operators (DSOs) are turning to household flexibility measures. However, most current approaches assume households behave uniformly, overlooking important behavioral differences.

This thesis uses an Agent-Based Model to simulate five household profiles (Conscientious Individuals, Structure Seekers, Status-Driven, Responsibles, and Self-Developers) and their participation in three flexibility measures: smart EV charging, solar PV curtailment, and flexible heat pump control. Awareness campaigns are included as a soft intervention. Profiles and parameters were informed by literature and interviews with Dutch DSOs. Scenarios reflect current conditions and two future policy paths, including the planned abolition of net metering.

Results show large differences in participation across profiles. Conscientious Individuals and Responsibles adopt early, while Status-Driven households are least likely to engage. Summer feed-in peaks can be fully mitigated in ideal conditions, but reducing winter peaks proves more difficult due to limited uptake of heat pump flexibility.

The study shows that behavioral segmentation adds critical value to energy modeling. Targeted engagement strategies based on user profiles can help DSOs design more effective, inclusive flexibility programs, aligning grid stability efforts with real-world household behavior.

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