Modeling and characterization of the impact of capacity limitation services on distribution networks

Zhe Chen, Charalampos Ziras*, Henrik W. Bindner

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Various congestion management strategies have been proposed to tackle the operational challenges arising from the widespread integration of distributed energy resources (DERs) in distribution networks. Among these strategies, capacity limitation services have recently gained significant attention. However, comprehensive analyses are essential for system operators to fully understand the impact and effectiveness of these services in distribution networks. In this study, we develop a model to represent the aggregator's response to capacity limitation services and assess their impact on network states. The proposed model, from the aggregator's perspective, consists of non-flexible baseload and controllable DERs, optimizing the aggregator's benefits based on current market conditions without accessing network states. Consequently, system operators must ensure distribution network security while facilitating flexible resources. Given the unavailability of customer privacy and the complexity of multi-period consumption behaviors, system operators concentrate on capturing aggregator behaviors during potentially risky congestion periods. Our analysis specifically aims to quantify the effects of service area coverage, power capacity limitation values, and service durations. We establish an evaluation framework to coordinate various modules by assessing these services under different scenarios. Simulation results demonstrate that the proposed model can effectively represent power consumption behavior using partially accessible information. Furthermore, we design an associated procedure to offer distribution system operators valuable insights into system behavior, empowering them to request appropriate services in anticipation of potential operational issues.
Original languageEnglish
Article number101081
JournalSustainable Energy, Grids and Networks
Volume35
Number of pages11
ISSN2352-4677
DOIs
Publication statusPublished - 2023

Keywords

  • Flexibility
  • Power system
  • Capacity limitation service
  • Congestion management
  • Electric vehicle

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