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A review of congestion management methods for power distribution networks: Current practices and future challenges

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  • Mehmood, Khawaja Khalid
  • Moura, Ranier Alexsander Arruda
  • Molen, Anne van der
  • Tonkoski, Reinaldo
  • Tzscheutschler, Peter
  • Wielen, Peter van der
  • Nguyen, Phuong Hong

Abstract

The increasing volume of connection requests for load and generation is putting pressure on the limited grid capacity of distribution networks (DNs), resulting in growing waiting lists. Consequently, distribution system operators (DSOs) are seeking fast and effective congestion management (CM) strategies to reduce delays and enable timely customer connections. In this paper, we present a comprehensive review of CM methods for DNs to assist DSOs in addressing this challenge. By taking into account the severity of customer impact, we categorize existing CM methods into four groups: (1) DSO-owned technical solutions, (2) tariff- and flexible contract-based solutions, (3) DSO-procured market-based solutions, and (4) DSO-direct interventions. Within DSO-owned solutions, we provide an in-depth review of network reinforcement and equipment control-based solutions. Next, we examine tariff and flexible contract-based solutions, including time-of-use (TOU) tariffs, TOU tariffs with incentives, dynamic tariffs and non-firm capacity contracts. The DSO-procured market-based solutions cover research on various market designs aimed at addressing congestion issues. Finally, we review DSO-direct interventions as last-resort approaches for CM. Additionally, we analyze research studies that propose underlying mathematical methods for CM, categorizing them into three groups: (1) deterministic analysis, (2) stochastic analysis, and (3) machine learning-based methods. For each study, we highlight key contributions along with our reflections on its applicability. For the most relevant methods, we also present simulation results to validate their working principles. Finally, we highlight future challenges in CM, offering insights for DSOs and researchers in developing effective CM solutions.

Suggested Citation

  • Mehmood, Khawaja Khalid & Moura, Ranier Alexsander Arruda & Molen, Anne van der & Tonkoski, Reinaldo & Tzscheutschler, Peter & Wielen, Peter van der & Nguyen, Phuong Hong, 2026. "A review of congestion management methods for power distribution networks: Current practices and future challenges," Applied Energy, Elsevier, vol. 407(C).
  • Handle: RePEc:eee:appene:v:407:y:2026:i:c:s0306261925020720
    DOI: 10.1016/j.apenergy.2025.127342
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    References listed on IDEAS

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    1. Hennig, Roman J. & de Vries, Laurens J. & Tindemans, Simon H., 2023. "Congestion management in electricity distribution networks: Smart tariffs, local markets and direct control," Utilities Policy, Elsevier, vol. 85(C).
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    3. Hennig, Roman J. & de Vries, Laurens J. & Tindemans, Simon H., 2024. "Risk vs. restriction—An investigation of capacity-limitation based congestion management in electric distribution grids," Energy Policy, Elsevier, vol. 186(C).
    4. Sultana, Beenish & Mustafa, M.W. & Sultana, U. & Bhatti, Abdul Rauf, 2016. "Review on reliability improvement and power loss reduction in distribution system via network reconfiguration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 297-310.
    5. de Lima, Tayenne Dias & Lezama, Fernando & Soares, João & Franco, John F. & Vale, Zita, 2024. "Modern distribution system expansion planning considering new market designs: Review and future directions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 202(C).
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    7. Koirala, Arpan & Van Acker, Tom & D’hulst, Reinhilde & Van Hertem, Dirk, 2022. "Hosting capacity of photovoltaic systems in low voltage distribution systems: A benchmark of deterministic and stochastic approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
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