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Unsupervised Profiling of Operator Macro-Behaviour in the Italian Ancillary Service Market via Stability-Driven k-Means

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Listed:
  • Mahmood Hosseini Imani

    (Department of Energy, Politecnico di Torino, 10129 Torino, Italy)

  • Atefeh Khalili Param

    (Department of Energy, Politecnico di Torino, 10129 Torino, Italy)

Abstract

The transition toward sustainability in the electric power sector, driven by increasingly renewable integration, has amplified the need to understand complex market dynamics. This study addresses a critical gap in the existing literature by presenting a systematic and reproducible methodology for profiling generating-unit operators’ macro-behaviour in the Italian Ancillary Services market (MSD). Focusing on the Northern zone (NORD) during the pivotal period of 2022–2024, a stability-driven k-means clustering framework is applied to a dataset of capacity-normalized features from the day-ahead market (MGP), intraday market (MI), and MSD. The number of clusters is determined using the Gap Statistic with a 1-SE criterion and validated with bootstrap stability (Adjusted Rand Index), resulting in a robust and reproducible 13-group taxonomy. The use of up-to-date data (2022–2024) enabled a unique investigation into post-2021 market phenomena, including the effects of geopolitical events and extreme price volatility. The findings reveal clear operator-coherent archetypes ranging from units that mainly trade in the day-ahead market to specialists that monetize flexibility in the MSD. The analysis further highlights the dominance of thermoelectric and dispatchable hydro technologies in providing ancillary services, while illustrating varying degrees of responsiveness to price signals. The proposed taxonomy offers regulators and policymakers a practical tool to identify inefficiencies, monitor concentration risks, and inform future market design and policy decisions.

Suggested Citation

  • Mahmood Hosseini Imani & Atefeh Khalili Param, 2025. "Unsupervised Profiling of Operator Macro-Behaviour in the Italian Ancillary Service Market via Stability-Driven k-Means," Energies, MDPI, vol. 18(20), pages 1-34, October.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:20:p:5446-:d:1772231
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    References listed on IDEAS

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    1. Huang, Chunyi & Li, Kangping & Zhang, Ning, 2025. "Strategic joint bidding and pricing of load aggregators in day-ahead demand response market," Applied Energy, Elsevier, vol. 377(PC).
    2. Diego Andreotti & Matteo Spiller & Andrea Scrocca & Filippo Bovera & Giuliano Rancilio, 2024. "Modeling and Analysis of BESS Operations in Electricity Markets: Prediction and Strategies for Day-Ahead and Continuous Intra-Day Markets," Sustainability, MDPI, vol. 16(18), pages 1-35, September.
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