Summary:
This paper addresses the problem of feeder selection in conventional under-frequency Load-Shedding (UFLS) schemes, which remain the predominant choice in large power systems due to their simplicity. These schemes rely on local under-frequency relays to disconnect feeders when predefined frequency thresholds are reached. However, the increasing integration of distributed generation (DG) and changing consumption patterns complicate the feeder selection process, leading to higher deviations from the designed load-shedding targets. Moreover, feeder selection modeling for UFLS schemes remains underdeveloped in the literature. To address these challenges, three different mixed-integer linear programming (MILP) models are proposed for feeder selection across all frequency steps. In addition, a time series aggregation (TSA)-based approach is introduced to reduce computational complexity while preserving the quality of the results. The proposed models are evaluated and compared in terms of result quality and computational performance using the key performance indicators (KPIs) introduced in this work.
Spanish layman's summary:
Este artículo propone tres modelos de optimización MILP y un método de agregación temporal para la selección de alimentadores en esquema UFLS. Aborda los retos de la generación distribuida y variabilidad del consumo, evaluando el rendimiento y calidad de resultados con nuevos indicadores.
English layman's summary:
This paper proposes three MILP models and a time series aggregation (TSA) approach for feeder selection in under-frequency load-shedding (UFLS) schemes. It addresses challenges from distributed generation, evaluating computational performance and result quality using introduced KPIs.
Keywords: Feeder selection and allocation; Under-frequency load shedding; Optimization techniques; Distributed generation
JCR-JIF Impact Factor and WoS quartile: 5,700 - Q1 (2025)
DOI reference:
https://doi.org/10.1016/j.segan.2026.102407
Published on paper: September 2026.
Published on-line: July 2026.
Citation:
O. Arenas, M. Rajabdorri, L. Sigrist, E. Lobato, L. Rouco, V. Sordo, J. Gutiérrez, A. Santamaría, "MILP-based optimization models for UFLS feeder selection", Sustainable Energy, Grids and Networks, Vol. 47, pp. 102407, September 2026. [Online: July 2026] doi: 10.1016/j.segan.2026.102407
