Coordinated Optimization Framework for Frequency Deviation Minimization in Multi-Energy Systems

Conference Paper (2026)
Author(s)

Jose Luis Rueda Torres (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Harshit Nayak (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Peter Palensky (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Research Group
Intelligent Electrical Power Grids
DOI related publication
https://doi.org/10.1109/GPECOM70462.2026.11578780 Final published version
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Publication Year
2026
Language
English
Research Group
Intelligent Electrical Power Grids
Pages (from-to)
746-751
Publisher
IEEE
ISBN (electronic)
9798331552046
Event
8th Global Power, Energy and Communication Conference, GPECOM 2026 (2026-06-03 - 2026-06-05), Naples, Italy
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Abstract

Power systems with increasing integration of power electronic converters are characterized by low inertia, limited short-circuit support, and fast dynamic behavior, making them vulnerable to active power imbalances. Under such conditions, frequency excursions and rapid change in rates of change of frequency (RoCoF) can threaten system stability. Although power electronic interfaced (PEI) units can provide fast frequency support (FFS), their uncoordinated operation may lead to inefficient or even adverse control actions. This paper proposes a coordinated optimization framework for the FFS in multi-area-energy systems incorporating MMC-based HVDC links, electrolyzers, and wind turbines. The framework optimally tunes the control actions of all participating resources to minimize frequency deviations across interconnected areas, while enabling effective sharing of active power imbalances through HVDC links. The integration of wind turbines as additional fast-acting resources is explicitly investigated, highlighting their role in improving the initial frequency response. The proposed approach is validated on a modified multi-energy HVDC system using RMS simulations in DIgSILENT PowerFactory, with the optimization problem solved by the mean-variance mapping optimization (MVMO) algorithm. Simulation results demonstrate that coordinated utilization of HVDC links, electrolyzers, and wind turbines significantly enhances frequency performance, improving RoCoF, reducing frequency nadir, and achieving better steady-state recovery under severe disturbance scenarios.

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