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Publishing Language: Chinese | Open Access

GrHDP-based optimization of primary frequency regulation parameters for sending-end power grid

Xinlong WU, Xiong HU, Caibo LIAO, Xing NIE, Xiaoyun YANG
School of Information Engineering, Nanchang University, Nanchang 330031, China
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Abstract

With the rapid development of high-voltage direct current (HVDC) transmission projects, the frequency regulation problem of sending-end power grids operating asynchronously with the main grid has become increasingly prominent. To coordinate the primary frequency regulation responses between sending-end hydropower units and the HVDC system, and enhance the primary frequency regulation performance of the sending-end grid, a cooperative optimization method for primary frequency regulation parameters based on goal representation heuristic dynamic programming (GrHDP) is proposed. Firstly, the power network is simplified, retaining only generator buses and HVDC converter station buses, and the HVDC system is equivalent to a synchronous generator. Then, a GrHDP network is configured for each hydropower unit and the equivalent synchronous generator. The GrHDP networks are trained under typical load disturbance conditions with a designed objective function, so as to realize the collaborative optimization of primary frequency regulation parameters for hydropower units and HVDC systems. Simulation results demonstrate that, compared with genetic algorithm and particle swarm optimization, the parameters collaboratively optimized by the GrHDP algorithm can coordinate the primary frequency regulation responses of hydropower units and HVDC systems, suppress mutual power oscillation among units, and achieve smaller frequency overshoot and shorter regulation time.

CLC number: TM731 Document code: A

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Electric Power Engineering Technology
Pages 48-57

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Cite this article:
WU X, HU X, LIAO C, et al. GrHDP-based optimization of primary frequency regulation parameters for sending-end power grid. Electric Power Engineering Technology, 2026, 45(10): 48-57. https://doi.org/10.12158/j.2096-3203.2026.10.005

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Received: 07 April 2026
Revised: 12 June 2026
Published: 30 October 2026
© After publication of the article, the authors shall own the right of signature. 2026.

The authors can use or share the published article under the Attribution-Non Commercial 4.0 International (CC BY-NC 4.0) license.