Author(s)

YanKun Li^*, Yuan Zhang, Chao Si

Affiliation(s)

Electrical Department, China Institute of Atomic Energy, Beijing 102400, China.

Corresponding Author

YanKun Li

ABSTRACT

The Reactor Protection System (RPS) of nuclear power plants requires stable operation in complex time-varying electromagnetic environments, and the shielding grounding of safety-class cables is critical for anti-interference capability. Traditional static grounding schemes (e.g., single-point, multi-point grounding) lack adaptability to interference spectrum changes, equipment aging, and dynamic operating conditions, leading to issues like false alarms and even accidental reactor trips. This paper proposes an intelligent shielding grounding optimization technology based on deep reinforcement learning (DRL). First, a multi-physics digital twin system was established, integrating key electromagnetic interference sources (e.g., main circulating pump VFD, CRDM pulses) and lifecycle aging factors (e.g., insulation aging, shielding corrosion) to characterize shielding performance attenuation. Then, the optimization problem was modeled as a Markov Decision Process (MDP) with an 18-dimensional state space and a multi-objective reward function (considering shielding effectiveness, leakage current, and cost). The Proximal Policy Optimization (PPO) algorithm was adopted to realize millisecond-level optimal grounding configuration. A four-layer safety architecture was constructed to meet nuclear safety requirements (failure probability <10^-20 per year). This technology breaks the traditional static design paradigm, providing a new path for digital and adaptive cable system optimization in nuclear power plants.

KEYWORDS

Nuclear power plant; Safety-class cable; Shielding grounding; Deep reinforcement learning; Digital twin; Electromagnetic compatibility

CITE THIS PAPER

YanKun Li, Yuan Zhang, Chao Si. Intelligent optimization technology for shielding grounding of safety-class cables in nuclear power plants based on deep reinforcement learning. World Journal of Information Technology. 2025, 3(5): 56-67. DOI: https://doi.org/10.61784/wjit3068.

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