A multiple-model based internal model control method for power control of small pressurized water reactors. (1st November 2020)

• Record Type: Journal Article
• Authors: Wang, Pengfei; Chen, Zhi; Liao, Longtao; Wan, Jiashuang; Wu, Shifa
• Is Part Of: Energy. Volume 210(2020)
• Publication Date: 2020-11-01
• Subjects: Small pressurized water reactor -- Reactor power control system -- Internal model control -- Multiple model approach -- Multi-objective genetic algorithm; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2020.118527
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Small pressurized water reactors (PWRs) usually have variable operating conditions and complex operating environments. It is significant to design a robust control system to ensure stable and satisfactory reactor power maneuvers under large uncertainties. This paper purposes a multiple-model based internal model control (IMC) method for power control of small PWRs. Six local transfer function models are first developed from a nonlinear reactor core model over the entire operating range. Then, six local power controllers are designed for a small PWR based on these local models using the IMC scheme. The IMC filter time constant is determined by the genetic algorithm based multi-objective optimization to keep good balance between the control performance and cost. The local controllers are connected by a probability-weighted multiple model approach to generate a global IMC system for the reactor. Dynamic simulation results of the small PWR under the IMC scheme as well as performance assessments of the IMC scheme against the PID control scheme during typical transient operations have shown good reference tracking performances and strong disturbance rejection capabilities of the multiple-model based IMC system, demonstrating the feasibility and effectiveness of the proposed method for the power control of small PWRs. Highlights: Internal model controllers are designed at six power levels in the entire operating range of the reactor. IMC filter time constant is optimized by the NSGA-II algorithm to keep good balance between control performance and cost. The local controllers are connected by a probability-weighted multiple model approach to generate a global IMC system. The multiple-model based IMC method can guarantee satisfactory control performances for small PWRs under large uncertainties.