Flexible operation of the pressurized water reactor nuclear power system using multi-model predictive control over a wide nonlinear operating range

The nonlinearity problem caused by the large load variation is a significant challenge for the pressurized water reactor nuclear power system (PWRNPS) to realize its flexible operation over a wide operating range when it participates in peak regulation in the power grid. Thus, this work proposes a novel multi-model predictive control (MMPC) strategy for PWRNPS to address its nonlinearity problem in multivariable control within a wide range of conditions, in which the coupling effect between the average coolant temperature and the steam turbine power is considered. Given the insufficient understanding of the nonlinearity of PWRNPS in previous work, an in-depth investigation in this regard is performed to support the control design, in which the nonlinearity of PWRNPS at the system level is analyzed both on quantitative and qualitative aspects for the first time. Considering the captured uneven nonlinearity distribution of PWRNPS, a new approach integrating hierarchical clustering with gap metric is proposed to guide the decomposition of the operating space of PWRNPS system-atically, based on which MMPC is designed to realize the nonlinearity control of PWRNPS under the large load variation. Three types of simulations demonstrate the effectiveness of the proposed methods.