Robust nonlinear model predictive control for nuclear power plants in load following operations with bounded xenon oscillations

One of the important operations in nuclear power plants is load-following in which imbalance of axial power distribution induces xenon oscillations. These oscillations must be maintained within acceptable limits otherwise the nuclear power plant could become unstable. Therefore, bounded xenon oscillation considered to be a constraint for the load-following operation. In this paper, a robust nonlinear model predictive control for the load-following operation problem is proposed that ensures xenon oscillations are kept bounded within acceptable limits. The proposed controller uses constant axial offset (AO) strategy to maintain xenon oscillations to be bounded. The constant AO is a robust state constraint for load-following problem. The controller imposes restricted state constraints on the predicted trajectory during optimization which guarantees robust satisfaction of state constraints without restoring to a min–max optimization problem. Simulation results show that the proposed controller for the load-following operation is so effective so that the xenon oscillations kept bounded in the given region.

Research highlights▶ In this work, a robust nonlinear model predictive control algorithm is developed. ▶ This algorithm is applied to control the power level for load following. ▶ The state constraints are imposed on the predicted trajectory during optimization. ▶ The xenon oscillations are the main constraint for the load following problem. ▶ In this algorithm, xenon oscillations are bounded within acceptable limits.