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A nuclear heating reactor (NHR) is a typical integral pressurized water reactor (iPWR) with advanced design features such as an integral primary circuit, self-pressurization, full-power-range natural circulation, and hydraulic control rods. Through adjusting its electric power output according to the variation of demand, NHR power plants can be adopted to stablize the fluctuation of grid frequency caused by the intermittent nature of renewable generation, which is useful for deepening the penetration of renewables. The flexibility of an NHR power plant relies on the automatic generation control (AGC) function of the plant coordination control system, whose central is the AGC law. In this paper, the plant control system with AGC function is designed for NHR plants, where the AGC is realized based on the stabilizers of grid frequency and main steam pressure. Then, the AGC problem is transferred to the disturbance attenuation problem of a second-order dynamic system, and an active disturbance attenuation control (ADRC), which is just the addition of a feedback control given by a proportional‒integral (PI) law and a feedforward control driven by a disturbance observer (DO), is then proposed. Finally, this ADRC is applied to realize the AGC function for NHR-200II reactor power plant, and numerical simulation results show the implementation feasibility and satisfactory performance. Full article

Although there have been some severe nuclear accidents such as Three Mile Island (USA), Chernobyl (Ukraine) and Fukushima (Japan), nuclear fission energy is still a source of clean energy that can substitute for fossil fuels in a centralized way and in a great amount with commercial availability and economic competitiveness. Since the pressurized water reactor (PWR) is the most widely used nuclear fission reactor, its safe, stable and efficient operation is meaningful to the current rebirth of the nuclear fission energy industry. Power-level regulation is an important technique which can deeply affect the operation stability and efficiency of PWRs. Compared with the classical power-level controllers, the advanced power-level regulators could strengthen both the closed-loop stability and control performance by feeding back the internal state-variables. However, not all of the internal state variables of a PWR can be obtained directly by measurements. To implement advanced PWR power-level control law, it is necessary to develop a state-observer to reconstruct the unmeasurable state-variables. Since a PWR is naturally a complex nonlinear system with parameters varying with power-level, fuel burnup, xenon isotope production, control rod worth and etc., it is meaningful to design a nonlinear observer for the PWR with adaptability to system uncertainties. Due to this and the strong learning capability of the multi-layer perceptron (MLP) neural network, an MLP-based nonlinear adaptive observer is given for PWRs. Based upon Lyapunov stability theory, it is proved theoretically that this newly-built observer can provide bounded and convergent state-observation. This observer is then applied to the state-observation of a special PWR, i.e., the nuclear heating reactor (NHR), and numerical simulation results not only verify its feasibility but also give the relationship between the observation performance and observer parameters. Full article