Modeling of nuclear reactor core for power control simulation with temperature feedback and xenon concentration effect

Bélaid Djaroum; Boussaad Mohammedi; Abderrahmane khelil Khelil; Sofiane Laouar

doi:10.57056/ajet.v8i2.125

Authors

Bélaid Djaroum Nuclear Technology Division, Nuclear Research Center of Birine, Djelfa, Algeria
Boussaad Mohammedi Nuclear Technology Division, Nuclear Research Center of Birine, Djelfa, Algeria
Abderrahmane khelil Khelil Reactor Division, Nuclear Research Center of Birine, Djelfa, Algeria
Sofiane Laouar Nuclear Technology Division, Nuclear Research Center of Birine, Djelfa, Algeria

DOI:

https://doi.org/10.57056/ajet.v8i2.125

Keywords:

Modeling, Nuclear reactor, Power control, PID, Python Algorithms

Abstract

Modeling nuclear reactor cores stands as an essential initial step in nuclear technology research and development. The reactor core, serving as the primary thermal energy source in nuclear power plants (NPPs), plays a pivotal role. Such reactor core modeling serves various objectives, including core power control and load-following operations within NPPs. In this study, the pressurized water reactor (PWR) core was modeled using the point reactor method, a technique widely applied in conjunction with multiple reactor core power control strategies during load-following operations. Employing a proportional-integral-derivative (PID) controller, load-following scenarios tailored to grid load maneuvers were implemented in the developed reactor core model. The study also delved into the effects of temperature feedback and xenon. The analysis of simulation results revealed only a very small deviation in power between the desired and actual reactor core power. A substantial movement of the control rods effectively countered the notable impact of xenon on reactor power. Regarding temperature feedback, its contribution to the core total réactivity with a negative reactivity was confirmed. This study utilized the Python language for both the development of the nuclear reactor model and the creation of algorithms required for power control during load-following mode. Typically, similar endeavors with distinct objectives are conducted using MATLAB SIMULINK.

References

Abdulraheem KK, Korolev S A. Robust optimal-integral sliding mode control for a pressurized water nuclear reactor in load following mode of operation. Annals of Nuclear Energy. 2021; 158: 108-288.

Li G, Wang X, Liang B, Li X, Zhang B, Zou Y. Modeling and control of nuclear reactor cores for electricity generation: A review of advanced technologies. Renewable and Sustainable Energy Reviews. 2016;60:116-128.

Dong Z, Cheng Z, Zhu Y, Huang X, Dong Y, Zhang Z. Review on the Recent Progress in Nuclear Plant Dynamical Modeling and Control. Energies 2023; 16: 1443.

Idrees A, Awais Z, Nadeem S, Rizwan A, Abdus S, Shakeel A. Generating function method for the solution of point reactor kinetic equations. Progress in Nuclear Energy.2020; 123 :103-286.

Silva MWD, Vilhena MT, Bodmann BEJ, Vasques R. The solution of the neutron point kinetics equation with stochastic extension: an analysis of two moments. International Nuclear Atlantic Conference – INAC. 2015.

Abdulraheem KK, Korolev SA, Laidani Z. A differentiator based second-order sliding-mode control of a pressurized water nuclear research reactor considering xenon concentration feedback. Annals of Nuclear Energy . 2021; 156: 108-193

El-Genk MS, Tournier JMP. A point kinetics model for dynamic simulations of next generation nuclear reactor. Progress in Nuclear Energy . 2016; 92: 91-103

Ismail M, Abulaban D, Genco F, Alkhedher M. Solution of the Reactor Point Neutron Kinetic Equations with Temperature Feedback Control Using MATLAB-Simulink Toolbox. 10th International Conference on Thermal Engineering: Theory and Applications February 26-28, 2017, Muscat, Oman. 2017.

Wright SA. Travis Sanchez. Dynamic Modeling and Control of Nuclear Reactors Coupled to Closed-Loop Brayton Cycle Systems using SIMULINK. Space Technology and Applications International Forum-STAIF. 2005

Mahendra Kumar JL, Abdul Majeed AP, Zakaria MA, Mohd Razman MA, Khairuddin MI. The Power Level Control of a Pressurised Water Reactor Nuclear Power Plant. InIntelligent Manufacturing and Mechatronics: Proceedings of the 2nd Symposium on Intelligent Manufacturing and Mechatronics–SympoSIMM 2019, 8 July 2019, Melaka, Malaysia 2020 (pp. 451-455). Springer Singapore.

Edwards RM, Lee KY, Ray A. Robust optimal control of nuclear reactors and power plants. Nuclear Technology. 1992; 98:137-148.

Adel BA, Edwards RM, Lee KY. LQG/LTR Robust Control of Nuclear Reactors with Improved Temperature Performance. IEEE Transactions on Nuclear Science. December 1992, 39.

Dong Z. Nonlinear Adaptive Dynamic Output-Feedback Power-Level Control of Nuclear Heating Reactors. Science and Technology of Nuclear Installations. 2013

Aab-Alibeik H, Setayeshi S. Improved Temperature Control of a PWR Nuclear Reactor Using an LQG/LTR Based Controller. IEEE Transactions on Nuclear Science. 2003; 50:211-218.

Ben-Abdennour A., Edwards R.M., Lee K.Y. LQG/LTR robust control of nuclear reactors with improved temperature performance. IEEE Trans. Nucl. Sci. 1992;39: 2286-2294

Ansarifar GR, Rafiei M. Second-order sliding-mode control for a pressurized water nuclear reactor considering the xenon concentration feedback. Nucl Eng Techno . 2015; l47: 94-101

Ansarifar GR, Rafiei M. Higher order sliding mode controller design for a research nuclear reactor considering the effect of xenon concentration during load following operation. Annals of Nuclear Energy. 2015; 75: 728–735

Mehrdad N. Khajavia, Mohammad B. Menhaj AA, Suratgar A. neural network controller for load following operation of nuclear reactors. Annals of Nuclear Energy. 2002; 29: 751–760

Park MG, Cho NZ. Time-Optimal Control of Nuclear Reactor Power with Adaptive Proportional- Integral -Feed forward Gains. IEEE Transactions on Nuclear Science. 1993; 40:266-270.

Eliasi H, Menhaj MB, Davilu H. Robust nonlinear model predictive control for a PWR nuclear power plant. Progress in Nuclear Energy. 2012; 54: 177-185

Mousakazemi SMH, Ayoobian N, Ansarifar GR. Control of the reactor core power in PWR using optimized PID controller with the real-coded GA. Annals of Nuclear Energy. 2018; 118: 107–121

Liu C, Peng JF, Zhao FY, Li C. Design and optimization of fuzzy-PID controller for the nuclear reactor power control. Nuclear Engineering and Design . 2009; 239: 2311–2316

Mousakazemi SMH, Ayoobian N, Ansarifar GR. Control of the pressurized water nuclear reactors power using optimized proportionaleintegralederivative controller with particle swarm optimization algorithm. Nuclear Engineering and Technology. 2018; 1- 9

Rahgoshaya M, Noori-Kalkhoranb O. Calculation of control rod worth and temperature reactivity coefficient of fuel and coolant with burn-up changes for VVRS-2 MWth nuclear reactor. Nuclear Engineering and Design. 2013; 256 : 322– 331

Eissa M, Naguib M, Badawi A. PWR control rods position monitoring. Annals of Nuclear Energy . 2015; 81:106–116.

Boustani E, Khoshahval F. Control rods reactivity worth calculation using deterministic and Monte Carlo approaches for an MTR type research reactor. Iranian Journal of Physics Research. 2021; 21.

Hafez N, Shahbunder H, Amin E, Elfiki SA, Abdel-Latif A. Study on criticality and reactivity coefficients of VVER-1200 reactor. Progress in Nuclear Energy. 2021; 131: 103594

Louis HK. Neutronic Analysis of the VVER-1200 under Normal Operating Conditions. Journal of Nuclear and Particle Physics 2021; 11(3): 53-66