Embedding nuclear physics rules and fuel chemistry limits in control algorithms for a fuel-efficient nuclear reactor

Das, Shantanu; Biswas, B.B.

doi:10.1504/ijngee.2007.014672

Cited by 2 publications

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“…In such cases, there is no thermal loop taking part in power controls, like power reactors of Canadian Deuterium Uranium (CANDU) type, PWR and Boiling Water Reactor (BWR) type etc. For small research reactors the idea is to govern the basic neutronics only, as done conventionally by ON-OFF controls of the control rods, looking at only the linear neutron channel signal [37], [38]. But for power reactors unlike research reactors have a loop of thermal-hydraulics and thus control inputs from these parts to affect the reactivity.…”

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confidence: 99%

Fractional order fuzzy control of nuclear reactor power with thermal-hydraulic effects in the presence of random network induced delay and sensor noise having long range dependence

Das

Pan

Das

2013

Energy Conversion and Management

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Nonlinear state space modeling of a nuclear reactor has been done for the purpose of controlling its global power in load following mode. The nonlinear state space model has been linearized at different percentage of reactor powers and a novel fractional order (FO) fuzzy proportional integral derivative (PID) controller is designed using real coded Genetic Algorithm (GA) to control the reactor power level at various operating conditions. The effectiveness of using the fuzzy FOPID controller over conventional fuzzy PID controllers has been shown with numerical simulations. The controllers tuned with the highest power models are shown to work well at other operating conditions as well; over the lowest power model based design and hence are robust with respect to the changes in nuclear reactor operating power levels. This paper also analyzes the degradation of nuclear reactor power signal due to network induced random delays in shared communication network and due to sensor noise while being fed-back to the Reactor Regulating System (RRS). The effect of long range dependence (LRD) which is a practical consideration for the stochastic processes like network induced delay and sensor noise has been tackled by optimum tuning of FO fuzzy PID controllers using GA, while also taking the operating point shift into consideration.Keywords: fractional order fuzzy PID controller; long-range dependence; network induced stochastic delay; nuclear reactor thermal-hydraulics; power level control; antipersistent noise.The Point kinetics equation based nonlinear model of a 500 MW nuclear reactor is derived in this paper, taking into account the thermal effects on reactivity. The nonlinear state space is linearized around the steady state operating conditions corresponding to the various operating powers of the nuclear reactor. The parameters of the FO fuzzy PID controllers are then tuned with these linearized models to obtain a trade-off design between good set point tracking and reduced controller effort. The fuzzy FOPID controllers tuned with the linearized models of the reactor at highest/lowest power shows good set-point tracking ability though the system's dc-gain changes due to change in the range of operation. Similar multiple model based control scheme for nuclear reactors has been proposed by Hu et al. [23] and the mathematical model for the guidance of control rod movement is proposed by Alireza and Shirazi [24].Evaluation of the performance of nuclear reactor control systems over communication networks is being a big concern now-a-days because a small amount of stochastic delay is capable of destabilizing a well-tuned control loop as shown by Pan et al. [25]. Das et al. [26] have given experimental evidence of the impact of the presence of network in the control of nuclear reactors. Therefore, the possible random delays and the packet dropouts which occur during long distance transmission of signal from the sensors to the controller or from the controller to the actuator must be considered in the controller design phase i...

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confidence: 99%

Fractional order fuzzy control of nuclear reactor power with thermal-hydraulic effects in the presence of random network induced delay and sensor noise having long range dependence

Das

Pan

Das

2013

Energy Conversion and Management

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“…The set-point of the RRS is specified at the desired level, which is called the demand power and the control loop error is corrected by the continuous measurement of the reactor power level or bulk power by the Self-PoweredNeutron-Detectors (SPND). So, the goal of the reactor control system is to minimize the effective power error (EPE) which is the sum of the difference between demand power and bulk power and the difference between their instantaneous rates [20], [21]. The present RRS in operating PHWRs uses proportional controller as described in [20], [21].…”

Section: Reactor Model Developmentmentioning

confidence: 99%

“…So, the goal of the reactor control system is to minimize the effective power error (EPE) which is the sum of the difference between demand power and bulk power and the difference between their instantaneous rates [20], [21]. The present RRS in operating PHWRs uses proportional controller as described in [20], [21]. Now, in order to identify the test PHWR from test data along with its power regulator in loop ( Fig.…”

Section: Reactor Model Developmentmentioning

confidence: 99%

“…In the present study, model reduction in NIOPTD-I and NIOPTD-II templates are attempted with the minimization of the 2 H -norm of the identified and the fractional order NIOPTD models (20)- (21). The 2 H norm of a system reflects how much it amplifies or attenuates its inputs over all the frequencies.…”

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confidence: 99%

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Fractional Order Modeling of a PHWR Under Step-Back Condition and Control of Its Global Power With a Robust ${\rm PI}^{\lambda} {\rm D} ^{\mu}$ Controller

Das

Gupta

2011

IEEE Trans. Nucl. Sci.

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Abstract-Bulk reduction of reactor power within a small finite time interval under abnormal conditions is referred to as step-back. In this paper, a 500MWe Canadian Deuterium Uranium (CANDU) type Pressurized Heavy Water Reactor (PHWR) is modeled using few variants of Least Square Estimator (LSE) from practical test data under a control rod drop scenario in order to design a control system to achieve a dead-beat response during a stepped reduction of its global power. A new fractional order (FO) model reduction technique is attempted which increases the parametric robustness of the control loop due to lesser modeling error and ensures iso-damped closed loop response with a PI λ D μ or FOPID controller. Such a controller can, therefore, be used to achieve active step-back under varying load conditions for which the system dynamics change significantly. For closed loop active control of the reduced FO reactor models, the PI λ D μ controller is shown to perform better than the classical integer order PID controllers and present operating Reactor Regulating System (RRS) due to its robustness against shift in system parameters.

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Embedding nuclear physics rules and fuel chemistry limits in control algorithms for a fuel-efficient nuclear reactor

Cited by 2 publications

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Fractional order fuzzy control of nuclear reactor power with thermal-hydraulic effects in the presence of random network induced delay and sensor noise having long range dependence

Fractional order fuzzy control of nuclear reactor power with thermal-hydraulic effects in the presence of random network induced delay and sensor noise having long range dependence

Fractional Order Modeling of a PHWR Under Step-Back Condition and Control of Its Global Power With a Robust ${\rm PI}^{\lambda} {\rm D} ^{\mu}$ Controller

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