• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4685-4694
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• 2023

The ability to calculate the material density sensitivity coefficients of power with respect to the material density has broad application prospects for accelerating Monte Carlo-Thermal Hydraulics iterations. The second-order material density sensitivity coefficients for the general Monte Carlo score have been derived based on the differential operator sampling method in this paper, and the calculation of the sensitivity coefficients of cell power scores with respect to the material density has been realized in continuous-energy Monte Carlo code RMC. Based on the power-density sensitivity coefficients, the sensitivity coefficients of power scores to some other physical quantities, such as power-boron concentration coefficients and power-temperature coefficients considering only the thermal expansion, were subsequently calculated. The effectiveness of the proposed method is demonstrated in the power-density coefficients problems of the pressurized water reactor (PWR) moderator and the heat pipe reactor (HPR) reflectors. The calculations were carried out using RMC and the ENDF/B-VII.1 neutron nuclear data. It is shown that the calculated sensitivity coefficients can be used to predict the power scores accurately over a wide range of boron concentration of the PWR moderator and a wide range of temperature of HPR reflectors.

• Proceedings of the KIEE Conference
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• summer
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• pp.345-347
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• 2004

In small signal stability analysis of power systems, eigenvalue analysis is the most useful method and the detailed modeling of generator has an important effect to the eigenvalues. Generator full model is used for precise dynamic analysis of generators and controllers while two-axis model is used for multi-machine systems because of the reduced order of the state matrix. Also, the eigenvalue sensitivity coefficients are used for optimizing controller parameters to improve system stability. This paper compare the first and second order eigenvalue sensitivity coefficients of controllers using generator full model with those of two-axis model. As a result of an example, the estimated eigenvalues using the first and the second eigenvalue sensitivity coefficients using generator full model is very close to those of state matrix. Also the error ratios throughout a wide range of controller parameters is less than $1\%$.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.119-121
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• 2003

In small signal stability analysis of power systems, eigenvalue analysis is the most useful method and the detailed modeling of generator gives an important effect to the eigenvalues. Generator full model is used for precise dynamic analysis of generators and controllers while two-axis model is used for multimachine systems because of the reduced order of the state matrix. Also, the eigenvalue sensitivity coefficients are used for optimization of controller parameters to improve system stability. This paper compare the first order eigenvalue sensitivity coefficients of controllers in case of generator full model with those of two-axis model. As a result of an example the estimated eigenvalues using sensitivity coefficients in case of generator full model is very close to those of state matrix within 1% error ratios.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.3
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• pp.363-368
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• 2008

In this paper, the Resistive Companion Form(RCF) analysis method is applied to analyze small signal stability of power systems including thyristor controlled FACTS equipments such as SVC. The eigenvalue sensitivity analysis algorithm in discrete systems based on the RCF analysis method is presented and applied to the power system including SVC. As a result of simulation, the RCF analysis method is proved very effective to precisely calculate the variations of eigenvalues or newly generated unstable oscillation modes after periodic switching operations of SVC. Also the eigenvalue sensitivity analysis method based on the RCF analysis method enabled to precisely calculate eigenvalue sensitivity coefficients of controller parameters about the dominant oscillation mode after periodic switching operations in discrete systems. These simulation results are different from those of the conventional continuous system analysis method such as the state space equation and proved that the RCF analysis method is very effective to analyze the discrete power systems including periodically operated switching equipments such as SVC.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.12
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• pp.193-200
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• 2010

In this paper, the eigenvalue sensitivity analysis is calculated in the power system which is including both generator controllers such as Exciter, PSS and thyristor controlled FACTS devices in transmission lines such as TCSC. Exciter and PSS are continuously operating controllers but TCSC has a switching device which operates non-continuously. To analyze both continuous and non-continuous operating equipments, the RCF method one of the numerical analysis method in discrete time domain is applied using discrete models of the power system. Also the eigenvalue sensitivity calculation algorithm using state transition equations in discrete time domain is devised and applied to a sampled system. As a result of simulation, the eigenvalue sensitivity coefficients calculated using discrete system models in discrete time domain are changed periodically and showed different values compared to those of continuous system model in time domain by the effect of periodic switching operations of TCSC.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.644-645
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• 2007

In this paper, the eigenvalue sensitivity analysis algorithm in discrete systems by the RCF method are presented and applied to the power system including TCSC. The RCF analysis method enabled to precisely calculate eigenvalue sensitivity coefficients of dominant oscillation modes after periodic switching operations. These simulation results are very different from those of the conventional continuous system analysis method such as the state space equation method

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.237-238
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• 2008

In this paper, the RCF method is applied to analyze small signal stability of power systems including thyristor controlled FACTS equipments such as TCSC. The eigenvalue sensitivity analysis algorithm in discrete systems by the RCF method are presented and applied to the power system including TCSC. The RCF analysis method enabled to precisely calculate eigenvalue sensitivity coefficients of dominant oscillation modes after periodic switching operations. These simulation results are very different from those of the conventional continuous system analysis method such as the state space equation method.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.33 no.9
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• pp.364-371
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• 1984

This paper describes a method for the state estimation in electric power system. The state values are estimated through the weighted least square method considering the bad data. Then, the bad data are identified by using sensitivity coefficients of power system after being detected the bad data through the distribution of T. This method was applied to the model power system, and, the results of test for proposed method are given.

• Journal of Power System Engineering
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• v.5 no.4
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• pp.82-89
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• 2001

To design a structural or a mechanical system with the best performance, the main procedure of a typical design usually consists of repeated modifications of design parameters and the investigation of the system response for each set of these parameters. But this procedure requires much time, effort and experience. Sensitivity analysis can provide systematic information for improving performance of a system. The author has studied on the development of the structural analysis algorithm and suggested recently the transfer stiffness coefficient method(TSCM). This method is very suitable algorithm to a personal computer because the concept of the TSCM is based on the transfer of the nodal stiffness coefficients which are related to force and displacement vectors at each node. In this paper, a new sensitivity analysis algorithm using the concept of the TSCM is formulated for the computation of state variable sensitivity in static problems. The trust of the proposed algorithm is confirmed through the comparison with the computation results using existent sensitivity analysis algorithm and reanalysis for computation models.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.602-603
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• 2007

In this paper, the RCF method is applied to analyze small signal stability of power systems including thyristor controlled FACTS equipments such as SVC. The eigenvalue sensitivity analysis algorithm in discrete systems by the RCF method are presented and applied to the power system including SVC. As a result of simulation, the RCF analysis method is very powerful to calculate the newly generated unstable oscillation modes precisely after periodic switching operations of SVC. Also the RCF analysis method enabled to precisely calculate eigenvalue sensitivity coefficients of dominant oscillation modes after periodic switching operations. These simulation results are very different from those of the conventional continuous system analysis method such as the state space equation method.