• Journal of Electrical Engineering and Technology
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• v.7 no.5
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• pp.698-704
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• 2012

This paper proposes a new methodology for evaluating the probabilistic reliability based grid expansion planning of composite power system including the Wind Turbine Generators. The proposed model includes capacity limitations and uncertainties of the generators and transmission lines. It proposes to handle the uncertainties of system elements (generators, lines, transformers and wind resources of WTG, etc.) by a Composite power system Equivalent Load Duration Curve (CMELDC)-based model considering wind turbine generators (WTG). The model is derived from a nodal equivalent load duration curve based on an effective nodal load model including WTGs. Several scenarios are used to choose the optimal solution among various scenarios featuring new candidate lines. The characteristics and effectiveness of this simulation model are illustrated by case study using Jeju power system in South Korea.

• KIEE International Transactions on Power Engineering
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• v.3A no.3
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• pp.119-123
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• 2003

Successful operation of power systems under the deregulated electricity market depends on the management of the transmission system reliability. Quantitative evaluation of the transmission system reliability is an important issue. Particularly, the nodal reliability indices can be of value in the management and control of congestion and reliability of the transmission system under the deregulated electricity market. In this study, a method developed for the reliability evaluation of the transmission system is presented. The Monte Carlo methods are used because of their flexibility when complex operating conditions are being considered. The usefulness and effectiveness of the proposed method are illustrated by a case study with the KEPCO system.

• Proceedings of the KIEE Conference
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• 2001.05a
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• pp.169-171
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• 2001

This paper presents a method fer evaluation nodal probabilistic congestion and reliability indices of transmission systems using Monte Carlo simulation methods. Quantitative evaluation of transmission system reliability is very important because successful operation of an electric power system. In the deregulated electricity market depends on transmission system reliability management Monte Carlo methods are often preferable, when complex operating conditions are involved and/or the number of sever events is relatively large. To evaluate the reliability of a real power system, Monte Carlo Methods will be more useful. The characteristics and effectiveness of this methodology are illustrated by the case study using a small test system.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2104-2125
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• 2021

This paper presents the verification and validation (V&V) of a calculation module for isotope inventory prediction to control the back-end cycle of spent nuclear fuel (SNF). The calculation method presented herein was implemented in a two-step code system of a lattice code STREAM and a nodal diffusion code RAST-K. STREAM generates a cross section and provides the number density information using branch/history depletion branch calculations, whereas RAST-K supplies the power history and three history indices (boron concentration, moderator temperature, and fuel temperature). As its primary feature, this method can directly consider three-dimensional core simulation conditions using history indices of the operating conditions. Therefore, this method reduces the computation time by avoiding a recalculation of the fuel depletion. The module for isotope inventory calculates the number densities using the Lagrange interpolation method and power history correction factors, which are applied to correct the effects of the decay and fission products generated at different power levels. To assess the reliability of the developed code system for back-end cycle analysis, validation study was performed with 58 measured samples of pressurized water reactor (PWR) SNF, and code-to-code comparison was conducted with STREAM-SNF, HELIOS-1.6 and SCALE 5.1. The V&V results presented that the developed code system can provide reasonable results with comparable confidence intervals. As a result, this paper successfully demonstrates that the isotope inventory prediction code system can be used for spent nuclear fuel analysis.