• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.9
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• pp.431-439
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• 2001

This Paper illustrates a new numerical analysis method using a nodal effective load model for nodal probabilistic production cost simulation of the load point in a composite power system. The new effective load model includes capacities and uncertainties of generators as well as transmission lines. The CMELDC(composite power system effective load duration curve) based on the new effective load model at HLll(Hierarchical Level H) has been developed also. The CMELDC can be obtained from convolution integral processing of the outage capacity probabilistic distribution function of the fictitious generator and the original load duration curve given at the load point. It is expected that the new model for the CMELDC proposed in this study will provide some solutions to many problems based on nodal and decentralized operation and control of an electric power systems under competition environment in future. The CMELDC based on the new model at HLll will extend the application areas of nodal probabilistic production cost simulation, outage cost assessment and reliability evaluation etc. at load points. The characteristics and effectiveness of this new model are illustrated by a case study of MRBTS(Modified Roy Billinton Test System).

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.243-245
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• 2001

The reliability and probabilistic generation production cost evaluation of composite power systems are important for power system operation and expansion planning. This paper present a computer program which can evaluate the reliability and probabilistic generation production cost of composite power system using GUI(Graphic User Interface). In this computer program, Monte Carlo simulation methods and CMELDC(CoMposite power system Effective Load Duration Curve) were used.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.9
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• pp.425-432
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• 2002

This Paper illustrates a method for evaluating nodal probabilistic production cost using the CMELDC. A new method for constructing CMELDC(CoMposite Power System Equivalent Load Duration Curve) has been developed by authors. The CMELDC can be obtained by convolution integral processing between the probability distribution functions of the fictitious generators outage capacity and the load duration curves at each load point. In general, if complex operating conditions are involved and/or the number of severe events is relatively large, Monte Carlo methods are more efficient. Because of that reason, Monte Carlo Methods are applied for the construction of CMELDC in this study. And IEEE-RTS 24 buses model is used as our case study with satisfactory results.

• Proceedings of the KIEE Conference
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• 2001.05a
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• pp.112-115
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• 2001

This paper illustrates a new nodal effective load model for nodal probabilistic production cost simulation of the load point in a composite power system. The new effective load model includes capacities and uncertainties of generators as well as transmission lines. The CMELDC based on the new effective load model at HLII has been developed also. The CMELDC can be obtain from convolution integral processing of the outage capacity probabilistic distribution function of the fictitious generator and the original load duration curve given at the load point. It is expected that the new model for the CMELDC proposed. In this study will provide some solutions to many problems based on nodal and decentralized operation and control of an electric power systems under competition environment in future. The CMELDC based on the new model at HLII will extend the application areas of nodal probabilistic production cost simulation, outage cost assessment and reliability evaluation etc. at load points. The characteristics and effectiveness of this new model are illustrated by a case study of a test system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.4
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• pp.195-198
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• 2000

This paper illustrates a new method for constructing composite power system effective load duration curve(CMELDC) at load points. The main concept of proposed method is that the CMELDC can be obtain from convolution integral processing of the outage probabilistic distribution function of not supplied power and the load duration curve given at each load point. The effective load duration curve (ELDC) at HLI plays an important part in probabilistic production simulation, reliability evaluation, outage cost assessment and power supply margins assesment for power system planning and operation. And also, the CMELDC at HLII will extend the application areas of outage cost assessment and reliability evaluation at each load point. The CMELDC at load points using the Monte Carlo method and a DC load flow constrained LP have already been developed by authors. The effective load concept at HLII, however, has not been introduced sufficiently in last paper although the concept is important. In this paper, the main concept of the effective load at HLII which is proposed in this study is defined in details as the summation of the original load and the probabilistic loads caused by the forced outage of generators and transmission lines at this load point. The outage capacity probabilistic distribution function at HLII can be obtained by combining the not supplied powers and the probabilities of the not supplied powers at this load point. It si also expected that the proposed CMELDC can be applied usefully to research areas such as reliability evaluation, probabilistic production cost simulation and analytical outage cost assessment, etc. at HLII in future. The characteristics and effectiveness of this methodology are illustrated by case study of IEEE-RTS.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.275-278
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• 2006

This paper describes a probabilistic annual congestion cost assessment of a grid at a composite power system derived from a model. This probabilistic congestion cost assessment simulation model includes capacity limitation and uncertainties of the generators and transmission lines. In this paper, the proposed probabilistic congestion cost assessment model is focused on an annualized simulation methodology for solving long-term grid expansion planning issues. It emphasizes the questions of "how should the uncertainties of system elements (generators, lines and transformers, etc.) be considered for annual congestion cost assessment from the macro economic view point"? This simulation methodology comes essentially from a probabilistic production cost simulation model of composite power systems. This type of model comes from a nodal equivalent load duration curve based on a new effective load model at load points. The characteristics and effectiveness of this new simulation model are illustrated by several case studies of a test system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.9
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• pp.1507-1513
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• 2010

The $CO_2$ emission can be decreased due to freedom of generator maintenance scheduling(GMS). This paper proposes assessment of $CO_2$ emission considering generator maintenance scheduling(GMS) and evaluates effect of the GMS on $CO_2$ emission. And also, this paper assesses the $CO_2$ emission and the probabilistic production cost simulation of nuclear and thermal power generators considering operation of hydro and pumped generator. The minimum reliability criterion level satisfied production cost minimization function model is used in this paper. The practicality and effectiveness of the proposed approach are demonstrated by simulation studies for a real size power system in Korea in 2010.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.206-209
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• 2001

This paper illustrates a new method for reliability evaluation at load points in a composite power system. The algorithm includes uncertainties of generators and transmission lines as well as main transformers at substations. The CMELDC based on the new effective load model at HLII has been developed also. The CMELDC can be obtain from convolution integral processing of the outage capacity probabilistic distribution function of the fictitious generator and the original load duration curve given at the load point. The CMELDC based on the new model at HLII will extend the application areas of nodal probabilistic production cost simulation, outage cost assessment and reliability evaluation etc. at load points. The characteristics and effectiveness of this new model are illustrated by a case study of a small test system.

• Proceedings of the KIEE Conference
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• 2007.11b
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• pp.173-175
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• 2007

This paper introduces the characteristics of relationship between probabilistic reliability (LOLE; Loss of Load Expectation) and deterministic reliability (SRR; supply reserve rate) for 2008 year in Korea power system. Korea power system has been using the LOLE criterion to determine the adequacy of installed capacity (ICAP) requirement. The criterion is that load shall not exceed the avaliable capacity, on the average, more than five day in ten years. The probabilistic reliability evaluation and production cost simulation program which is called PPHFHT was used in order to obtain the relationship in this paper.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.8
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• pp.1318-1326
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• 2008

This paper proposes an alternative methodology for deciding an optimum deterministic reliability level (IRR; Installed Reserve Rate) by using probabilistic reliability criterion (LOLE; Loss of Load Expectation). Additionally, case studies using the proposed method induce the characteristics of relationship between the probabilistic reliability index (LOLE) and deterministic reliability index (IRR) for 2008 and 2010 years in Korea power system. The case study presents a possibility that an optimum IRR level in Korea can be assessed using the proposed method. Korea power system has been using the LOLE criterion to determine the adequacy of installed capacity (ICAP) requirement. The criterion in Korea is that the loss of load expectation shall not exceed the available capacity more than five day in ten years (=0.5[days/year]), The probabilistic reliability evaluation and production cost simulation program which is called PRASim is used in order to evaluate the relationship and optimum IRR in this paper.