• Proceedings of the KIEE Conference
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• 2005.11b
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• pp.46-48
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• 2005

This paper discusses a probabilistic method for power system security assessment. The security analysis relates to the ability of the electric power systems to survive sudden disturbances such as electric short circuits or unanticipated loss of system elements. It consists of both steady state and dynamic security analyses, which are not two separate issues but should be considered together. In steady state security analysis including voltage security analysis, the analysis checks that the system is operated within security limits by OPF (optimal power flow) after the transition to a new operating point. Until now, many utilities have difficulty in including dynamic aspects due to computational capabilities. On the other hand. dynamic security analysis is required to ensure that the transition may lead to an acceptable operating condition. Transient stability, which is the ability of power systems to maintain synchronism when subjected to a large disturbance. is a principal component in dynamic security analysis. Usually any loss of synchronism may cause additional outages and make the present steady state analysis of the post-contingency condition inadequate for unstable cases. This is the reason for the need of dynamic studies in power systems. Probabilistic criterion can be used to recognize the probabilistic nature of system components while considering system security. In this approach. we do not have to assign any predetermined margin of safety. A comprehensive conceptual framework for probabilistic static and dynamic assessment is presented in this paper. The simulation results of the Western System Coordinating Council (WSCC) system compare an analytical method with Monte-Carlo simulation (MCS).

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.804-806
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• 2005

In this paper, a new probabilistic generation modeling method which can address the characteristics of changed electricity industry is proposed. The major contribution of this paper can be captured in the development of a probabilistic generation modeling considering generator maintenance outage and in the classification of market demand into multiple demand clusters for the applications to electricity markets. Conventional forced outage rates of generators are conceptually combined with maintenance outage of generators and, consequently, effective outage rates of generators are new iy defined in order to properly address the probabilistic characteristic of generation in electricity markets. Then, original market demands are classified into several distinct demand clusters, which are defined by the effective outage rates of generators and by the inherent characteristic of the original demand. We have found that generators have different effective outage rates values at each classified demand cluster, depending on the market situation. From this, therefore, it can be seen that electricity markets can also be classified into several groups which show similar patterns and that the fundamental characteristics of power systems can be more efficiently analyzed in electricity markets perspectives, for this classification can be widely applicable to other technical problems in power systems such as generation scheduling, power flow analysis, price forecasts, and so on.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.5
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• pp.185-190
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• 2006

The security analysis relates to the ability of the electric systems to survive sudden disturbances such as electric short circuits or unanticipated loss of system elements. It is composed of both steady state and dynamic security analyses, which are not two separate issues but should be considered together. In steady state security analysis including voltage security analysis, the analysis checks that the system is operated within security limits by OPF (optimal power flow) after the transition of a new operating point. On the other hand, dynamic security analysis deals that the transition will lead to an acceptable operating condition. Transient stability, which is the ability of power systems to maintain synchronism when subjected to a large disturbance, is a principal component in dynamic security analysis. Usually any loss of synchronism will cause additional outages. They make the present steady state analysis of the post-contingency condition inadequate for unstable cases. This is the reason of the need for dynamics of systems. Probabilistic criterion can be used to recognize the probabilistic nature of system components and shows the possibility of system security. A comprehensive conceptual framework for probabilistic static and dynamic assessment is presented in this paper. The simulation results of the Western System Coordinating Council (WSCC) system compare an analytical method with Monte-Carlo simulation (MCS). Also, a case study of the extended IEEE Reliability Test System (RTS) shows the efficiency of this approach.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.11
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• pp.533-539
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• 2005

According to NERC definition, Available Transfer Capability (ATC) is a measure of the transfer capability remaining in the physical transmission network for the future commercial activity. To calculate Available Transfer Capability, accurate and defensible Total Transfer Capability, Capacity Benefit Margin and Transmission Reliability Margin should be calculated in advance. This paper proposes a method to quantify time varying Available Transfer Capability based on probabilistic approach. The uncertainties of power system and market are considered as complex random variables. Total Transfer Capability is determined by optimization technique such as SQP(Sequential Quadratic Programming). Transmission Reliability Margin with the desired probabilistic margin is calculated based on Probabilistic Load Flow analysis, and Capacity Benefit Margin is evaluated using LOLE of the system. Suggested Available Transfer Capability quantification method is verified using IEEE RTS with 72 bus. The proposed method shows efficiency and flexibility for the quantification of Available Transfer Capability.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2211-2220
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• 2015

This paper analyzes multiple active management (AM) techniques of active distribution network (ADN), and proposes an optimal coordination model of intermittent distributed generation (IDG) accommodation considering the timing characteristic of load and IDG. The objective of the model is to maximize the daily amount of IDG accommodation under the uncertainties of IDG and load. Various active management techniques such as IDG curtailment, on-load tap changer (OLTC) tap adjusting, voltage regulator (VR) tap adjusting, shunt capacitors compensation and so on are fully considered. Genetic algorithm and Primal-Dual Interior Point Method (PDIPM) is used for the model solving. Point estimate method is used to simulate the uncertainties. Different scenarios are selected for the IDG accommodation capability investigation under different active management schemes. Finally a modified IEEE 123 case is used to testify the proposed accommodation model, the results show that the active management can largely increase the IDG accommodation and penetration.

• 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.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.820-831
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• 2015

In a deregulated electricity market, congestion of the transmission lines is a major problem the independent system operator (ISO) would face. Rescheduling of generators is one of the most practiced techniques to alleviate the congestion. However, not all generators in the system operate deterministically and independently, especially wind power generators (WTGs). Therefore, a novel optimal rescheduling model for congestion management that accounts for the uncertain and correlated power sources and loads is proposed. A probabilistic power flow (PPF) model based on 2m+1 point estimate method (PEM) is used to simulate the performance of uncertain and correlated input random variables. In addition, the impact of direct electricity purchase contracts on the congestion management has also been studied. This paper uses artificial bee colony (ABC) algorithm to solve the complex optimization problem. The proposed algorithm is tested on modified IEEE 30-bus system and IEEE 57-bus system to demonstrate the impacts of the uncertainties and correlations of the input random variables and the direct electricity purchase contracts on the congestion management. Both pool and nodal pricing model are also discussed.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.80-89
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• 2014

A stochastic optimal power flow (S-OPF) model considering uncertainties of load and wind power is developed based on chance constrained programming (CCP). The difficulties in solving the model are the nonlinearity and probabilistic constraints. In this paper, a limit relaxation approach and an iterative learning control (ILC) method are implemented to solve the S-OPF model indirectly. The limit relaxation approach narrows the solution space by introducing regulatory factors, according to the relationship between the constraint equations and the optimization variables. The regulatory factors are designed by ILC method to ensure the optimality of final solution under a predefined confidence level. The optimization algorithm for S-OPF is completed based on the combination of limit relaxation and ILC and tested on the IEEE 14-bus system.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.4
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• pp.346-354
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• 1992

In the power-system, the active and reactive power levels of load bus randomly vary over days, months, and years which are stochastic in nature. This paper presents an algorithm for optimal Var planning considering the uncertainties of loads. The optimization problem is solved by a stochastic linear programming technique which can handle stochastic constraints to evaluate optimal Var requirement at load bus to maintain the voltage profile which results in probabilistic density function by stochastic Load Flow analysis within admissible range. The effectiveness of the proposed algorithm has been verified by the test on the IEEE-30 bus system.

• Nuclear Engineering and Technology
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• v.47 no.3
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• pp.332-339
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• 2015

The leak before break (LBB) concept is widely used in designing pipe lines in nuclear power plants. According to the concept, the amount of leaking liquid from a pipe should be more than the minimum detectable leak rate of a leak detection system before catastrophic failure occurs. Therefore, accurate estimation of the leak rate is important to evaluate the validity of the LBB concept in pipe line design. In this paper, a program was developed to estimate the leak rate through circumferential cracks in pipes in nuclear power plants using the Henry-Fauske flow model and modified Henry-Fauske flow model. By using the developed program, the leak rate was calculated for a circumferential crack in a sample pipe, and the effect of the flow model on the leak rate was examined. Treating the crack morphology parameters as random variables, the statistical behavior of the leak rate was also examined. As a result, it was found that the crack morphology parameters have a strong effect on the leak rate and the statistical behavior of the leak rate can be simulated using normally distributed crack morphology parameters.