• 대한전기학회논문지:전력기술부문A
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• 제54권11호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 추계학술대회 논문집 전력기술부문
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• pp.360-362
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• 2006

가용송전용량(Available Transfer Capability : ATC) 계산을 위해 우선 견정해야할 요소는 총 송전용량(Total Transfer Capability : TTC)이며 이는 일반적으로 열, 전압, 안정도 한계치에 의해 결정된다. 국내 계통의 송전선로 길이를 고려할 때, 이 세 가지 한계치 중 열 정격은 TTC 결정에 가장 큰 비중을 차지하는 요소이다. 따라서 본 논문은 열적 한계치에 동적 송전용량(Dynamic Line Rating : DLR)의 개념을 도입 하여 TTC를 결정하는 새로운 접근법을 제안한다. 이 방법은 기존의 방법에 비해 주변 환경의 물리적 변화에 따른 정확한 계산 결과를 제공함으로서, 실제 사용가능한 용량을 평가한다. 마지막으로 제안하는 방법의 유용성을 보이기 위해 IEEE-24 모선 RTS를 이용하여, 기존의 방법과 제안하는 방법을 비교하였다.

• 대한전기학회논문지:전력기술부문A
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• 제53권5호
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• pp.296-301
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• 2004

The Available Transfer Capability (ATC) is defined as the measure of the transfer capability remaining in the physical transmission network for further commercial activity above already committed uses. Available Transfer Capability (ATC) calculation is a complicated task, which involves the determination I of total transfer capability (TTC), transmission reliability margin (TRM) and capability benefit margin (CBM). As the electrical power industry is restructured and the electrical power exchange is updated per hour, it is important to accurately and rapidly quantify the available transfer capability (ATC) of the transmission system. In ATC calculation,. the existing CPF method is accurate but it has long calculation time. On the contrary, the method using PTDF is fast but it has relatively a considerable error. This paper proposed QFA method, which can reduce calculation time comparing with CPF method and has few errors in ATC calculation. It proved that the method can calculate ATC more fast and accurately in case study using IEEE 24 bus RTS.

• 대한전기학회논문지:전력기술부문A
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• 제55권1호
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• pp.45-51
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• 2006

This paper proposes a method to evaluate the Total Transfer Capability (TTC) by considering uncertainty of weather conditions. TTC is limited not only by the violation of system thermal and voltage limits, but also restricted by transient stability limit. Impact of the contingency on the power system performance could not be addressed in a deterministic way because of the random nature of the system equipment outage and the increase of outage probability according to the weather conditions. For these reasons, probabilistic approach is necessary to realize evaluation of the TTC. This method uses a sequential Monte Carlo simulation (MCS). In sequential simulation, the chronological behavior of the system is simulated by sampling sequence of the system operating states based on the probability distribution of the component state duration. Therefore, MCS is used to accomplish the probabilistic calculation of the TTC with consideration of the weather conditions.

• 대한전기학회논문지:전력기술부문A
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• 제55권12호
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• pp.549-554
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• 2006

Available transfer capability(ATC) is an important indicator of the usable amount of transmission capacity accessible by several parties for commercial trading in power transaction activities. This paper deals with an application of optimization technique for available transfer capability(ATC) calculation and analyzes the results of ATC by considering several constraints. Especially several optimization techniques are used to solve the ATC problem with state-steady security constraints. The results are compared with that of repeat power flow(RPF), sequential quadratic programming(SQP) and linear programming(LP). The proposed method is applied to 10 machines 39 buses model systems to show its effectiveness.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 추계학술대회 논문집 전력기술부문
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• pp.271-273
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• 2002

This paper proposes a process that determines inter-area TTC(total transfer capability) by supplementing the existing process. The process is composed of three steps, which is composed of (a) estimation of input data, (b) selection of contingencies, and (c) determination of the transfer capability. In this study, one step is added to develop the methodology that enhances the TTC.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 A
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• pp.199-201
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• 2005

This paper proposes a method to evaluate the TTC by considering uncertainty of weather. Impact of the contingency on the system performance could not be addressed in a deterministic way because of the random nature of the system equipment outage and the increase of outage probability according to weather condition. For this reasons, probabilistic approach is necessary to realize evaluation of TTC. This method uses a sequential MCS. In sequential simulation, the chronological behavior of the system is simulated by sampling sequence of the system operating states based on the probability distribution of the component state duration. Therefor, MCS is used to accomplish the probabilistic calculation of TTC with consideration of weather condition.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.570-571
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• 2008

This paper presents a method for the determination of total transfer capability in interconnected power systems, which is based on sequential quadratic programming (SQP). The objective function is the maximization of the interconnected line flow. To calculate TTC the control variables are the active power of the generating units, the voltage magnitude of the generator, transformer tap settings and SVC setting. The state variables are the bus voltage magnitude, the reactive power of the generating unit, line flows and the tie line flow. The method proposed is applied to the modified IEEE 14 buses model system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 추계학술대회 논문집 전력기술부문
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• pp.223-225
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• 2005

This paper presents a scheme to solve the congestion problem using hybrid control with phase-shifting transformer(PST) and power generation in power systems. A good design of PST and power generation control can improve total transfer capability(TTC) in interconnected systems. This paper deals with an application of optimization technique for TTC calculation. The optimization method is used to maximize power flow of tic line subject to security constraints such as voltage magnitude and real power flow. The proposed method is applied to 10 machines 39 buses model systems to show its effectiveness.

• Journal of Electrical Engineering and Technology
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• 제8권1호
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• pp.20-30
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• 2013

An intelligent grid computing architecture is proposed and developed for transient stability constrained total transfer capability evaluation of future smart grid. In the proposed intelligent grid computing architecture, a model of generalized compute nodes with 'able person should do more work' feature is presented and implemented to make full use of each node. A timeout handling strategy called conditional resource preemption is designed to improve the whole system computing performance further. The architecture can intelligently and effectively integrate heterogeneous distributed computing resources around Intranet/Internet and implement the dynamic load balancing. Furthermore, the robustness of the architecture is analyzed and developed as well. The case studies have been carried out on the IEEE New England 39-bus system and a real-sized Chinese power system, and results demonstrate the practicability and effectiveness of the intelligent grid computing architecture.