• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.12
• /
• pp.1965-1970
• /
• 2016

This paper studies generator rescheduling technique for congestion management in power system with wind farms. The proposed technique is formulated to minimize the rescheduling cost of conventional and wind generators to alleviate congestion subject to operational line overloading. The generator rescheduling method has been used with incorporation of wind farms in the power system. The locations of wind farms are selected based upon power transfer distribution factor (PTDF). Because all generators in the system do not need to participate in congestion management, the rescheduling has been done by generator selection based on the proposed generator sensitivity factor (GSF). The selected generators have been rescheduled using linear programming(LP) optimization techniques to alleviate transmission congestion. The effectiveness of the proposed methodology has been analyzed on IEEE 14-bus systems.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.66 no.2
• /
• pp.255-260
• /
• 2017

This paper studies on effective rescheduling of generation when the single line contingency has occurred in power system with wind farm. The suggested method is formulated to minimize the rescheduling cost of conventional and wind generators to alleviate congestion. The generator rescheduling method has been used with incorporation of wind farms in the power system. Since all sensitivity is different about congestion line, Line Outage Distribution Factor(LODF) and Generator Sensitivity Factor(GSF) is used to alleviate congestion. The formulation have been proccessed using linear programming(LP) optimization techniques to alleviate transmission congestion. The effectiveness of the proposed rescheduling of generation method has been analyzed on revised IEEE 30-bus systems.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.27 no.1
• /
• pp.68-75
• /
• 2013

This paper presents a scheme to improve transient stability using Newton's Approach for generation rescheduling. For a given contingency, the energy margin and sensitivities are computed. The bigger energy margin sensitivity of generator is, the more the generation of the generator effects to the transient stability. According to energy margin sensitivity, the control variables of generation rescheduling are selected. The fuel cost function is used as objective function to reallocate power generation. The results are compared to the results of time simulation to show its the effectiveness.

• Journal of Electrical Engineering and Technology
• /
• v.6 no.1
• /
• pp.32-41
• /
• 2011

This paper presents a new method of Fuzzy Particle Swarm Optimization (FPSO)-based Congestion Management (CM) by optimal rescheduling of active powers of generators. In the proposed method, generators are selected based on their sensitivity to the congested line for efficient utilization. The task of optimally rescheduling the active powers of the participating generators to reduce congestion in the transmission line is attempted by FPSO, Fitness Distance Ratio PSO (FDR-PSO), and conventional PSO. The FPSO and FDR-PSO algorithms are tested on the IEEE 30-bus and Practical Indian 75-bus systems, after which the results are compared with conventional PSO to determine the effectiveness of CM. Compared with FDR-PSO and PSO, FPSO can better perform the optimal rescheduling of generators to relieve congestion in the transmission line.

• JOURNAL OF ELECTRICAL WORLD
• /
• no.10 s.82
• /
• pp.10-17
• /
• 1983

• JOURNAL OF ELECTRICAL WORLD
• /
• no.9 s.81
• /
• pp.12-20
• /
• 1983

• Journal of Electrical Engineering and Technology
• /
• v.10 no.1
• /
• pp.83-91
• /
• 2015

This paper presents preventive and emergency control measures for on line transient stability (security) enhancement. For insecure operating state, generation rescheduling based on a real power generation shift factor (RPGSF) is proposed as a preventive control measure to bring the system back to secure operating state. For emergency operating state, two emergency control strategies namely generator shedding and load shedding have been developed. The proposed emergency control strategies are based on voltage magnitudes and rotor trajectories data available through Phasor Measurement Units (PMUs) installed in the systems. The effectiveness of the proposed approach has been investigated on IEEE-39 bus test system under different contingency and fault conditions and application results are presented.

• 전기의세계
• /
• v.32 no.11
• /
• pp.664-669
• /
• 1983

대규모 system을 취급하는 공학분야에 있어서 Matrix의 demension이 커짐에 따라 전산부담을 줄이기 위한 소요기억용량 절감 및 계산시간의 단축이 주된 관심사 중의 하나가 되어 왔다. LP(Linear Programming)기법 역시 대규모 선형 system에 적용될 경우 Basic Matrix 에 대한 dimensionality 문제를 포함하고 있으며 이에 대한 효과적인 해결방법으로 Bartels-Golub Decomposition 방법이 연구되어 있다. 이 방법은 Chan과 Yip등이 LSGA(Load Shedding and Generator Rescheduling) 문제에의 적용을 시도한 바 있으며, 일반적인 선형최적화 문제뿐만 아니라, dimensionality가 큰 Matrix의 Inverse 계산을 요하는 문제에 널리 적용될 수 있으므로 그 개요를 소개하고자 한다.

• Journal of Electrical Engineering and Technology
• /
• v.6 no.4
• /
• pp.493-504
• /
• 2011

The present paper presents a genetic algorithm (GA) to maximize social welfare and perform congestion management by optimally placing and sizing one Thyristor-Controlled Series Capacitor (TCSC) device in a double-sided auction market. Simulation results, with line flow constraints before and after the compensation, are compared through the Sequential Quadratic Programming SQP method, and are used to analyze the effect of TCSC on the congestion levels of modified IEEE 14-bus and 30-bus test systems. Quadratic, smooth and nonsmooth (with sine components due to valve point loading effect) generator cost curves, and quadratic smooth consumer benefit functions are considered. The main aims of the present study are the inclusion of customer benefit in the social welfare maximization and congestion management objective function, the consideration of nonsmooth generator characteristics, and the optimal locating and sizing of the TCSC using real code-based GA to guarantee fast convergence to the best solution.