Study of the location of TCSC for improving ATC considering N-1 security constraints

Tang, Wenjie; Pan, Wei; Zhang, Kaifeng; Liu, Cheng

doi:10.1109/ccdc.2014.6852526

Cited by 4 publications

(2 citation statements)

References 11 publications

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“…With existing investigated technologies this work gives a fundamental detailing of the WEVCS for fixed and dynamic uses [263]. This research presents a TCSC locating technique in the PS in an attempt to optimize the available transfer capability (ATC) between system buses [264].…”

Section: Evs With D-facts Planningmentioning

confidence: 99%

Challenges and opportunities of FACTS devices interacting with electric vehicles in distribution networks: A technological review

Mousaei,

Gheisarnejad,

Khooban

2023

Journal of Energy Storage

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Section: Evs With D-facts Planningmentioning

confidence: 99%

Challenges and opportunities of FACTS devices interacting with electric vehicles in distribution networks: A technological review

Mousaei,

Gheisarnejad,

Khooban

2023

Journal of Energy Storage

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“…The optimal placement and size of TCSC in power systems to reduce the risks in power grid operation is discussed in [19]. The optimal allocation of TCSCs for congestion management is also studied in [20][21][22][23] for different applications.…”

Section: Introductionmentioning

confidence: 99%

Optimal Placement of TCSC for Congestion Management and Power Loss Reduction Using Multi-Objective Genetic Algorithm

Nguyen

Mohammadi

2020

Sustainability

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Electricity demand has been growing due to the increase in the world population and higher energy usage per capita as compared to the past. As a result, various methods have been proposed to increase the efficiency of power systems in terms of mitigating congestion and minimizing power losses. Power grids operating limitations result in congestion that specifies the final capacity of the system, which decreases the conventional power capabilities between coverage areas. Flexible AC Transmission Systems (FACTS) can help to decrease flows in heavily loaded lines and lead to lines loadability improvements and cost reduction. In this paper, total power loss reduction and line congestion improvement are assessed by determining the optimal locations and compensation rates of Thyristor-Controlled Series Compensator (TCSC) devices using the Multi-Objective Genetic Algorithm (MOGA). The results of applying the proposed method on the IEEE 30-bus test system confirmed the efficiency of the proposed procedure. In addition, to check the performance, applicability, and effectiveness of the proposed method, different heuristic algorithms, such as the multi-objective Particle Swarm Optimization (PSO) algorithm, Differential Evolution (DE) algorithm, and Mixed-Integer Non-Linear Program (MINLP) technique, are used for comparison. The obtained results show the accuracy and fast convergence of the proposed method over the other heuristic techniques.

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The Development of a Risk Assessment Modeling for the Power System of Kazakhstan

Zhakiyeva

Gabbassov

Akhmetbekov

et al. 2021

2021 IEEE International Conference on Smart Information Systems and Technologies (SIST)

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Study of the location of TCSC for improving ATC considering N-1 security constraints

Cited by 4 publications

References 11 publications

Challenges and opportunities of FACTS devices interacting with electric vehicles in distribution networks: A technological review

Challenges and opportunities of FACTS devices interacting with electric vehicles in distribution networks: A technological review

Optimal Placement of TCSC for Congestion Management and Power Loss Reduction Using Multi-Objective Genetic Algorithm

The Development of a Risk Assessment Modeling for the Power System of Kazakhstan

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