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Application of Modified Teaching-Learning Algorithm in Coordination Optimization of TCSC and SVC

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Pattern Recognition (CCPR 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 483))

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Abstract

Due to the interaction among FACTS devices, coordination control of multi-FACTS devices is a hot and urgent topic. A multi-objective optimization problem is formulated in this paper. And a modified teaching-learning algorithm (MTLA) is presented to coordinate Thyristor Controlled Series Capacitor (TCSC), Static Var Compensator (SVC) and power angle difference damping characteristics of generators. The optimal parameters of controller are found out to improve the coordination control. Compared with basic-TLA, MTLA applies a new learner phase in order to avoid entrapment into local optima. Then it comes with a locked device phase for the improvement of convergence rate. Meanwhile, several meta-heuristic techniques are utilized to search and save Pareto-optimal solutions of controller parameters. The proposed algorithm is validated and illustrated on IEEE 4-machine 11-bus system.

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Xiao, L., Zhu, Q., Li, C., Cao, Y., Tan, Y., Li, L. (2014). Application of Modified Teaching-Learning Algorithm in Coordination Optimization of TCSC and SVC. In: Li, S., Liu, C., Wang, Y. (eds) Pattern Recognition. CCPR 2014. Communications in Computer and Information Science, vol 483. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45646-0_5

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  • DOI: https://doi.org/10.1007/978-3-662-45646-0_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45645-3

  • Online ISBN: 978-3-662-45646-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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