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Optimal Control Strategy to Alleviate Line Congestion in Power System using Bus Power Rescheduling

Publication Type : Journal Article

Publisher : Journal of Electrical Systems

Source : Journal of Electrical Systems, Volume 16, Issue 2, p.201-217 (2020)

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Campus : Coimbatore

School : School of Engineering

Department : Electrical and Electronics

Year : 2020

Abstract : The Line flow limit is one of the major challenges faced by electric utilities. The prevailing load conditions cause congestion in transmission line. A decisive control action is essential to relieve the congestion by allowing the power to flow in a different route in the same system. The rerouting of power is possible by controlling the generation at a bus or controlling the load in such a way that the power is rerouted through the other lines present in the power system. In this paper, an attempt has been made to relieve the congestion using a sensitivity based direct method and Genetic algorithm (GA) based optimization technique, wherein the power flows in the transmission lines are maintained within the security limits by using both generation shifting and load control. GA is used to calculate the amount of generation and load control required for congestion management in the system. The results of the sensitivity based direct method for congestion management are compared with the results of GA based congestion management technique by implementing both the proposed methods on IEEE 5 bus system and IEEE 30 bus systemwith a congested line. The effectiveness of each algorithm is also analyzed by applying the techniques on hardware of reduced order model of IEEE 5 bus system. It is found that GA based method is able to alleviate the overloads in transmission line more effectively than the direct method

Cite this Research Publication : Janarthanan N., Dr. Balamurugan S., and Dr. Sasi K. K., “Optimal Control Strategy to Alleviate Line Congestion in Power System using Bus Power Rescheduling”, Journal of Electrical Systems, vol. 16, no. 2, pp. 201-217, 2020.

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