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Corrective Control Strategies for Mitigation of Line Overloads during Contingencies


Affiliations
1 Department of Electrical Engineering, Indian Institute of Technology, Madras, Chennai - 600 036, India
     

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This paper presents a new corrective control strategy to mitigate the transmission line overloading, with the help of a local optimisation concept. A new Direct Acylic Graph (DAG) technique for selection of participating generators and buses with respect to a contingency is presented. Particle Swarm Optimisation (PSO) technique has been employed for generator rescheduling and/or load shedding problem locally to restore the system from abnormal to normal operating state. The effectiveness of the proposed approach is demonstrated for different contingency cases in IEEE 14 and 30 bus systems. The result shows that the proposed approach is computationally fast, reliable and efficient, in restoring the system to normal state after a contingency with minimal control actions.

Keywords

Direct Acyclic Graph, Local Optimisation, Corrective Control Strategy, Particle Swarm Optimisation, Generator Rescheduling, Load Shedding.
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  • Corrective Control Strategies for Mitigation of Line Overloads during Contingencies

Abstract Views: 273  |  PDF Views: 0

Authors

Manoj Kumar Maharana
Department of Electrical Engineering, Indian Institute of Technology, Madras, Chennai - 600 036, India
K. Shanti Swarup
Department of Electrical Engineering, Indian Institute of Technology, Madras, Chennai - 600 036, India

Abstract


This paper presents a new corrective control strategy to mitigate the transmission line overloading, with the help of a local optimisation concept. A new Direct Acylic Graph (DAG) technique for selection of participating generators and buses with respect to a contingency is presented. Particle Swarm Optimisation (PSO) technique has been employed for generator rescheduling and/or load shedding problem locally to restore the system from abnormal to normal operating state. The effectiveness of the proposed approach is demonstrated for different contingency cases in IEEE 14 and 30 bus systems. The result shows that the proposed approach is computationally fast, reliable and efficient, in restoring the system to normal state after a contingency with minimal control actions.

Keywords


Direct Acyclic Graph, Local Optimisation, Corrective Control Strategy, Particle Swarm Optimisation, Generator Rescheduling, Load Shedding.



DOI: https://doi.org/10.33686/prj.v5i2.189655