Reactive power planning problem considering multiple type of FACTS in power systems

Vikash Kumar Gupta () and Rohit Babu ()
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Vikash Kumar Gupta: National Institute of Foundry & Forge Technology (NIFFT)
Rohit Babu: Lendi Institute of Engineering and Technology

International Journal of System Assurance Engineering and Management, 2022, vol. 13, issue 4, No 26, 1885-1894

Abstract: Abstract Reactive power planning problem has received a considerable amount of attention for the allocation of reactive power resources, both static and dynamic such as switchable capacitors and/or reactors, as well as Var compensators like different types of FACTS devices. The reactive power has a significant impact on node voltages and transmission loss in connected power network. In the present work, Moth-flame optimization (MFO) algorithm has been proposed for reactive power planning by properly sizing of Static VAr Compensator (SVC), Thyristor Controlled Switched Capacitor (TCSC), Thyristor Controlled Phase Angle Regulator (TCPAR) and controlling reactive power generation of the generators along with transformer tap settings at the same time. The L-index method is used to select weak nodes in the power system for SVC’s placement, the reactive power flow in lines determines the location of TCSC’s and the loss sensitivity determines the location of TCPAR. The suggested technique is tested on conventional IEEE 57 bus networks, with simulation results obtained under both normal and fluctuating reactive power loads, making the reactive power planning problem more difficult to solve. The proposed approach reduces the transmission losses by 9.21% in 100% loading, 11.08% in 130% loading and 9.79% in 150% loading. From the obtained results, it is found that the proposed method shows better performance when compared to other techniques suggested in the literature in terms of reduced reactive power flow, active power loss and system operating cost.

Keywords: Loss reduction; Optimal power flow; Economical operation; Moth-flame optimization (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s13198-021-01588-9

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