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Fuzzy-Based Shunt VAR Source Placement and Sizing by Oppositional Crow Search Algorithm

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Abstract

In a typical power system network, transmission losses are considered as one of the important parameters for economic operation. To concern this problem, researchers have proposed many techniques to minimize the transmission losses based on the cost benefit analysis which is associated with the optimal placement of the reactive power sources. In the present work, a novel technique, namely oppositional crow search algorithm (CSA), is proposed for Var planning by utilizing the fuzzy logic technique to determine capacitor placement positions. In this approach, fuzzy membership value is calculated based on the loss sensitivity factor of each bus of the test networks. Then, shunt capacitors placement positions are assigned to buses having the higher membership values. Once the capacitor placement positions are evaluated, the CSA and oppositional CSA are executed to obtain the optimal setting of transformer tap positions, reactive power generation of the generators, and magnitude of shunt capacitors placed at the weak nodes. The proposed method is performed on standard IEEE 30 and IEEE 57 bus networks, and the obtained results are compared with several other established methods for Var planning. 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 active power loss and system operating cost.

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SR was mainly involved in coding and developing the optimization codes and implements them to attain the mentioned. CKS, SSG and BV has major contributor in writing the manuscript. RB has helped in revision. BB supervised the manuscript. All authors read and approved the final manuscript.

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Correspondence to Swetha Shekarappa Gudadappanavar, Basetti Vedik, Rohit Babu or Saurav Raj.

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Shiva, C.K., Gudadappanavar, S.S., Vedik, B. et al. Fuzzy-Based Shunt VAR Source Placement and Sizing by Oppositional Crow Search Algorithm. J Control Autom Electr Syst 33, 1576–1591 (2022). https://doi.org/10.1007/s40313-022-00903-4

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  • DOI: https://doi.org/10.1007/s40313-022-00903-4

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