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Research Article

An Efficient Hybrid Technique for Power Flow Management in Smart Grid with Renewable Energy Resources

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Received 28 Aug 2020, Accepted 08 Nov 2020, Published online: 14 Dec 2020
 

ABSTRACT

In this paper, an optimal power flow management of a hybrid renewable energy source (HRES) with a hybrid approach is proposed. Here, the proposed method is the consolidation of Improved Bear Smell Search (IBSS) and Sparrow Search Algorithm (SSA); hence, it is named as IB4SA technique. Here, the IBSS generates the voltage source inverter control signals based on the power exchange variety between the source side and load side. In the proposed work, the Bear Smell Search (BSS) is incorporated by crossover and mutation function, therefore it is named as IBSS. The multi-objective function is designed by the grid needed active with reactive power varieties generated based on the available source power. SSA process guarantees the detection of online control signals using a parallel implementation against active with reactive power varieties. The control method based on the proposed approach improves the control parameters of the power controller under power flow variations. The power flow management of the smart-grid system is controlled using the proposed technique based on variations in the parameters of the source and load side. The proposed technique is responsible for controlling energy sources using both renewable energy sources and energy storage devices, in order to generate the power requirement by the grid. The proposed approach is executed in MATLAB/Simulink work site and the performance is analyzed with the existing approaches. The statistical analysis for Case 1, 2, and 3 using proposed as well as existing approaches are analyzed. In Case 1, using the proposed technique the parameter of ΔId with mean represents 0.528, median represents 0.512 and standard deviation represents 0.033. In Case 2, using the proposed technique the parameter of ΔIqwith mean implies 0.671, median implies 0.656, and standard deviation implies 0.026.

Additional information

Notes on contributors

Sureshkumar Kumaravel

Sureshkumar Kumaravelcompleted his B.E., degree in Electrical and Electronics Engineering from Government College of Technology, Coimbatore, Tamilnadu, in 1999 and M.E., degree in Applied Electronics from Coimbatore Institute of Technology, Coimbatore, Tamilnadu, in 2002. He received his PhD., from Anna University, Chennai, in 2016. He is currently working as Associate Professor in the department of EEE, Velammal Engineering College, Chennai, Tamilnadu, His research interests are in the area of Power Quality and Renewable Energy Systems.

Vijayakumar Ponnusamy

Vijayakumar Ponnusamy  graduated  in Electrical and Electronics Engineering from PSG College of Technology, Coimbatore, Tamilnadu, in 1992. He obtained his Post Graduation degree in Applied Electronics from PSG College of Technology, Coimbatore, Tamilnadu, in 2002 and PhD in Low Power VLSI Design from Anna University, Chennai, Tamilnadu in 2007. His areas of interest include VLSI Design, Instrumentation and Automation. At present he is working as  Principal in Karpagam College of Engineering, Coimbatore, Tamilnadu. Other than 21 years of teaching experience and 7 years of industrial experience under his belt, he has to his credit more than 60 papers published in International and National Journals. He has also presented more than 35 papers in various National and International conferences. He has successfully guided 7 PhD scholars and 8 scholars are currently pursuing PhD under him. He is a member of IEEE, ISTE, VSI and SSI.

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