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An Ant Colony Optimized MPPT for Standalone Hybrid PV-Wind Power System with Single Cuk Converter

Author

Listed:
  • Neeraj Priyadarshi

    (Department of Electrical Engineering, Birsa Institute of Technology (Trust), Ranchi 835217, India)

  • Vigna K. Ramachandaramurthy

    (Institute of Power Engineering, Department of Electrical Power Engineering, Universiti Tenaga Nasional, Kajang 43000, Malaysia)

  • Sanjeevikumar Padmanaban

    (Department of Energy Technology, Aalborg University, 6700 Esbjerg, Denmark)

  • Farooque Azam

    (School of Computing & Information Technology, REVA University, Bangalore 560064, India)

Abstract

This research work explains the practical realization of hybrid solar wind-based standalone power system with maximum power point tracker (MPPT) to produce electrical power in rural places (residential applications). The wind inspired Ant Colony Optimization (ACO)-based MPPT algorithm is employed for the purpose of fast and accurate tracking power from wind energy system. Fuzzy Logic Control (FLC) inverter controlling strategy is adopted in this presented work compared to classical proportional-integral (PI) control. Moreover, single Cuk converter is operated as impedance power adapter to execute MPPT functioning. Here, ACO-based MPPT has been implemented with no voltage and current extra circuit requirement compared to existing evolutionary algorithms single cuk converter is employed to improve conversion efficiency of converter by maximizing power stages. DC-link voltage can be regulated by placing Cuk converter Permanent Magnet Synchronous Generator (PMSG) linked rectifier and inverter. The proposed MPPT method is responsible for rapid battery charging and gives power dispersion of battery for hybrid PV-Wind system. ACO-based MPPT provides seven times faster convergence compared to the particle swarm optimization (PSO) algorithm for achievement of maximum power point (MPP) and tracking efficiency. Satisfactory practical results have been realized using the dSPACE (DS1104) platform that justify the superiority of proposed algorithms designed under various operating situations.

Suggested Citation

  • Neeraj Priyadarshi & Vigna K. Ramachandaramurthy & Sanjeevikumar Padmanaban & Farooque Azam, 2019. "An Ant Colony Optimized MPPT for Standalone Hybrid PV-Wind Power System with Single Cuk Converter," Energies, MDPI, vol. 12(1), pages 1-23, January.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:1:p:167-:d:194966
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    References listed on IDEAS

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    Cited by:

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    12. Youjie Ma & Long Tao & Xuesong Zhou & Wei Li & Xueqi Shi, 2019. "Analysis and Control of Wind Power Grid Integration Based on a Permanent Magnet Synchronous Generator Using a Fuzzy Logic System with Linear Extended State Observer," Energies, MDPI, vol. 12(15), pages 1-19, July.
    13. Chanuri Charin & Dahaman Ishak & Muhammad Ammirrul Atiqi Mohd Zainuri & Baharuddin Ismail & Turki Alsuwian & Adam R. H. Alhawari, 2022. "Modified Levy-based Particle Swarm Optimization (MLPSO) with Boost Converter for Local and Global Point Tracking," Energies, MDPI, vol. 15(19), pages 1-30, October.
    14. Kuei-Hsiang Chao & Muhammad Nursyam Rizal, 2021. "A Hybrid MPPT Controller Based on the Genetic Algorithm and Ant Colony Optimization for Photovoltaic Systems under Partially Shaded Conditions," Energies, MDPI, vol. 14(10), pages 1-17, May.
    15. Changsheng Yuan & Xuesong Zhou & Youjie Ma & Zhiqiang Gao & Yongliang Zhou & Chenglong Wang, 2020. "Improved Application of Third-Order LADRC in Wind Power Inverter," Energies, MDPI, vol. 13(17), pages 1-22, August.
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    17. Eltamaly, Ali M. & Al-Saud, M.S. & Abokhalil, Ahmed G. & Farh, Hassan M.H., 2020. "Simulation and experimental validation of fast adaptive particle swarm optimization strategy for photovoltaic global peak tracker under dynamic partial shading," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    18. Youjie Ma & Luyong Yang & Xuesong Zhou & Xia Yang & Yongliang Zhou & Bo Zhang, 2020. "Linear Active Disturbance Rejection Control for DC Bus Voltage Under Low-Voltage Ride-Through at the Grid-Side of Energy Storage System," Energies, MDPI, vol. 13(5), pages 1-22, March.
    19. Jayshree Pande & Paresh Nasikkar, 2023. "A Maximum Power Point Tracking Technique for a Wind Power System Based on the Trapezoidal Rule," Energies, MDPI, vol. 16(6), pages 1-18, March.

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