Assistant Professor

Dr Mrutyunjaya Mangaraj

Department of Electrical and Electronics Engineering

Interests

  • Power Quality
  • Renewable Energy Integration
  • Artificial Intelligence

Faculty Details

Education

2006

Berhampur University
India
B E

2010

VSSUT Burla
India
MTech

2018

NIT Rourkela
India
PhD

Experience

  • 2023- Reviewer– Electric Power Component & System
  • 2022- Reviewer– Electric Power Component & System
  • 2021- Reviewer– Electric Power Component & System
  • 2020- Reviewer– Electric Power Component & System
  • 2019- Reviewer– IET Power Electronics
  • 2019- Reviewer– IET Generation, Transmission & Distribution
  • 2018 – Reviewer– IET Generation, Transmission & Distribution
  • 2018 – Reviewer–IET Power Electronics
  • 2018 – Reviewer–IET Power Electronics
  • 2017 – Reviewer–IET Generation, Transmission & Distribution

    • Research Interests

  • Design and Experimental Validation of DSTATCOM Using Various Hybrid ANN Techniques
  • Distributed Energy Renewable Integrated Back-to-Back VSI Based DSTATCOM for Micro Grid
  • Inductively coupled distributed static compensator for power quality analysis

    • Awards & Fellowships

  • 2019 – Start-up Research Grant – SERB-DST, New Delhi
  • 2014-2018- Institute Fellowship- MHRD, New Delhi

    • Memberships

    • MISTE
    • LMISTE
    • MIEEE

    Patents

    • Title:201941054849, Patent Application No: Smart Wind Farm Management System, Authors:M. Mangaraj, R. Kampara, B.Sahoo, A K Chahattaray, M Satish and KS Rao
    • Title:201931052205, Patent Application No: Multimodality Transportation System, Authors:M. Mangaraj, K. Ravisankar and A. K Chahattaray

    List of Publications

    • Journals:
    • (1) Sabat, J., Mangaraj, M., Kundala, P.K.Y. et al. Shunt compensation using Deep Belief Learning Network Based Inductively Coupled DSTATCOM. Energy System, Dec. 2023.
    • (2) S Mohanty, A Bhanja, SP Gautam, D Chittathuru, SK Dash, M Mangaraj, all “ Review of a Comprehensive Analysis of planning, Functionality, Control, and Protection for Direct Current Microgrids” International Journal of Sustainability (MDPI), vol. 15, no.21, pp. 15405-15433, Oct. 2023.
    • (3) Mangaraj, M., Pilla, R., Kumar, P.P. et al. “ Design and dynamic analysis of superconducting magnetic energy storage-based voltage source active power filter using deep Q-learning,” Electrical Engineering, (Springer) vol. 106, pp. 1241–1250, Jan. 2024.
    • (4) Sabat, J., Mangaraj, M., & Barisal, A.K. “Improvement of power quality in distribution utility using X-LMS based adaptive algorithm,” Electrical Engineering, Springer, vol.106, pp. 4575–4589, Feb. 2024.
    • (5) Mangaraj, Jogeswara Sabat , Ajit Kumar Barisal, “Experimental test performance for a comparative evaluation of a voltage source inverter: Dual voltage source inverter” Journal of Electrical Engineering, vol.75, no. 1, pp. 56-62, 2024,
    • (6) Sabat, J., Mangaraj, M. & Barisal, A.K. “ Power quality enhancement in utility grid using distributed energy resources integrated BBC-VSI based DSTATCOM”,  International Journal of System Assurance and Engineering Management, Springer, vol. 15, pp. 2677–2688, Mar. 2024.
    • (7) Mangaraj, Praveen Kumar Yadav Kundala, S Singh, “Modelling and Experimental Validation of DSTATCOM using Deep Belief Learning Network with Anti windup Regulator”, International Journal of Ambient Energy, Taylor & Francis, vol 45, no.1. May 2024.
    • (8) Mangaraj, S M Muyeen, B Chitti Babu, T K Nizami, S Singh, A Chakravarty, “ Deep Reinforced Learning Based Inductively Coupled DSTATCOM Under Load Uncertainties” International Journal of Electrical Engineering, Springer. May. 2024.
    • (9) Mangaraj, M., Nizami, T.K., Babu, B.C. et al.Realization of superconducting-magnetic energy storage supported DSTATCOM using deep Bayesian Active Learning. Electrical Engineering, Springer, 2024). https://doi.org/10.1007/s00202-024-02560-z.
    • DSTATCOM employing hybrid neural network control technique for power quality improvement- A.K. Panda and M. Mangaraj, IET Power Electronics, 10(4), 480-489, (2017).
    • Performance analysis of DSTATCOM employing various control algorithms- M. Mangaraj and A. K. Panda, IET Generation, Transmission & Distribution, 11(10), 2643-2653, (2017).
    • NBP-based icosϕ control strategy for DSTATCOM- M. Mangaraj and A. K. Panda, IET Power Electronics, 10 (12),1617 – 1625, (2017).
    • DSTATCOM deploying CGBP based icosϕ neural network technique for power conditioning- M. Mangaraj and A. K. Panda, International Journal of Ain Shams Engg. Journal (Elsevier), 9(4), 1535-1546, (2018).
    • Modelling and simulation of KHLMS algorithm-based DSTATCOM- M. Mangaraj and A.K Panda, IET Power Electronics, 12 (9), 2304 – 2311, (2019).
    • An Adaptive LMBP Training Based Control Technique for DSTATCOM- M. Mangaraj, A. K. Panda, T. Penthia and A. R. Dash, IET Generation, Transmission and Distribution, 14(3), 516–524, (2020).
    • Real-time simulation and Performance of DSTATCOM using an improved load current detection-based control technique for compensation of current harmonics and load transients- T. Penthia, A. K. Panda and M. Mangaraj, International Journal on European Power Electronics and Drives, 1 – 6, (2020).
    • Experimental validation of ADALINE least mean square algorithm in a three-phase four-wire DSTATCOM to enhance power quality- T. Penthia, A. K. Panda and M. Mangaraj, International Journal on Electric Power Components & Systems, 48(8), 769 – 780, (2020).
    • Sparse LMS Algorithm for Two-level DSTATCOM, - M. Mangaraj and A. K. Panda, IET Generation, Transmission and Distribution, 15(1), 86 – 96, 2021.
    • Operation of Hebbian Least Mean Square controlled distributed Static Compensator- M. Mangaraj, IET Generation, Transmission and Distribution, 15 (13), 1939 – 1948. ( 2021).
    • GLMS Control Strategy based DSTATCOM for Power Quality Enhancement: Modelling & Comparative Analysis- J. Sabat and M. Mangaraj, International Journal of Energy System, Oct. 2021. (DOI:10.1007/s12667-021-00489-x )
    • Operation and Control Performance of Interactive DZSI based DSTATOM- J. Sabat and M. Mangaraj, International Journal of Institution of Engineers: Series B, 103(4), 1259-1267, (2022).
    • PQ Assessment of EDS With DER Penetration by DVSI based DSTATCOM Using ALMS Algorithm- M. Mangaraj and J. Sabat, International Journal of Ambient Energy, pp. 7775-7786, (2022).
    • Experimental Study of T-I-VSI Based DSTATCOM using ALMS Technique for PQ Analysis- J Sabat and M Mangaraj, International Journal of Institution of Engineers: Series B, 104, 165–174 (2023).
    • FPGA Based Execution on DER Supported EDS for Enhanced PQ with OAPFC- M Mangaraj and J Sabat, International Journal of ECTI Transactions on Electrical Engineering, Electronics, and Communications. https://doi.org/10.37936/ecti-eec.2023211.248571. I.F: 0.83.
    • DER Integrated BTB-VSI Based DSTATCOM for PQ Enhancement- M Mangaraj and J Sabat, International Journal of Electronics, https://doi.org/10.1080/00207217.2023.2224069
    • MVSI and AVSI supported DSTATCOM for power quality analysis- M. Mangaraj and J. Sabat, IETE Journal of Research, 69 (6), 3852–3858, (2023).

    Contact Details

    TOP