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A Comparative Analysis of Peak Load Shaving Strategies for Isolated Microgrid Using Actual Data

Author

Listed:
  • Md Masud Rana

    (Centre for Smart Grid Energy Research (CSMER), Electrical and Electronic Engineering Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak, Malaysia)

  • Akhlaqur Rahman

    (Department of Electrical Engineering and Industrial Automation, Melbourne Campus, Engineering Institute of Technology, Melbourne, VIC 3001, Australia)

  • Moslem Uddin

    (School of Engineering & Information Technology, The University of New South Wales, Canberra, ACT 2610, Australia)

  • Md Rasel Sarkar

    (School of Engineering & Information Technology, The University of New South Wales, Canberra, ACT 2610, Australia)

  • Sk. A. Shezan

    (Department of Electrical Engineering and Industrial Automation, Melbourne Campus, Engineering Institute of Technology, Melbourne, VIC 3001, Australia)

  • Md. Fatin Ishraque

    (Department of Electrical, Electronic and Communication Engineering, Pabna University of Science and Technology, Pabna 6600, Bangladesh)

  • S M Sajjad Hossain Rafin

    (School of Engineering and Built Environment, Griffith University, Gold Coast, QLD 4215, Australia)

  • Mohamed Atef

    (Centre for Smart Grid Energy Research (CSMER), Electrical and Electronic Engineering Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak, Malaysia)

Abstract

Peak load reduction is one of the most essential obligations and cost-effective tasks for electrical energy consumers. An isolated microgrid (IMG) system is an independent limited capacity power system where the peak shaving application can perform a vital role in the economic operation. This paper presents a comparative analysis of a categorical variable decision tree algorithm (CVDTA) with the most common peak shaving technique, namely, the general capacity addition technique, to evaluate the peak shaving performance for an IMG system. The CVDTA algorithm deals with the hybrid photovoltaic (PV)—battery energy storage system (BESS) to provide the peak shaving service where the capacity addition technique uses a peaking generator to minimize the peak demand. An actual IMG system model is developed in MATLAB/Simulink software to analyze the peak shaving performance. The model consists of four major components such as, PV, BESS, variable load, and gas turbine generator (GTG) dispatch models for the proposed algorithm, where the BESS and PV models are not applicable for the capacity addition technique. Actual variable load data and PV generation data are considered to conduct the simulation case studies which are collected from a real IMG system. The simulation result exhibits the effectiveness of the CVDTA algorithm which can minimize the peak demand better than the capacity addition technique. By ensuring the peak shaving operation and handling the economic generation dispatch, the CVDTA algorithm can ensure more energy savings, fewer system losses, less operation and maintenance (O&M) cost, etc., where the general capacity addition technique is limited.

Suggested Citation

  • Md Masud Rana & Akhlaqur Rahman & Moslem Uddin & Md Rasel Sarkar & Sk. A. Shezan & Md. Fatin Ishraque & S M Sajjad Hossain Rafin & Mohamed Atef, 2022. "A Comparative Analysis of Peak Load Shaving Strategies for Isolated Microgrid Using Actual Data," Energies, MDPI, vol. 15(1), pages 1-16, January.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:1:p:330-:d:717222
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    References listed on IDEAS

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    1. Zhang, Yan & Fu, Lijun & Zhu, Wanlu & Bao, Xianqiang & Liu, Cang, 2018. "Robust model predictive control for optimal energy management of island microgrids with uncertainties," Energy, Elsevier, vol. 164(C), pages 1229-1241.
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    Cited by:

    1. Tee, Wei Hown & Gan, Chin Kim & Sardi, Junainah, 2024. "Benefits of energy storage systems and its potential applications in Malaysia: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    2. Md Masud Rana & Mohamed Atef & Md Rasel Sarkar & Moslem Uddin & GM Shafiullah, 2022. "A Review on Peak Load Shaving in Microgrid—Potential Benefits, Challenges, and Future Trend," Energies, MDPI, vol. 15(6), pages 1-17, March.
    3. Hossam M. Hussein & Ahmed Aghmadi & Mahmoud S. Abdelrahman & S M Sajjad Hossain Rafin & Osama Mohammed, 2024. "A review of battery state of charge estimation and management systems: Models and future prospective," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 13(1), January.
    4. Sk. A. Shezan & Innocent Kamwa & Md. Fatin Ishraque & S. M. Muyeen & Kazi Nazmul Hasan & R. Saidur & Syed Muhammad Rizvi & Md Shafiullah & Fahad A. Al-Sulaiman, 2023. "Evaluation of Different Optimization Techniques and Control Strategies of Hybrid Microgrid: A Review," Energies, MDPI, vol. 16(4), pages 1-30, February.
    5. Md. Fatin Ishraque & Akhlaqur Rahman & Sk. A. Shezan & S. M. Muyeen, 2022. "Grid Connected Microgrid Optimization and Control for a Coastal Island in the Indian Ocean," Sustainability, MDPI, vol. 14(24), pages 1-22, December.
    6. Md Masud Rana & Akhlaqur Rahman & Moslem Uddin & Md Rasel Sarkar & SK. A. Shezan & C M F S Reza & Md. Fatin Ishraque & Mohammad Belayet Hossain, 2022. "Efficient Energy Distribution for Smart Household Applications," Energies, MDPI, vol. 15(6), pages 1-19, March.

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