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Model Predictive Control Based Energy Management System Literature Assessment for RES Integration

Author

Listed:
  • Nor Liza Tumeran

    (Electrical and Computer Engineering Department, International Islamic University Malaysia, Kuala Lumpur 53100, Malaysia)

  • Siti Hajar Yusoff

    (Electrical and Computer Engineering Department, International Islamic University Malaysia, Kuala Lumpur 53100, Malaysia)

  • Teddy Surya Gunawan

    (Electrical and Computer Engineering Department, International Islamic University Malaysia, Kuala Lumpur 53100, Malaysia)

  • Mohd Shahrin Abu Hanifah

    (Electrical and Computer Engineering Department, International Islamic University Malaysia, Kuala Lumpur 53100, Malaysia)

  • Suriza Ahmad Zabidi

    (Electrical and Computer Engineering Department, International Islamic University Malaysia, Kuala Lumpur 53100, Malaysia)

  • Bernardi Pranggono

    (School of Computing and Information Science, Anglia Ruskin University, Cambridge CB1 1PT, UK)

  • Muhammad Sharir Fathullah Mohd Yunus

    (Electrical and Computer Engineering Department, International Islamic University Malaysia, Kuala Lumpur 53100, Malaysia)

  • Siti Nadiah Mohd Sapihie

    (Petronas Research Sdn Bhd, Bandar Baru Bangi 43000, Malaysia)

  • Asmaa Hani Halbouni

    (Electrical and Computer Engineering Department, International Islamic University Malaysia, Kuala Lumpur 53100, Malaysia)

Abstract

Over the past few decades, the electric power industry evolved in response to growing concerns about climate change and the rising price of fossil fuels. The usage of renewable energy sources (RES) rose as a remedy for these problems. The increased penetration of RES in the existing generation system increased the need for an intelligent energy management system (EMS) so that the system can operate in any possible circumstances. Many sectors of society, including the education sector, are working to realize the importance of this sustainable energy system. This paper reviews the process of selecting an efficient control technique for continuous power flow from different RES to meet the load demand requirement using an enhanced model predictive control (MPC)-based EMS framework. This EMS is a software platform to provide fundamental support services and applications to deliver the functionality needed for the effective operation of electrical generation and transmission facilities to ensure adequate security of energy supply at minimum cost. The centralized EMS with technical objectives focusing on power quality and seamless power flow can be achieved through dynamically enhanced MPC.

Suggested Citation

  • Nor Liza Tumeran & Siti Hajar Yusoff & Teddy Surya Gunawan & Mohd Shahrin Abu Hanifah & Suriza Ahmad Zabidi & Bernardi Pranggono & Muhammad Sharir Fathullah Mohd Yunus & Siti Nadiah Mohd Sapihie & Asm, 2023. "Model Predictive Control Based Energy Management System Literature Assessment for RES Integration," Energies, MDPI, vol. 16(8), pages 1-27, April.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:8:p:3362-:d:1120672
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    References listed on IDEAS

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    Cited by:

    1. Saqib Iqbal & Kamyar Mehran, 2024. "Data-Driven Management Systems for Wave-Powered Renewable Energy Communities," Energies, MDPI, vol. 17(5), pages 1-19, March.
    2. Israth Jahan Chowdhury & Siti Hajar Yusoff & Teddy Surya Gunawan & Suriza Ahmad Zabidi & Mohd Shahrin Bin Abu Hanifah & Siti Nadiah Mohd Sapihie & Bernardi Pranggono, 2024. "Analysis of Model Predictive Control-Based Energy Management System Performance to Enhance Energy Transmission," Energies, MDPI, vol. 17(11), pages 1-19, May.

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