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An advanced real time energy management system for microgrids

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  • Elsied, Moataz
  • Oukaour, Amrane
  • Youssef, Tarek
  • Gualous, Hamid
  • Mohammed, Osama

Abstract

This paper presents an advanced Real-Time Energy Management System (RT-EMS) for Microgrid (MG) systems. The proposed strategy of RT-EMS capitalizes on the power of Genetic Algorithms (GAs) to minimize the energy cost and carbon dioxide emissions while maximizing the power of the available renewable energy resources. MATLAB-dSPACE Real-Time Interface Libraries (MLIB/MTRACE) are used as new tools to run the optimization code in Real-Time Operation (RTO). The communication system is developed based on ZigBee communication network which is designed to work in harsh radio environment where the control system is developed based on Advanced Lead-Lag Compensator (ALLC) which its parameters are tuned online to achieve fast convergence and good tracking response. The proposed RT-EMS along with its control and communication systems is experimentally tested to validate the results obtained from the optimization algorithm in a real MG testbed. The simulation and experimental results using real-world data highlight the effectiveness of the proposed RT-EMS for MGs applications.

Suggested Citation

  • Elsied, Moataz & Oukaour, Amrane & Youssef, Tarek & Gualous, Hamid & Mohammed, Osama, 2016. "An advanced real time energy management system for microgrids," Energy, Elsevier, vol. 114(C), pages 742-752.
    • Handle: RePEc:eee:energy:v:114:y:2016:i:c:p:742-752
    DOI: 10.1016/j.energy.2016.08.048
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    1. Niknam, Taher & Meymand, Hamed Zeinoddini & Mojarrad, Hasan Doagou, 2011. "An efficient algorithm for multi-objective optimal operation management of distribution network considering fuel cell power plants," Energy, Elsevier, vol. 36(1), pages 119-132.
    2. Ippolito, M.G. & Di Silvestre, M.L. & Riva Sanseverino, E. & Zizzo, G. & Graditi, G., 2014. "Multi-objective optimized management of electrical energy storage systems in an islanded network with renewable energy sources under different design scenarios," Energy, Elsevier, vol. 64(C), pages 648-662.
    3. Moghaddam, Amjad Anvari & Seifi, Alireza & Niknam, Taher & Alizadeh Pahlavani, Mohammad Reza, 2011. "Multi-objective operation management of a renewable MG (micro-grid) with back-up micro-turbine/fuel cell/battery hybrid power source," Energy, Elsevier, vol. 36(11), pages 6490-6507.
    4. Usman, Ahmad & Shami, Sajjad Haider, 2013. "Evolution of Communication Technologies for Smart Grid applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 191-199.
    5. Elsied, Moataz & Oukaour, Amrane & Gualous, Hamid & Hassan, Radwan, 2015. "Energy management and optimization in microgrid system based on green energy," Energy, Elsevier, vol. 84(C), pages 139-151.
    6. Chen, Yen-Haw & Lu, Su-Ying & Chang, Yung-Ruei & Lee, Ta-Tung & Hu, Ming-Che, 2013. "Economic analysis and optimal energy management models for microgrid systems: A case study in Taiwan," Applied Energy, Elsevier, vol. 103(C), pages 145-154.
    7. Niknam, Taher & Golestaneh, Faranak & Shafiei, Mehdi, 2013. "Probabilistic energy management of a renewable microgrid with hydrogen storage using self-adaptive charge search algorithm," Energy, Elsevier, vol. 49(C), pages 252-267.
    8. Justo, Jackson John & Mwasilu, Francis & Lee, Ju & Jung, Jin-Woo, 2013. "AC-microgrids versus DC-microgrids with distributed energy resources: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 387-405.
    9. Marzband, Mousa & Ghadimi, Majid & Sumper, Andreas & Domínguez-García, José Luis, 2014. "Experimental validation of a real-time energy management system using multi-period gravitational search algorithm for microgrids in islanded mode," Applied Energy, Elsevier, vol. 128(C), pages 164-174.
    10. Marzband, Mousa & Sumper, Andreas & Ruiz-Álvarez, Albert & Domínguez-García, José Luis & Tomoiagă, Bogdan, 2013. "Experimental evaluation of a real time energy management system for stand-alone microgrids in day-ahead markets," Applied Energy, Elsevier, vol. 106(C), pages 365-376.
    11. Lidula, N.W.A. & Rajapakse, A.D., 2011. "Microgrids research: A review of experimental microgrids and test systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 186-202, January.
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