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Intelligent demand side energy management system for autonomous polygeneration microgrids

Author

Listed:
  • Kyriakarakos, George
  • Piromalis, Dimitrios D.
  • Dounis, Anastasios I.
  • Arvanitis, Konstantinos G.
  • Papadakis, George

Abstract

Autonomous polygeneration microgrids is a novel approach in addressing the needs of remote areas. These needs can include power, fuel for transportation in the form of hydrogen, potable water through desalination and space heating and cooling. This approach has been investigated technically and economically and has proved viable. Further research has taken place in the supervisory management of this topology using computational intelligence techniques like fuzzy logic, which has optimized the concept minimizing the sizes of the installed components. The optimal design of the system can meet, though, only the design principles and needs. In reality experience has shown that most autonomous power systems operate out of specifications very shortly after installation or after a couple of years new needs arise and it is not possible economic wise for the people to extend it. In these cases the microgrid would struggle to cover the increased needs and in the end fail, causing blackouts. A solution to this is partial load shedding in an intelligent manner. This paper presents a multi agent system for intelligent demand side management of the polygeneration microgrid topology which also includes grey prediction algorithms for better management. This approach can also be used for designing the optimal polygeneration microgrid for a given amount of an investment. The results show that the proposed intelligent demand side management system can address its design principles successfully and guaranty the most effective operation even in conditions near and over the limits of the design specification of the autonomous polygeneration microgrid.

Suggested Citation

  • Kyriakarakos, George & Piromalis, Dimitrios D. & Dounis, Anastasios I. & Arvanitis, Konstantinos G. & Papadakis, George, 2013. "Intelligent demand side energy management system for autonomous polygeneration microgrids," Applied Energy, Elsevier, vol. 103(C), pages 39-51.
  • Handle: RePEc:eee:appene:v:103:y:2013:i:c:p:39-51
    DOI: 10.1016/j.apenergy.2012.10.011
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    References listed on IDEAS

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    1. Erdinc, O. & Uzunoglu, M., 2012. "Optimum design of hybrid renewable energy systems: Overview of different approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1412-1425.
    2. Matallanas, E. & Castillo-Cagigal, M. & Gutiérrez, A. & Monasterio-Huelin, F. & Caamaño-Martín, E. & Masa, D. & Jiménez-Leube, J., 2012. "Neural network controller for Active Demand-Side Management with PV energy in the residential sector," Applied Energy, Elsevier, vol. 91(1), pages 90-97.
    3. Kyriakarakos, George & Dounis, Anastasios I. & Arvanitis, Konstantinos G. & Papadakis, George, 2012. "A fuzzy logic energy management system for polygeneration microgrids," Renewable Energy, Elsevier, vol. 41(C), pages 315-327.
    4. Kyriakarakos, George & Dounis, Anastasios I. & Rozakis, Stelios & Arvanitis, Konstantinos G. & Papadakis, George, 2011. "Polygeneration microgrids: A viable solution in remote areas for supplying power, potable water and hydrogen as transportation fuel," Applied Energy, Elsevier, vol. 88(12), pages 4517-4526.
    5. Sperber, Allison N. & Elmore, Andrew Curtis & Crow, Mariesa L. & Cawlfield, Jeffrey D., 2012. "Performance evaluation of energy efficient lighting associated with renewable energy applications," Renewable Energy, Elsevier, vol. 44(C), pages 423-430.
    6. Di Giorgio, Alessandro & Pimpinella, Laura, 2012. "An event driven Smart Home Controller enabling consumer economic saving and automated Demand Side Management," Applied Energy, Elsevier, vol. 96(C), pages 92-103.
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