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A flexible and efficient multi-agent gas turbine power plant energy management system with economic and environmental constraints

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  • Roche, Robin
  • Idoumghar, Lhassane
  • Suryanarayanan, Siddharth
  • Daggag, Mounir
  • Solacolu, Christian-Anghel
  • Miraoui, Abdellatif

Abstract

Gas turbine power plants have characteristics that make them well-suited for applications where fast dynamics and high outputs are required, for example to accommodate variable load profiles and intermittent energy sources. However, this flexibility comes at a cost: these plants are much more expensive to operate than other types of power plants. This article proposes a new energy management system that enables a flexible and efficient operation of gas power plants. It is based on a multi-agent system combined with an economic and environmental dispatch algorithm obtained through an optimization algorithm based on differential evolution. Simulation results for a test system based on actual data of a GE 9E turbine show that the system helps reducing operation costs by up 4.7% and NOx emissions by up to 20.5%, and can be used with a large variety of gas power plants, as well as be adapted to evolutions in the plant structure.

Suggested Citation

  • Roche, Robin & Idoumghar, Lhassane & Suryanarayanan, Siddharth & Daggag, Mounir & Solacolu, Christian-Anghel & Miraoui, Abdellatif, 2013. "A flexible and efficient multi-agent gas turbine power plant energy management system with economic and environmental constraints," Applied Energy, Elsevier, vol. 101(C), pages 644-654.
  • Handle: RePEc:eee:appene:v:101:y:2013:i:c:p:644-654
    DOI: 10.1016/j.apenergy.2012.07.011
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    1. El-Shirbeeny, El-Hosseiny T. & Kadum, Muhamud K., 1986. "Review of current communication schemes for electric energy management," Energy, Elsevier, vol. 11(7), pages 679-683.
    2. El-Shirbeeny, El-Hosseiny T. & Kadum, Mahmud K., 1986. "Communication schemes for electric energy management," Applied Energy, Elsevier, vol. 24(4), pages 277-286.
    3. Alsumait, J.S. & Sykulski, J.K. & Al-Othman, A.K., 2010. "A hybrid GA-PS-SQP method to solve power system valve-point economic dispatch problems," Applied Energy, Elsevier, vol. 87(5), pages 1773-1781, May.
    4. Niknam, Taher & Mojarrad, Hassan Doagou & Nayeripour, Majid, 2010. "A new fuzzy adaptive particle swarm optimization for non-smooth economic dispatch," Energy, Elsevier, vol. 35(4), pages 1764-1778.
    5. Niknam, Taher, 2010. "A new fuzzy adaptive hybrid particle swarm optimization algorithm for non-linear, non-smooth and non-convex economic dispatch problem," Applied Energy, Elsevier, vol. 87(1), pages 327-339, January.
    6. De Jonghe, Cedric & Delarue, Erik & Belmans, Ronnie & D'haeseleer, William, 2011. "Determining optimal electricity technology mix with high level of wind power penetration," Applied Energy, Elsevier, vol. 88(6), pages 2231-2238, June.
    7. Vahidinasab, V. & Jadid, S., 2009. "Multiobjective environmental/techno-economic approach for strategic bidding in energy markets," Applied Energy, Elsevier, vol. 86(4), pages 496-504, April.
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    Cited by:

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    5. Celik, Berk & Roche, Robin & Suryanarayanan, Siddharth & Bouquain, David & Miraoui, Abdellatif, 2017. "Electric energy management in residential areas through coordination of multiple smart homes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 260-275.
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    7. Bhowmik, Chiranjib & Bhowmik, Sumit & Ray, Amitava & Pandey, Krishna Murari, 2017. "Optimal green energy planning for sustainable development: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 796-813.
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