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Optimal coordinated scheduling of combined heat and power fuel cell, wind, and photovoltaic units in micro grids considering uncertainties

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  • Bornapour, Mosayeb
  • Hooshmand, Rahmat-Allah
  • Khodabakhshian, Amin
  • Parastegari, Moein

Abstract

In this paper, a stochastic model is proposed for coordinated scheduling of combined heat and power units in micro grid considering wind turbine and photovoltaic units. Uncertainties of electrical market price; the speed of wind and solar radiation are considered using a scenario-based method. In the method, scenarios are generated using roulette wheel mechanism based on probability distribution functions of input random variables. Using this method, the probabilistic specifics of the problem are distributed and the problem is converted to a deterministic one. The type of the objective function, coordinated scheduling of combined heat and power, wind turbine, and photovoltaic units change this problem to a mixed integer nonlinear one. Therefore to solve this problem modified particle swarm optimization algorithm is employed. The mentioned uncertainties lead to an increase in profit. Moreover, the optimal coordinated scheduling of renewable energy resources and thermal units in micro grids increase the total profit. In order to evaluate the performance of the proposed method, its performance is executed on modified 33 bus distributed system as a micro grid.

Suggested Citation

  • Bornapour, Mosayeb & Hooshmand, Rahmat-Allah & Khodabakhshian, Amin & Parastegari, Moein, 2016. "Optimal coordinated scheduling of combined heat and power fuel cell, wind, and photovoltaic units in micro grids considering uncertainties," Energy, Elsevier, vol. 117(P1), pages 176-189.
    • Handle: RePEc:eee:energy:v:117:y:2016:i:p1:p:176-189
    DOI: 10.1016/j.energy.2016.10.072
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    1. Holjevac, Ninoslav & Capuder, Tomislav & Kuzle, Igor, 2015. "Adaptive control for evaluation of flexibility benefits in microgrid systems," Energy, Elsevier, vol. 92(P3), pages 487-504.
    2. Wang, Chengshan & Liu, Yixin & Li, Xialin & Guo, Li & Qiao, Lei & Lu, Hai, 2016. "Energy management system for stand-alone diesel-wind-biomass microgrid with energy storage system," Energy, Elsevier, vol. 97(C), pages 90-104.
    3. Singh, Parm Pal & Singh, Sukhmeet, 2010. "Realistic generation cost of solar photovoltaic electricity," Renewable Energy, Elsevier, vol. 35(3), pages 563-569.
    4. Bornapour, Mosayeb & Hooshmand, Rahmat-Allah, 2015. "An efficient scenario-based stochastic programming for optimal planning of combined heat, power, and hydrogen production of molten carbonate fuel cell power plants," Energy, Elsevier, vol. 83(C), pages 734-748.
    5. Zare, Mohsen & Niknam, Taher, 2013. "A new multi-objective for environmental and economic management of Volt/Var Control considering renewable energy resources," Energy, Elsevier, vol. 55(C), pages 236-252.
    6. 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.
    7. Ferruzzi, Gabriella & Cervone, Guido & Delle Monache, Luca & Graditi, Giorgio & Jacobone, Francesca, 2016. "Optimal bidding in a Day-Ahead energy market for Micro Grid under uncertainty in renewable energy production," Energy, Elsevier, vol. 106(C), pages 194-202.
    8. Sreedharan, P. & Farbes, J. & Cutter, E. & Woo, C.K. & Wang, J., 2016. "Microgrid and renewable generation integration: University of California, San Diego," Applied Energy, Elsevier, vol. 169(C), pages 709-720.
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    5. Bornapour, Mosayeb & Hooshmand, Rahmat-Allah & Khodabakhshian, Amin & Parastegari, Moein, 2017. "Optimal stochastic coordinated scheduling of proton exchange membrane fuel cell-combined heat and power, wind and photovoltaic units in micro grids considering hydrogen storage," Applied Energy, Elsevier, vol. 202(C), pages 308-322.
    6. Bornapour, Mosayeb & Hooshmand, Rahmat-Allah & Parastegari, Moein, 2019. "An efficient scenario-based stochastic programming method for optimal scheduling of CHP-PEMFC, WT, PV and hydrogen storage units in micro grids," Renewable Energy, Elsevier, vol. 130(C), pages 1049-1066.
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