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Optimal bidding strategy for an energy hub in energy market

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  • Davatgaran, Vahid
  • Saniei, Mohsen
  • Mortazavi, Seyed Saeidollah

Abstract

An energy hub, as an active element in smart distribution grid, can participate in the day-ahead market via submitting bids to maximize its profit. The multi-input and multi-output energy vectors make energy hub different from other active elements. In this paper, a comprehensive optimal bidding strategy for an energy hub is modeled. The proposed model enables the energy hub to benefit from day-ahead and real-time markets. Stochastic optimization is proposed in this strategy to handle several market uncertainties consisting of day-ahead market prices, real-time market prices, and wind generation. The model takes advantages of multi-inputs vector of energy hub to submit the optimal bids including electricity selling/buying and optimizes the cost. Moreover, it handles the coupling between different types of loads. The problem is modeled as a mixed integer linear program. Numerical simulations evaluate the proposed model.

Suggested Citation

  • Davatgaran, Vahid & Saniei, Mohsen & Mortazavi, Seyed Saeidollah, 2018. "Optimal bidding strategy for an energy hub in energy market," Energy, Elsevier, vol. 148(C), pages 482-493.
  • Handle: RePEc:eee:energy:v:148:y:2018:i:c:p:482-493
    DOI: 10.1016/j.energy.2018.01.174
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    References listed on IDEAS

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    1. Evins, Ralph & Orehounig, Kristina & Dorer, Viktor & Carmeliet, Jan, 2014. "New formulations of the ‘energy hub’ model to address operational constraints," Energy, Elsevier, vol. 73(C), pages 387-398.
    2. Allegrini, Jonas & Orehounig, Kristina & Mavromatidis, Georgios & Ruesch, Florian & Dorer, Viktor & Evins, Ralph, 2015. "A review of modelling approaches and tools for the simulation of district-scale energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1391-1404.
    3. Ottesen, Stig Odegaard & Tomasgard, Asgeir, 2015. "A stochastic model for scheduling energy flexibility in buildings," Energy, Elsevier, vol. 88(C), pages 364-376.
    4. Antonio J. Conejo & Miguel Carrión & Juan M. Morales, 2010. "Decision Making Under Uncertainty in Electricity Markets," International Series in Operations Research and Management Science, Springer, number 978-1-4419-7421-1, April.
    5. Moghaddam, Iman Gerami & Saniei, Mohsen & Mashhour, Elaheh, 2016. "A comprehensive model for self-scheduling an energy hub to supply cooling, heating and electrical demands of a building," Energy, Elsevier, vol. 94(C), pages 157-170.
    6. Chicco, Gianfranco & Mancarella, Pierluigi, 2009. "Matrix modelling of small-scale trigeneration systems and application to operational optimization," Energy, Elsevier, vol. 34(3), pages 261-273.
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