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Probabilistic optimization in operation of energy hub with participation of renewable energy resources and demand response

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  • Rakipour, Davood
  • Barati, Hassan

Abstract

Optimal operation of energy systems is one of the main challenges in relation to economic discussions, flexibility and sustainable energy supply of these systems. In this paper, a combined energy system (CES)with the concept of energy hub, including electrical, heating and cooling hubs, is offered along with demand response programs (DRPS) of electrical and cooling, and also renewable energy resources (RERS) to study optimal operation of the proposed hub. This study is based on uncertainty modeling and scenario generation in electrical, heating and cooling demands, wind speed and solar irradiances well as in the price of energy carriers including electricity and natural gas. Monte Carlo method is used to generate different scenarios of uncertainties in the model. The optimization problem with the aim of maximizing the profit of energy hub with the presence of DRPS and RERS in four case studies has been done. A MILP formulation for the optimization problem is presented and solved using the CPLEX solver in GAMS software. The simulation results of the proposed model show an increase in energy hub profit, reducing the cost of purchased power from electricity grid as well as decreasing cost of operation.

Suggested Citation

  • Rakipour, Davood & Barati, Hassan, 2019. "Probabilistic optimization in operation of energy hub with participation of renewable energy resources and demand response," Energy, Elsevier, vol. 173(C), pages 384-399.
    • Handle: RePEc:eee:energy:v:173:y:2019:i:c:p:384-399
    DOI: 10.1016/j.energy.2019.02.021
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    References listed on IDEAS

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    1. Shams, Mohammad H. & Shahabi, Majid & Khodayar, Mohammad E., 2018. "Stochastic day-ahead scheduling of multiple energy Carrier microgrids with demand response," Energy, Elsevier, vol. 155(C), pages 326-338.
    2. Salehimaleh, Mohammad & Akbarimajd, Adel & Valipour, Khalil & Dejamkhooy, Abdolmajid, 2018. "Generalized modeling and optimal management of energy hub based electricity, heat and cooling demands," Energy, Elsevier, vol. 159(C), pages 669-685.
    3. Wang, Yi & Zhang, Ning & Zhuo, Zhenyu & Kang, Chongqing & Kirschen, Daniel, 2018. "Mixed-integer linear programming-based optimal configuration planning for energy hub: Starting from scratch," Applied Energy, Elsevier, vol. 210(C), pages 1141-1150.
    4. Kamyab, Farhad & Bahrami, Shahab, 2016. "Efficient operation of energy hubs in time-of-use and dynamic pricing electricity markets," Energy, Elsevier, vol. 106(C), pages 343-355.
    5. Ayele, Getnet Tadesse & Haurant, Pierrick & Laumert, Björn & Lacarrière, Bruno, 2018. "An extended energy hub approach for load flow analysis of highly coupled district energy networks: Illustration with electricity and heating," Applied Energy, Elsevier, vol. 212(C), pages 850-867.
    6. Ghaffarpour, Reza & Mozafari, Babak & Ranjbar, Ali Mohammad & Torabi, Taghi, 2018. "Resilience oriented water and energy hub scheduling considering maintenance constraint," Energy, Elsevier, vol. 158(C), pages 1092-1104.
    7. Najafi, Arsalan & Falaghi, Hamid & Contreras, Javier & Ramezani, Maryam, 2016. "Medium-term energy hub management subject to electricity price and wind uncertainty," Applied Energy, Elsevier, vol. 168(C), pages 418-433.
    8. Ottesen, Stig Odegaard & Tomasgard, Asgeir, 2015. "A stochastic model for scheduling energy flexibility in buildings," Energy, Elsevier, vol. 88(C), pages 364-376.
    9. 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.
    10. Hemmati, S. & Ghaderi, S.F. & Ghazizadeh, M.S., 2018. "Sustainable energy hub design under uncertainty using Benders decomposition method," Energy, Elsevier, vol. 143(C), pages 1029-1047.
    11. Baležentis, Tomas & Streimikiene, Dalia, 2017. "Multi-criteria ranking of energy generation scenarios with Monte Carlo simulation," Applied Energy, Elsevier, vol. 185(P1), pages 862-871.
    12. Sheikhi, Aras & Bahrami, Shahab & Ranjbar, Ali Mohammad, 2015. "An autonomous demand response program for electricity and natural gas networks in smart energy hubs," Energy, Elsevier, vol. 89(C), pages 490-499.
    13. Soares, João & Borges, Nuno & Fotouhi Ghazvini, Mohammad Ali & Vale, Zita & de Moura Oliveira, P.B., 2016. "Scenario generation for electric vehicles' uncertain behavior in a smart city environment," Energy, Elsevier, vol. 111(C), pages 664-675.
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