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A medium-term coalition-forming model of heterogeneous DERs for a commercial virtual power plant

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  • Shabanzadeh, Morteza
  • Sheikh-El-Eslami, Mohammad-Kazem
  • Haghifam, Mahmoud-Reza

Abstract

Within a medium-term market horizon, this research work provides a methodology that allows a commercial virtual power plant (CVPP) to form an optimal coalition of heterogeneous distributed energy resources (DERs) based on weekly bilateral contracting, futures-market involvement, and pool participation. The established model aims at composing an optimal portfolio of available DERs and jointly takes into account the risk associated with the energy trading strategy of the CVPP. Perceiving the fact that pool prices have highly uncertain nature, a framework based on stochastic programming approach is utilized to model this decision-making problem. The proposed framework consists of two stages. The first stage deals with decisions regarding DERs optimal selection for the VPP coalition, the amount of agreed quantity in the bilateral negotiation, and the type and quantity selection of futures-market contracts as well. In the second stage, decisions are made based on the most plausible realizations of the stochastic prices in the day-ahead market. For a given pre-specified risk level on profit volatility, the main objective is to maximize the expected profit for the VPP manager over the planning horizon. The efficiency and applicability of the developed model is illustrated and analyzed by its implementation in a system with few heterogeneous DERs and through different scenarios, and finally thereby meaningful conclusions are duly drawn.

Suggested Citation

  • Shabanzadeh, Morteza & Sheikh-El-Eslami, Mohammad-Kazem & Haghifam, Mahmoud-Reza, 2016. "A medium-term coalition-forming model of heterogeneous DERs for a commercial virtual power plant," Applied Energy, Elsevier, vol. 169(C), pages 663-681.
    • Handle: RePEc:eee:appene:v:169:y:2016:i:c:p:663-681
    DOI: 10.1016/j.apenergy.2016.02.058
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    1. Lima, Ricardo M. & Novais, Augusto Q. & Conejo, Antonio J., 2015. "Weekly self-scheduling, forward contracting, and pool involvement for an electricity producer. An adaptive robust optimization approach," European Journal of Operational Research, Elsevier, vol. 240(2), pages 457-475.
    2. Zhao, Haoran & Wu, Qiuwei & Hu, Shuju & Xu, Honghua & Rasmussen, Claus Nygaard, 2015. "Review of energy storage system for wind power integration support," Applied Energy, Elsevier, vol. 137(C), pages 545-553.
    3. Tascikaraoglu, A. & Erdinc, O. & Uzunoglu, M. & Karakas, A., 2014. "An adaptive load dispatching and forecasting strategy for a virtual power plant including renewable energy conversion units," Applied Energy, Elsevier, vol. 119(C), pages 445-453.
    4. Pandžić, Hrvoje & Kuzle, Igor & Capuder, Tomislav, 2013. "Virtual power plant mid-term dispatch optimization," Applied Energy, Elsevier, vol. 101(C), pages 134-141.
    5. Deng, S.J. & Oren, S.S., 2006. "Electricity derivatives and risk management," Energy, Elsevier, vol. 31(6), pages 940-953.
    6. Pineda, S. & Conejo, A.J., 2012. "Managing the financial risks of electricity producers using options," Energy Economics, Elsevier, vol. 34(6), pages 2216-2227.
    7. Pandžić, Hrvoje & Morales, Juan M. & Conejo, Antonio J. & Kuzle, Igor, 2013. "Offering model for a virtual power plant based on stochastic programming," Applied Energy, Elsevier, vol. 105(C), pages 282-292.
    8. Bradbury, Kyle & Pratson, Lincoln & Patiño-Echeverri, Dalia, 2014. "Economic viability of energy storage systems based on price arbitrage potential in real-time U.S. electricity markets," Applied Energy, Elsevier, vol. 114(C), pages 512-519.
    9. Arslan, Okan & Karasan, Oya Ekin, 2013. "Cost and emission impacts of virtual power plant formation in plug-in hybrid electric vehicle penetrated networks," Energy, Elsevier, vol. 60(C), pages 116-124.
    10. Chavas, Jean-Paul, 2004. "Risk Analysis in Theory and Practice," Elsevier Monographs, Elsevier, edition 1, number 9780121706210.
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    19. Abubaker Basheer Abdalwhab Altohami & Nuzul Azam Haron & Aidi Hizami Ales@Alias & Teik Hua Law, 2021. "Investigating Approaches of Integrating BIM, IoT, and Facility Management for Renovating Existing Buildings: A Review," Sustainability, MDPI, vol. 13(7), pages 1-30, April.
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    21. Yu, Songyuan & Fang, Fang & Liu, Yajuan & Liu, Jizhen, 2019. "Uncertainties of virtual power plant: Problems and countermeasures," Applied Energy, Elsevier, vol. 239(C), pages 454-470.
    22. Nosratabadi, Seyyed Mostafa & Hooshmand, Rahmat-Allah & Gholipour, Eskandar, 2017. "A comprehensive review on microgrid and virtual power plant concepts employed for distributed energy resources scheduling in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 341-363.
    23. Moreno, Blanca & Díaz, Guzmán, 2019. "The impact of virtual power plant technology composition on wholesale electricity prices: A comparative study of some European Union electricity markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 99(C), pages 100-108.
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