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A joint approach for strategic bidding of a microgrid in energy and spinning reserve markets

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  • Gabriella Ferruzzi
  • Giorgio Graditi
  • Federico Rossi

Abstract

In the electricity market, short-term operation is organized in day-ahead and real-time stages. The two stages that are performed in different time intervals have reciprocal effects on each other. The paper shows the strategy of a microgrid that participates to both day-ahead energy and spinning reserve market. It is supposed that microgrid is managed by a prosumer, a decision maker who manages distributed energy sources, storage units, Information and Communication Technologies (ICT) elements, and loads involved in the grid. The strategy is formulated considering that all decisions about the amount of power to sell in both markets and the price links to the offer, must be taken contextually and at the same time, that is through a joint approach. In order to develop an optimal bidding strategy for energy markets, prosumer implements a nonlinear mixed integer optimization model: in this way, by aggregating and coordinating various distributed energy sources, including renewable energy sources, micro-turbines–electricity power plants, combined heat and power plants, heat production plants (boilers), and energy storage systems, prosumer is able to optimally allocate the capacities for energy and spinning reserve market and maximize its revenues from different markets. Moreover, it is considered that both generators and loads can take part in the reserve market. The demand participation happens through both shiftable and curtailable loads. Case studies based on microgrid with various distributed energy sources demonstrate the market behavior of the prosumer using the proposed bidding model.

Suggested Citation

  • Gabriella Ferruzzi & Giorgio Graditi & Federico Rossi, 2020. "A joint approach for strategic bidding of a microgrid in energy and spinning reserve markets," Energy & Environment, , vol. 31(1), pages 88-115, February.
  • Handle: RePEc:sae:engenv:v:31:y:2020:i:1:p:88-115
    DOI: 10.1177/0958305X18768128
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    References listed on IDEAS

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    1. Wang, Qi & Zhang, Chunyu & Ding, Yi & Xydis, George & Wang, Jianhui & Østergaard, Jacob, 2015. "Review of real-time electricity markets for integrating Distributed Energy Resources and Demand Response," Applied Energy, Elsevier, vol. 138(C), pages 695-706.
    2. Hao Bai & Shihong Miao & Xiaohong Ran & Chang Ye, 2015. "Optimal Dispatch Strategy of a Virtual Power Plant Containing Battery Switch Stations in a Unified Electricity Market," Energies, MDPI, vol. 8(3), pages 1-22, March.
    3. Kuznetsova, Elizaveta & Li, Yan-Fu & Ruiz, Carlos & Zio, Enrico, 2014. "An integrated framework of agent-based modelling and robust optimization for microgrid energy management," Applied Energy, Elsevier, vol. 129(C), pages 70-88.
    4. Tabar, Vahid Sohrabi & Jirdehi, Mehdi Ahmadi & Hemmati, Reza, 2017. "Energy management in microgrid based on the multi objective stochastic programming incorporating portable renewable energy resource as demand response option," Energy, Elsevier, vol. 118(C), pages 827-839.
    5. Zamani, Ali Ghahgharaee & Zakariazadeh, Alireza & Jadid, Shahram, 2016. "Day-ahead resource scheduling of a renewable energy based virtual power plant," Applied Energy, Elsevier, vol. 169(C), pages 324-340.
    6. Mingtao Yao & Zhaoguang Hu & Froylan Sifuentes & Ning Zhang, 2015. "Integrated Power Management of Conventional Units and Industrial Loads in China’s Ancillary Services Scheduling," Energies, MDPI, vol. 8(5), pages 1-23, May.
    7. Raineri, R. & Rios, S. & Schiele, D., 2006. "Technical and economic aspects of ancillary services markets in the electric power industry: an international comparison," Energy Policy, Elsevier, vol. 34(13), pages 1540-1555, September.
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    1. Nikpour, Ahmad & Nateghi, Abolfazl & Shafie-khah, Miadreza & Catalão, João P.S., 2021. "Day-ahead optimal bidding of microgrids considering uncertainties of price and renewable energy resources," Energy, Elsevier, vol. 227(C).

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