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Tri-level optimization of industrial microgrids considering renewable energy sources, combined heat and power units, thermal and electrical storage systems

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Listed:
  • Misaghian, M.S.
  • Saffari, M.
  • Kia, M.
  • Heidari, A.
  • Shafie-khah, M.
  • Catalão, J.P.S.

Abstract

This paper presents a new framework for optimizing the operation of Industrial MicroGrids (IMG). The proposed framework consists of three levels. At the first level, a Profit Based Security Constrained Unit Commitment (PB-SCUC) is solved in order to minimize the total expected cost of IMG via maximizing the IMG revenue by transacting in the day-ahead power market and optimizing the scheduling of the units. In this paper, the tendency of IMG for participating in the day-ahead power market is modelled as a quadric function. At the second level, a Security Constrained Unit Commitment is solved at the upper grid for minimizing the upper grid operation and guaranteeing its security. At this level, the accepted IMG bids in the day-ahead power market would be determined. Finally, at the third level, the IMG operator must settle its units on the basis of its accepted bids. Therefore, a rescheduling problem is solved in the third level. Notably, Renewable Energy Sources (RESs), Combined Heat and Power (CHP) units, thermal and electrical storage systems are considered in the IMG. As the RESs and day-ahead market price have stochastic behaviours, their uncertainty is taken into account by implementing stochastic programming. Further, different cases for grid-connected and island modes of IMG are discussed, and the advantages of utilizing RES and storage systems are given. The simulation results are provided based on the IEEE 18-bus test system for IMG and IEEE 30-bus test system for the upper grid.

Suggested Citation

  • Misaghian, M.S. & Saffari, M. & Kia, M. & Heidari, A. & Shafie-khah, M. & Catalão, J.P.S., 2018. "Tri-level optimization of industrial microgrids considering renewable energy sources, combined heat and power units, thermal and electrical storage systems," Energy, Elsevier, vol. 161(C), pages 396-411.
    • Handle: RePEc:eee:energy:v:161:y:2018:i:c:p:396-411
    DOI: 10.1016/j.energy.2018.07.103
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    References listed on IDEAS

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    1. Kia, Mohsen & Setayesh Nazar, Mehrdad & Sepasian, Mohammad Sadegh & Heidari, Alireza & Catalão, João P.S., 2017. "New framework for optimal scheduling of combined heat and power with electric and thermal storage systems considering industrial customers inter-zonal power exchanges," Energy, Elsevier, vol. 138(C), pages 1006-1015.
    2. Kia, Mohsen & Setayesh Nazar, Mehrdad & Sepasian, Mohammad Sadegh & Heidari, Alireza & Sharaf, Adel M., 2017. "Coordination of heat and power scheduling in micro-grid considering inter-zonal power exchanges," Energy, Elsevier, vol. 141(C), pages 519-536.
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    8. Alipour, Manijeh & Zare, Kazem & Mohammadi-Ivatloo, Behnam, 2016. "Optimal risk-constrained participation of industrial cogeneration systems in the day-ahead energy markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 421-432.
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    2. Nasiri, Nima & Mansour Saatloo, Amin & Mirzaei, Mohammad Amin & Ravadanegh, Sajad Najafi & Zare, Kazem & Mohammadi-ivatloo, Behnam & Marzband, Mousa, 2023. "A robust bi-level optimization framework for participation of multi-energy service providers in integrated power and natural gas markets," Applied Energy, Elsevier, vol. 340(C).
    3. Sina Eslamizadeh & Amineh Ghorbani & Yashar Araghi & Margot Weijnen, 2022. "Collaborative Renewable Energy Generation among Industries: The Role of Social Identity, Awareness and Institutional Design," Sustainability, MDPI, vol. 14(12), pages 1-25, June.
    4. Hamdi Abdi, 2023. "A Survey of Combined Heat and Power-Based Unit Commitment Problem: Optimization Algorithms, Case Studies, Challenges, and Future Directions," Mathematics, MDPI, vol. 11(19), pages 1-36, October.

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