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Operational scheduling of microgrids via parametric programming

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  • Umeozor, Evar Chinedu
  • Trifkovic, Milana

Abstract

We present a parametric programming based approach for energy management in microgrids. An operational planning problem for a grid-connected microgrid with energy sources including solar photovoltaic, wind turbine and battery energy storage system, in addition to a household load demand, is captured as a parametric mixed-integer linear programming problem (p-MILP) through parameterizations of the uncertain coordinates of wind and solar energy resources. Thus, the energy management problem - typically nonlinear - is transformed into a linear bi-level optimization problem, where choice of the parameterization scheme is made at the upper level while system operation decisions are made at the lower level. The p-MILP formulation leads to significant improvements in uncertainty handling, solution quality and computational ease; by removing dependency of the solution on meteorological forecasts and avoiding the multiple computational cycles of the traditional online optimization techniques. The problem is solved offline on a flexible time-scale basis, allowing online implementation to be achievable on real-time system state updates. The proposed parametric programming approach extends the state-of-the-art in microgrid energy management methods and the results from various case studies are used to demonstrate the feasibility of our method.

Suggested Citation

  • Umeozor, Evar Chinedu & Trifkovic, Milana, 2016. "Operational scheduling of microgrids via parametric programming," Applied Energy, Elsevier, vol. 180(C), pages 672-681.
  • Handle: RePEc:eee:appene:v:180:y:2016:i:c:p:672-681
    DOI: 10.1016/j.apenergy.2016.08.009
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    References listed on IDEAS

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    5. Mingyue He & Zahra Soltani & Mojdeh Khorsand & Aaron Dock & Patrick Malaty & Masoud Esmaili, 2022. "Behavior-Aware Aggregation of Distributed Energy Resources for Risk-Aware Operational Scheduling of Distribution Systems," Energies, MDPI, vol. 15(24), pages 1-18, December.
    6. Janko, Samantha A. & Johnson, Nathan G., 2018. "Scalable multi-agent microgrid negotiations for a transactive energy market," Applied Energy, Elsevier, vol. 229(C), pages 715-727.
    7. Sarshar, Javad & Moosapour, Seyyed Sajjad & Joorabian, Mahmood, 2017. "Multi-objective energy management of a micro-grid considering uncertainty in wind power forecasting," Energy, Elsevier, vol. 139(C), pages 680-693.
    8. Yoro, Kelvin O. & Daramola, Michael O. & Sekoai, Patrick T. & Wilson, Uwemedimo N. & Eterigho-Ikelegbe, Orevaoghene, 2021. "Update on current approaches, challenges, and prospects of modeling and simulation in renewable and sustainable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    9. Àlex Alonso-Travesset & Helena Martín & Sergio Coronas & Jordi de la Hoz, 2022. "Optimization Models under Uncertainty in Distributed Generation Systems: A Review," Energies, MDPI, vol. 15(5), pages 1-40, March.
    10. Lu, Tianguang & Ai, Qian & Wang, Zhaoyu, 2018. "Interactive game vector: A stochastic operation-based pricing mechanism for smart energy systems with coupled-microgrids," Applied Energy, Elsevier, vol. 212(C), pages 1462-1475.
    11. Chen, Y. & Trifkovic, M., 2018. "Optimal scheduling of a microgrid in a volatile electricity market environment: Portfolio optimization approach," Applied Energy, Elsevier, vol. 226(C), pages 703-712.
    12. Berrueta, Alberto & Urtasun, Andoni & Ursúa, Alfredo & Sanchis, Pablo, 2018. "A comprehensive model for lithium-ion batteries: From the physical principles to an electrical model," Energy, Elsevier, vol. 144(C), pages 286-300.
    13. Mousavizadeh, Saeed & Haghifam, Mahmoud-Reza & Shariatkhah, Mohammad-Hossein, 2018. "A linear two-stage method for resiliency analysis in distribution systems considering renewable energy and demand response resources," Applied Energy, Elsevier, vol. 211(C), pages 443-460.
    14. Liu, Yixin & Guo, Li & Wang, Chengshan, 2018. "A robust operation-based scheduling optimization for smart distribution networks with multi-microgrids," Applied Energy, Elsevier, vol. 228(C), pages 130-140.
    15. Purkayastha, Sagar N. & Chen, Yujun & Gates, Ian D. & Trifkovic, Milana, 2020. "A kelly criterion based optimal scheduling of a microgrid on a steam-assisted gravity drainage (SAGD) facility," Energy, Elsevier, vol. 204(C).

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