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Fast power flow scheduling and sensitivity analysis for sizing a microgrid with storage

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  • Rigo-Mariani, R.
  • Sareni, B.
  • Roboam, X.

Abstract

This article proposes a fast strategy for optimal dispatching of power flows in a microgrid with storage. The investigated approach is based on the use of standard mixed integer linear programming (MILP) algorithm in association with a coarse linear model of the microgrid. The resulting computational time is compatible with simulations over long periods of time allowing the integration of seasonal and stochastic features related to renewable energies. By using this fast scheduling strategy over a complete year of simulation, the microgrid cost effectiveness is considered. Finally, a sensitivity analysis is carried out in order to identify the most influent parameters that should be considered in a sizing loop. Different microgrid configurations are also investigated and compared in terms of cost-effectiveness.

Suggested Citation

  • Rigo-Mariani, R. & Sareni, B. & Roboam, X., 2017. "Fast power flow scheduling and sensitivity analysis for sizing a microgrid with storage," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 131(C), pages 114-127.
    • Handle: RePEc:eee:matcom:v:131:y:2017:i:c:p:114-127
    DOI: 10.1016/j.matcom.2015.11.010
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    References listed on IDEAS

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    1. Reichelstein, Stefan & Yorston, Michael, 2013. "The prospects for cost competitive solar PV power," Energy Policy, Elsevier, vol. 55(C), pages 117-127.
    2. Rigo-Mariani, Rémy & Sareni, Bruno & Roboam, Xavier & Turpin, Christophe, 2014. "Optimal power dispatching strategies in smart-microgrids with storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 649-658.
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    Cited by:

    1. Bourbon, R. & Ngueveu, S.U. & Roboam, X. & Sareni, B. & Turpin, C. & Hernandez-Torres, D., 2019. "Energy management optimization of a smart wind power plant comparing heuristic and linear programming methods," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 158(C), pages 418-431.
    2. Rigo-Mariani, Rémy & Chea Wae, Sean Ooi & Mazzoni, Stefano & Romagnoli, Alessandro, 2020. "Comparison of optimization frameworks for the design of a multi-energy microgrid," Applied Energy, Elsevier, vol. 257(C).
    3. Kutaiba Sabah Nimma & Monaaf D. A. Al-Falahi & Hung Duc Nguyen & S. D. G. Jayasinghe & Thair S. Mahmoud & Michael Negnevitsky, 2018. "Grey Wolf Optimization-Based Optimum Energy-Management and Battery-Sizing Method for Grid-Connected Microgrids," Energies, MDPI, vol. 11(4), pages 1-27, April.

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