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A statistical approach to electrical storage sizing with application to the recovery of braking energy

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  • Musolino, V.
  • Pievatolo, A.
  • Tironi, E.

Abstract

In the context of efficient energy use, electrical energy in electric drives plays a fundamental role. High efficiency energy storage systems permit energy recovery, peak shaving and power quality functions. Due to their cost and the importance of system integration, there is a need for a correct design based on technical-economical optimization. In this paper, a method to design a centralized storage system for the recovery of the power regenerated by a number of electric drives is presented. It is assumed that the drives follow deterministic power cycles, but shifted by an uncertain amount. Therefore the recoverable energy and, consequently, the storage size requires the optimization of a random cost function, embedding both the plant total cost and the saving due to the reduced energy consumption during the useful life of the storage. The underlying stochastic model for the power profile of the drives as a whole is built from a general Markov chain framework. A numerical example, based on Monte Carlo simulations, concerns the maximization of the recoverable potential energy of multiple bridge cranes, supplied by a unique grid connection point and a centralized supercapacitor storage system.

Suggested Citation

  • Musolino, V. & Pievatolo, A. & Tironi, E., 2011. "A statistical approach to electrical storage sizing with application to the recovery of braking energy," Energy, Elsevier, vol. 36(11), pages 6697-6704.
    • Handle: RePEc:eee:energy:v:36:y:2011:i:11:p:6697-6704
    DOI: 10.1016/j.energy.2011.07.037
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    References listed on IDEAS

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    1. Tan, Chee Wei & Green, Tim C. & Hernandez-Aramburo, Carlos A., 2010. "A stochastic method for battery sizing with uninterruptible-power and demand shift capabilities in PV (photovoltaic) systems," Energy, Elsevier, vol. 35(12), pages 5082-5092.
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    2. Qi, Lingfei & Wu, Xiaoping & Zeng, Xiaohui & Feng, Yan & Pan, Hongye & Zhang, Zutao & Yuan, Yanping, 2020. "An electro-mechanical braking energy recovery system based on coil springs for energy saving applications in electric vehicles," Energy, Elsevier, vol. 200(C).
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    7. Hauge, H.H. & Presser, V. & Burheim, O., 2014. "In-situ and ex-situ measurements of thermal conductivity of supercapacitors," Energy, Elsevier, vol. 78(C), pages 373-383.
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    9. Papaioannou, Vicky & Pietrosanti, Stefano & Holderbaum, William & Becerra, Victor M. & Mayer, Rayner, 2017. "Analysis of energy usage for RTG cranes," Energy, Elsevier, vol. 125(C), pages 337-344.
    10. Pavković, D. & Hoić, M. & Deur, J. & Petrić, J., 2014. "Energy storage systems sizing study for a high-altitude wind energy application," Energy, Elsevier, vol. 76(C), pages 91-103.
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