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Gaussian-Based Smoothing of Wind and Solar Power Productions Using Batteries

Alemayehu A. Desta 1, Pierre Courbin 1, Vincent Sciandra 1, and Laurent George 2
1. METRON, Paris, France
2. UPEM and ESIEE, Champs-sur-Marne, France

Abstract—Intermittent nature of Distributed Energy Resources (DER) such as solar and wind cause significant power fluctuations and integrating them to a power systems requires control mechanisms to reduce fluctuations. One way to control the effect of fluctuation is to use Energy Storage Systems (ESS) for smoothing out their power productions. A typical method to attain this goal is to use ESS with classical moving average approaches. However, these methods are affected by peaks and troughs in power production due to cloud passing and wind gust effects on solar panels and wind turbines, respectively. In this paper, we propose a Gaussian-based smoothing method to alleviate pitfalls of moving average methods to smooth out forecasted values of solar and wind powers. Then, we determine a minimum ESS size required to maintain a smoothed power curve for a day-ahead period. From our experiments, the proposed algorithm requires smaller ESS size than the classical approaches. 
Index Terms—distributed energy resources, solar, wind, moving average, gaussian-based, microgrid

Cite: Alemayehu A. Desta, Pierre Courbin, Vincent Sciandra, and Laurent George, "Gaussian-Based Smoothing of Wind and Solar Power Productions Using Batteries," International Journal of Mechanical Engineering and Robotics Research, Vol. 6, No. 2, pp. 154-159, March 2017. DOI: 10.18178/ijmerr.6.2.154-159