An Experimental Study of Power Smoothing Methods to Reduce Renewable Sources Fluctuations Using Supercapacitors and Lithium-Ion Batteries

Abstract

The random nature of renewable sources causes power fluctuations affecting the stability in the utility grid. This problem has motivated the development of new power smoothing techniques using supercapacitors and batteries. However, experimental studies based on multiple renewable sources (photovoltaic, wind, hydrokinetic) that demonstrate the validity of power smoothing techniques under real conditions still require further study. For this reason, this article presents a feasibility study of a renewable grid-connected system, addressing various aspects based on power quality and energy management. The first of them is related to the fluctuations produced by the stochastic characteristics of renewable sources and demand. Two power smoothing algorithms are presented (ramp rate and moving average) combining photovoltaic, wind, and hydrokinetic sources with a hybrid storage system composed of supercapacitors and lithium-ion batteries. Then, the self-consumption for an industrial load is analyzed by studying the energy flows between the hybrid renewable energy sources and the grid. The main novelty of this paper is the operability of the supercapacitor. The experimental results show that when applying the power smoothing ramp rate method, the supercapacitor operates fewer cycles with respect to the moving average method. This result is maintained by varying the capacity of the renewable sources. Moreover, by increasing the capacity of photovoltaic and wind renewable sources, the hybrid storage system requires a greater capacity only of supercapacitors, while by increasing the capacity of hydrokinetic turbines, the battery requirement increases considerably. Finally, the cost of energy and self-consumption reach maximum values by increasing the capacity of the hydrokinetic turbines and batteries