Energy harvesting out of colored Lévy fluctuations, by a nonlinear piezoelectric transducer

Abstract

This study investigates the performance of a nonlinear piezoelectric energy harvester subjectedto α-stable Lévy noise, which features infinite variance and long-tail distributions. Using numerical simulations, we analyze how the harvester’s nonlinear restoring potential interacts with these non-Gaussian fluctuations to enhance both average power output and efficiency. Our findings show that as the stability parameter α decreases from 2 (Gaussian noise), the system exploits the large jumps characteristic of Lévy processes, achieving significant improvements in energy harvesting, even under weak noise conditions. We also observe distinct efficiency behaviors for different load times, including a valley-shaped trend for high values of α. This work builds upon previous studies—J. I. Deza, R. R. Deza, and H. S. Wio. Epl. 100:38001, 2012.—that explored harvesters driven by noise within the framework of Tsallis entropy, allowing a direct comparison between Lévy and Tsallis processes. By extending the analysis to the infinite variance regime, this study highlights the broader potential of nonlinear systems to harvest energy from realistic, broadbandenvironmental fluctuations.