Energy Harvesting from Breeze Wind (0.7–6 m s−1) Using Ultra‐Stretchable Triboelectric Nanogenerator

By Zewei Ren, Ziming Wang, Zhirong Liu, Longfei Wang, Hengyu Guo, Linlin Li, Site Li, Xiangyu Chen, Wei-Yao Tang, Zhong Lin Wang. Advanced Energy Materials, 2020

150 citations recorded by the source corpus.

Wind is one of the most important sources of green energy, but the current technology for harvesting wind energy is only effective when the wind speed is beyond 3.5–4.0 m s−1. This is mainly due to the limitation that the electromagnetic generator works best at high frequency. This means that light breezes cannot reach the wind velocity threshold of current wind turbines. Here, a high‐performance triboelectric nanogenerator (TENG) for efficiently harvesting energy from an ambient gentle wind, especially for speeds below 3 m s−1 is reported, by taking advantage of the relative high efficiency of TENGs at low‐frequency. Attributed to the multiplied‐frequency vibration of ultra‐stretchable and perforated electrodes, an average output of 20 mW m−3 can be achieved with inlet wind speed of 0.7 m s−1, while an average energy conversion efficiency of 7.8% at wind speed of 2.5 m s−1 is reached. A self‐charging power package is developed and the applicability of the TENG in various light breezes is demonstrated. This work demonstrates the advantages of TENG technology for breeze energy exploitation and proposes an effective supplementary approach for current employed wind turbines and micro energy structure.

Subfields: Biomedical Engineering, Electrical and Electronic Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/8f1bec735e0eb2dce50afea03870d93fcb21a917

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

  1. Xinge Guo
  2. Long Liu
  3. Chengkuo Lee

In Electrical and Electronic Engineering

  1. Xinge Guo
  2. Long Liu
  3. Chengkuo Lee

In Mechanical Engineering

  1. Xinge Guo
  2. Long Liu
  3. Chengkuo Lee

Citations in the corpus