Efficient pedestrian-level wind energy harvesting using a hybridized technology

Abstract

Pedestrian-level wind (PLW, 0–2 m above ground level) is an affordable and clean energy source characterized by high transience, low-Reynolds-number airflow and turbulence. PLW energy capture in conventional systems (e.g., electromagnetic generators) is severely limited due to their mechanical inertia and electromagnetic resistance-induced inefficiencies at ultralow speeds (<2 m s−1). Here, we introduce a pedestrian-level wind energy hybrid harvester (PLW-HH) that synergistically couples a triboelectric nanogenerator (TENG) and electromagnetic generator (EMG) to leverage the complementary advantages of both technologies. At a wind speed of 1 m s−1, a common condition in built environments, the integrated system achieves a wind energy capture efficiency of 12%, with the TENG component contributing 86.7% of the total power output. This dominance of the TENG at ultralow speeds arises from its unique sensitivity to minute mechanical vibrations and ultralow activation thresholds, surpassing the EMG by over 650% in power under identical experimental conditions. By leveraging the ubiquitous PLW from urban buildings, tunnels, and areas near low obstacles, our approach demonstrates a scalable pathway toward power sensors, Internet of Things (IoT) devices, and low-energy systems without grid dependency. This work bridges the gap between underutilized micro-scale wind resources and the growing demand for in situ self-sustaining energy, focusing on feasibility to ensure universal access to modern, sustainable, and affordable energy for all.

Graphical abstract: Efficient pedestrian-level wind energy harvesting using a hybridized technology

Supplementary files

Article information

Article type
Paper
Submitted
19 Jun 2025
Accepted
17 Jul 2025
First published
18 Jul 2025

Energy Environ. Sci., 2025, Advance Article

Efficient pedestrian-level wind energy harvesting using a hybridized technology

G. Yu, P. Ji, X. Gao, T. Zhou, S. Wang, W. Gao, H. Li, Z. L. Wang and B. Chen, Energy Environ. Sci., 2025, Advance Article , DOI: 10.1039/D5EE03460D

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