Evaluating Seismic Vibrations as an Energy Resource in Mining and Urban Environments

Eduardo Monsalve^a, Claudia Pavez-Orrego^b, Ángela Flores^a, Nicolás Barbosa^b, Eckner Chaljub^a, Rodrigo Palma-Behnke^a, Nikolai H. Gaukås^d, Didrik R. Småbråten^d, Diana Comte^c*.

• a) Department of Electrical Engineering / Energy Center, Faculty of Mathematical and Physical Sciences, University of Chile, Santiago, Chile
• b) Department of Applied Geosciences, Geophysics, SINTEF Industry, Trondheim, Norway
• c) Advanced Mining Technology Center, Faculty of Mathematical and Physical Sciences, University of Chile, Santiago, Chile
• d) Department of Sustainable Energy Technology, SINTEF Industry, Oslo, Norway

In a global context marked by increasing energy demand and growing constraints on the large-scale deployment of conventional renewable sources, the exploration of alternative energy pathways has become increasingly relevant. Within this framework, vibrational energy harvesting (VEH) has garnered attention due to its potential to exploit ambient energy sources that are typically overlooked, such as mechanical vibrations. In particular, seismic vibrations, both natural and anthropogenic, represent a persistent and spatially distributed energy resource in regions characterized by intense industrial activity and significant seismicity.

This study presents a systematic and replicable methodology for assessing the energy harvesting potential from real seismic vibrations, with a specific focus on high-vibration environments, such as mining areas and urban settings. The proposed framework aims to quantify both the theoretical potential of the vibrational resource, understood as the maximum energy available in the environment, and the technical potential, defined by the current capability of electromagnetic energy harvesters (EMEHs) to capture and convert this energy into usable electrical power.

The developed methodology consists of six main stages: (i) seismic data acquisition, (ii) signal preprocessing, (iii) event identification, (iv) event characterization and classification, (v) device selection, and (vi) dynamic simulation for harvested power estimation. Continuous seismic records are analyzed to detect and isolate energetically relevant events of both natural and anthropogenic origin, including earthquakes, microseisms, blasting activities, and vehicular traffic. These events are characterized in terms of amplitude, frequency content, and duration, providing objective criteria to evaluate their relevance for energy harvesting applications. Representative seismic excitations are subsequently used as non-stationary inputs to a dynamic model of an EMH, enabling the estimation of the harvested power associated with each event type without parameter optimization. This approach allows for a direct comparison between different vibrational sources under realistic operating conditions and highlights the influence of site-specific factors such as local geology, proximity to vibration sources, and spectral characteristics of ground motion.

The application of the proposed framework to a mining environment in northern Chile reveals distinct, yet partially overlapping, ranges of harvestable power across different classes of seismic events. The results demonstrate a strong spatial dependence on the vibrational energy resource and emphasize the necessity of localized assessments when evaluating the feasibility and robustness of vibrational energy harvesting systems. This work contributes a methodological foundation for resource-oriented evaluation, providing quantitative insight into whether seismic vibrations can realistically support low-power applications such as autonomous sensors and monitoring systems.