Extracting tiny amounts of energy from non-conventional sources using Peltier cells, piezoelectrics, antennas or inductive probes has become very popular in recent years to power low-consuming sensors in IoT applications and smart grids. These energy harvesting methods rely on the continuous generation of small quantities of electrical energy scavenged from heat, vibration or electromagnetic emissions. This energy is stored in batteries or capacitors reaching low-voltage levels that cannot be used directly to power any device. In general, the voltage is boosted to more appropriate levels with a converter. Using inductive sensors to harvest energy from electrical power lines is common knowledge. Obtaining this energy from high-power low-frequency signals is currently possible and, in some cases, reliable and profitable. The aim of this paper is to evaluate the possibility of harvesting energy from extremely low-power and high-frequency events that occur in electrical assets when the insulation is damaged. These events, called partial discharges, are used in electrical maintenance to detect possible defects in the insulation. Evaluating partial discharge activity is a common protocol in all utilities that requires the use of expensive sensors and acquisition systems, and in most occasions, decommissioning the asset to connect the measuring system. The energy from these phenomena is stored in capacitors and the use of a high-frequency voltage multiplier allows to reach voltages close to 1 V. This voltage is proportional to the number of partial discharges in a certain time span. Therefore, if the number of partial discharges per time-unit has increased noticeably, the insulation has deteriorated and the asset should be decommissioned to evaluate the damages. The paper tests the possibility of using this method as an early-warning system in the maintenance of electrical assets.