Partial discharge (PD) is regarded as a precursor to plant failure and therefore, an effective indication of plant condition. Locating the source of PD before failure is key to efficient maintenance and improving reliability of power systems. This paper presents a low cost, autonomous partial discharge radiolocation mechanism to improve PD localization precision. The proposed radio frequency-based technique uses the wavelet packet transform (WPT) and machine learning ensemble methods to locate PDs. More specifically, the received signals are decomposed by the WPT and analyzed in order to identify localized PD signal patterns in the presence of noise. The regression tree algorithm, bootstrap aggregating method, and regression random forest are used to develop PD localization models based on the WPT-based PD features. The proposed PD localization scheme has been found to successfully locate PD with negligible error. Additionally, the principle of the PD location scheme has been validated using a separate test dataset. Numerical results demonstrate that the WPT-random forest PD localization scheme produced superior performance as a result of its robustness against noise.

A wireless sensor network (WSN) with the potential to monitor and locate partial discharge (PD) in high-voltage electricity substations using only received signal strength (RSS) is proposed. The advantages of an RSS-based operating principle over more traditional methods (e.g., time-of-arrival and time-difference-of-arrival) are described. Laboratory measurements of PD that emulate the operation of a PD WSN are presented. The hardware architecture of a prototype PD WSN is described and the particular challenges of an RSS-based location approach in an environment with an unknown, and spatially varying, path-loss index are discussed. It is concluded that an RSS-based PD WSN is a plausible solution for the monitoring of insulation integrity in electricity substations.

The lifespan assessment and maintenance planning of high-voltage power systems requires condition monitoring of all the operational equipment in a specific area. Electrical insulation of electrical apparatuses is prone to failure due to high electrical stresses, and thus it is a critical aspect that needs to be monitored. The ageing process of the electrical insulation in high voltage equipment may accelerate due to the occurrence of partial discharge (PD) that may in turn lead to catastrophic failures if the related defects are left untreated at an initial stage. Therefore, there is a requirement to monitor the PD levels so that an unexpected breakdown of high-voltage equipment is avoided. There are several ways of detecting PD, such as acoustic detection, optical detection, chemical detection, and radiometric detection. This paper focuses on reviewing techniques based on radiometric detection of PD, and more specifically, using received signal strength (RSS) for the localization of faults. This paper explores the advantages and disadvantages of radiometric techniques and presents an overview of a radiometric PD detection technique that uses a transistor reset integrator (TRI)-based wireless sensor network (WSN).

Monitoring of partial discharge (PD) activity within high‐voltage electrical environments is increasingly used for the assessment of insulation condition. Traditional measurement techniques employ technologies that either require off‐line installation or have high power consumption and are hence costly. A wireless sensor network is proposed that utilizes only received signal strength to locate areas of PD activity within a high‐voltage electricity substation. The network comprises low‐power and low‐cost radiometric sensor nodes which receive the radiation propagated from a source of PD. Results are reported from several empirical tests performed within a large indoor environment and a substation environment using a network of nine sensor nodes. A portable PD source emulator was placed at multiple locations within the network. Signal strength measured by the nodes is reported via WirelessHART to a data collection hub where it is processed using a location algorithm. The results obtained place the measured location within 2 m of the actual source location.

Partial discharge is a well-established metric for condition assessment of high-voltage plant equipment. Traditional techniques for partial discharge detection involve physical connection of sensors to the device under observation, limiting sensors to monitoring of individual apparatus, and therefore, limiting coverage. Wireless measurement provides an attractive low-cost alternative. The measurement of the radiometric signal propagated from a partial discharge source allows for multiple plant items to be observed by a single sensor, without any physical connection to the plant. Moreover, the implementation of a large-scale wireless sensor network for radiometric monitoring facilitates a simple approach to high voltage fault diagnostics. However, accurate measurement typically requires fast data conversion rates to ensure accurate measurement of faults. The use of high-speed conversion requires continuous high-power dissipation, degrading sensor efficiency and increasing cost and complexity. Thus, we propose a radiometric sensor which utilizes a gated, pipelined, sample-and-hold based folding analogue-todigital converter structure that only samples when a signal is received, reducing the power consumption and increasing the efficiency of the sensor. A proof of concept circuit has been developed using discrete components to evaluate the performance and power consumption of the system.

Partial discharge (PD) is one of the predominant factors to be controlled to ensure reliability and undisrupted functions of power generators, motors, Gas Insulated Switchgear (GIS) and grid connected power distribution equipment, especially in the future smart grid. The emergence of wireless technology has provided numerous opportunities to optimise remote monitoring and control facilities that can play a significant role in ensuring swift control and restoration of HV plant equipment. In order to monitor PD, several approaches have been employed, however, the existing schemes do not provide an optimal approach for PD signal analysis, and are very costly. In this paper an RTL-SDR (Software Defined Radio) based spectrum analyser has been proposed in order to provide a potentially low cost solution for PD detection and monitoring. Initially, a portable spectrum analyser has been used for PD detection that was later replaced by an RTL-SDR device. The proposed schemes exhibit promising results for spectral detection within the VHF and UHF band.