Distribution Line Pole Research Articles

Flashover Prevention System using IoT and Machine Learning for Transmission and Distribution Lines

Flashover on transmission and distribution line insulators occurs when the insulator’s resistance drops to a critical level and causes frequent power outages. Thin layers of dust, salt, and airborne particles, gradually deposited on the surface of insulators, as well as humidity, form an electrolyte which causes flashover. In this paper, a flashover prevention system using IoT technology and machine learning is proposed in order to reduce loss and increase power reliability. The system includes an IoT module, a service and clients. The IoT module prototype was installed at a distribution line pole located in Pracha-utit, Bangkok, Thailand and had collected data for thirty-four months. The data were pre-processed and split for the training process and evaluation. In this study, we built and compared four models including linear regression, polynomial regression, Auto-regressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) models. The results revealed that the LSTM model outperformed (<em>R</em><sup>2</sup>=.931, RMSE= 530.74) the others.

Research on poles selection and poles reuse of distribution line

Based on the model selection of distribution line poles and towers, this paper presents the application scheme of high strength concrete poles in distribution lines. At the same time, it studies the reuse of dismantled old concrete poles and puts forward a graded utilization programme. Research achievements can guide the model selection and reuse of distribution line poles so as to help power grid enterprise to improve their quality and enhance their efficiency.

Correction to: Distribution Line Pole Detection and Counting Based on YOLO Using UAV Inspection Line Video

The article “Distribution Line Pole Detection and Counting Based on YOLO Using UAV Inspection Line Video“, written by Binghuang Chen and Xiren Miao was originally published.

Distribution Line Pole Detection and Counting Based on YOLO Using UAV Inspection Line Video

In order to improve the efficiency of post-disaster treatment of power distribution network, the application of UAV in disaster reduction and relief has been paid much attention by the power sector. Aiming at the loss assessment needs of overhead transmission lines in distribution network, this paper proposes an innovative solution of pole detection and counting in distribution network based on UAV inspection line video. Combined with the characteristics of YOLO’s rapid detection, the convolution neural network is applied to the image detection of the pole state. In addition, the pole data and corresponding images are obtained at the same time of detecting the inspection line video. Therefore, the power department can quickly count the losses to cope with the disaster. The anchor value is modified before image training by YOLO v3, and sets the corresponding ROI for the UAV inspection line standard. In order to quickly obtain the loss assessment of post-disaster pole lodging, this paper proposes a counting algorithm by using the continuous ordinate change of the bounding box of the same pole in front and rear frame of video, so that the classified counting of pole is accurate and the detection precision is above 0.9. The results obtained in video test show that this method is effective in detecting and counting the state of the pole of overhead transmission line in distribution network.

Raptor Electrocution Rates for a Utility in the Intermountain Western United States

ABSTRACT We estimated electrocution rates for raptors and common ravens (Corvus corax) for the Moon Lake Electrical Association in northeastern Utah and northwestern Colorado, USA. From July 2001 to May 2003, we conducted mortality searches at randomly selected distribution line segments and poles within 3 regions, but rate estimates (0.0036–0.0112 deaths/pole/yr) may have been biased by the effects of scavengers and by long sampling intervals (≥ 3 months), which prevented us from determining the cause of death for most birds because of advanced decay. In 2002–2003, we conducted carcass removal experiments in the Rangely Oil Field (ROF) in northwestern Colorado to estimate scavenging effects, and in 2003–2004, we reduced sampling intervals to 1 month and searched for dead birds at all distribution poles in the ROF. The shorter sampling interval nearly tripled the number of birds suitable for necropsy, but we were still unable to establish cause of death for >40% of our sample. Instead of eliminating the unknowns from rate estimates, we estimated minimum annual electrocution rates using only confirmed electrocutions and maximum annual electrocution rates based on all available mortalities, including mortalities without known causes. Golden eagles (Aquila chrysaetos) accounted for 63% of dead birds found in 2003–2004, but they were removed by scavengers at rates well below hawks and owls (6.8% vs. 55.6%). We compared maximum rates for the ROF in 2003–2004 with the rates estimated from a survey conducted at the same poles in 1999 to assess the effects of retrofitting conducted by Moon Lake from 1999 to 2003. Electrocution rates in 2003–2004 were 47% lower than those in 1999. Raptor densities in the ROF did not change during our study, suggesting the reduction was not the result of changes in raptor populations. However, estimates of raptor densities in 1999 were not available, and we cannot be sure that numbers of birds using the oil field in 1999 were similar to those in 2003–2004. Our research emphasizes the difficulties of estimating electrocution rates precisely but suggests that utilities will have the greatest effect on mortality by monitoring power lines at large scales and focusing subsequent mitigation efforts in areas that pose the greatest risk to the greatest number of birds.

Electrical degradation of fiberglass distribution line pole

This paper presents the results of experiments conducted on fiberglass distribution line pole. First, the critical flashover (CFO) voltage of the fiberglass distribution line pole and its combination with polymer and porcelain insulators is given. Then, the data obtained from the study performed on accelerated aging of fiberglass distribution line poles are presented, followed by a discussion of the results

Added CFO Voltage by the Fiberglass Distribution Line Pole

This paper presents the study results conducted on the critical flashover (CFO) voltages of the fiberglass distribution line pole and its combination with polymer and porcelain insulators. Special attention was made to evaluate the added CFO voltages by the fiberglass pole to the insulators when pole served as a second component in the distribution line structure. A discussion of the results follows the data obtained.