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Inspecting and maintaining power lines is essential for ensuring the safety, reliability, and efficiency of electrical infrastructure. This process involves regular assessment to identify hazards such as damaged wires, corrosion, or vegetation encroachment, followed by timely maintenance to prevent accidents and power outages. By conducting routine inspections and maintenance, utilities can comply with regulations, enhance operational efficiency, and extend the lifespan of power lines and equipment. Unmanned Aerial Vehicles (UAVs) can play a relevant role in this process by increasing efficiency through rapid coverage of large areas and access to difficult-to-reach locations, enhanced safety by minimizing risks to personnel in hazardous environments, and cost-effectiveness compared to traditional methods. UAVs equipped with sensors such as visual and thermographic cameras enable the accurate collection of high-resolution data, facilitating early detection of defects and other potential issues. To ensure the safety of the autonomous inspection process, UAVs must be capable of performing onboard processing, particularly for detection of power lines and obstacles. In this paper, we address the development of a deep learning approach with YOLOv8 for power line detection based on visual and thermographic images. The developed solution was validated with a UAV during a power line inspection mission, obtaining mAP@0.5 results of over 90.5% on visible images and over 96.9% on thermographic images. [ABSTRACT FROM AUTHOR]

The energy transition relies on an increasingly massive and pervasive use of renewable energy sources, mainly photovoltaic and wind, characterized by an intrinsic degree of production uncertainty, mostly due to meteorological conditions variability that, even if accurately estimated, can hardly be kept under control. Because of this limit, continuously monitoring the operative status of each renewable energy-based power plant becomes relevant in order to timely face any other uncertainty source such as those related to the plant operation and maintenance (O&M), whose effect may become relevant in terms of the levelized cost of energy. In this frame, the use of robots, which incorporate fully automatic platforms capable of monitoring each plant and also allow effective and efficient process operation, can be considered a feasible solution. This paper carries out a review on the use of robots for the O&M of photovoltaic, wind, hydroelectric, and concentrated solar power, including robot applications for controlling power lines, whose role can in fact be considered a key complementary issue within the energy transition. It is shown that various robotic solutions have so far been proposed both by the academy and by industries and that implementing their use should be considered mandatory for the energy transition scenario. [ABSTRACT FROM AUTHOR]

Illegal killing of protected nongame birds is pervasive and can be demographically relevant. In 2021 and 2022, we evaluated spatial and temporal patterns in illegal killing of birds along 69.7 km of power lines in the Morley Nelson Snake River Birds of Prey National Conservation Area in Idaho, USA, to provide insight into potential drivers behind the activity and key information to manage this threat across the American west. The illegal shooting of 8 species of raptors and corvids we documented was clumped both temporally and spatially, as opposed to being randomly distributed across the year and landscape. We found 72 illegally shot birds, most killed during spring months (March to May), coincident with peak time periods of legal recreational shooting activity, and in places with high levels of recreational shooting. We also found evidence of targeted killing of raptors in the conservation area in areas not associated with recreational shooting. Given the numbers of nesting pairs of some local raptor species, this shooting is likely demographically relevant for some but not all local populations. Likewise, with the prevalence of recreational shooting across the American west, the inference we draw is broadly relevant beyond our Idaho study area. The insight our work provides can enable owners of power lines, law enforcement agencies, and resource managers to coordinate in outreach, regulatory, and law enforcement action to manage a threat that may have widespread impacts for some avian species. [ABSTRACT FROM AUTHOR]

In this work, we have analysed the different causes of admissions of stone martens (Martes foina), genets (Genetta genetta) and pine martens (Martes martes) in two rehabilitation centres in Castilla y León (Spain) during 32 years (1991–2022). The results indicate that the most important factor for stone martens was road kills with 227 martens (53.4 %) followed by electrocutions with 90 martens (21.2 %). From genets, 94 of them (68.6 %) were due to roadkill and 7 (5.1 %) were due to electrocution. The most important cause of admission for pine martens was road kills with 22 (88 %) and 1 (4 %) due to electrocution. Possible explanations for the observed high mortality of stone martens in electric pylons are discussed. [ABSTRACT FROM AUTHOR]

The aerial inspection of electricity infrastructure is gaining high interest due to the rapid advancements in unmanned aerial vehicle (UAV) technology, which has proven to be a cost- and time-effective solution for deploying computer vision techniques. Our objectives are focused on enabling the real-time detection of key power line components and identifying missing caps on insulators. To address the need for real-time detection, we evaluate the latest single-stage object detector, YOLOv8. We propose a fine-tuned model based on YOLOv8's architecture, trained on a custom dataset with three object classes, i.e., towers, insulators, and conductors, resulting in an overall accuracy rate of 83.8% (mAP@0.5). The model was tested on a GeForce RTX 3070 (8 GB), as well as on a CPU, reaching 243 fps and 39 fps for video footage, respectively. We also verify that our model can serve as a baseline for other power line detection models; a defect detection model for insulators was trained using our model's pre-trained weights on an open-source dataset, increasing precision and recall class predictions (F1-score). The model achieved a 99.5% accuracy rate in classifying defective insulators (mAP@0.5). [ABSTRACT FROM AUTHOR]

Electrical power systems represent an immense source of electromagnetic radiation spanning a wide frequency range, encompassing low-frequency, transient states, and high-frequency emissions. The radiation poses a significant self-pollution challenge for electric and electronic devices situated in close proximity to these systems. The present article aims to address this research, and provides a comprehensive review of the electromagnetic effects and pollution at differences frequency's ranges encompassing power systems network. In the context of the low-frequency range, the computation of electric and magnetic fields is conducted using quasi-static principles. To validate the behavior at high frequencies due to power line currents, Schelkunoff's approach is employed. Additionally, transient electromagnetic fields are analyzed using an exact analytical method. The results of computer simulations are compared with previously published and measured data for low-frequency regime and transient overvoltage conditions, verifying their consistency. Additionally, high-frequency results are presented and corroborated through the utilization of a numerical electromagnetic code (NEC-4). These analyses underscore the valuable role of computer-based calculations in examining the electromagnetic environment of power system networks. [ABSTRACT FROM AUTHOR]

The main aspects of the use of automatic monitoring and control systems in order to increase the reliability of power lines are considered. The article highlights modern technologies and techniques that make it possible to quickly identify and prevent possible emergency situations on power transmission lines. The advantages of automated systems compared to traditional monitoring and control methods are discussed, and examples of research and practical applications of such systems are presented. The results obtained can be useful for energy specialists and engineers involved in the design, operation and maintenance of power transmission lines, as well as for developers and manufacturers of automated monitoring and control systems. [ABSTRACT FROM AUTHOR]

This document is a list of references cited in a research article about the abundance and conservation of raptors in Argentina. The references cover various aspects of raptor research, including breeding ecology, habitat relationships, and threats such as electrocution and power line collisions. The document also includes references on the use of anthropogenic nest substrates by Crested Caracaras and the installation of devices in water tanks to prevent drowning of wild animals. This comprehensive list of references can be a valuable resource for library patrons interested in raptor research in Argentina. [Extracted from the article]

The Bonelli's Eagle (Aquila fasciata) is a critically endangered species in Israel, with electrocution on power lines posing a serious threat to its population. Because retrofitting of electricity pylons to prevent mortality is a slow and costly process, it is important to prioritize the pylons in the network for quick and efficient mitigation of eagle mortality. To determine which pylons need to be retrofitted, we applied a three-stage maximum entropy modeling process for identifying the risk factors posed by different environmental variables. The environmental feature with the highest correlation to electrocution is the distance to reservoirs (i.e. many electrocution events occur near water reservoirs). The reservoirs are foraging hotspots for Bonelli's Eagles in Israel's arid environment. Electricity pylons powering the reservoirs' pumping facilities tend to be the highest perches in the vicinity of many of the reservoirs, creating an ecological trap. The strong attraction of reservoirs to eagles may explain the high level of selectivity indicated by the model, suggesting that retrofitting only 3.6% of the pylons in the network would achieve 77% reduction in eagles' electrocution probability. Moreover, insulating pylons according to the model will also likely reduce electrocutions of other avian species, including Eastern Imperial Eagle (Aquila heliaca) and White-tailed Eagle (Haliaeetus albicilla). The modeling process presented here yielded 2 electrocution risk maps, one to facilitate prioritization of mitigation in Israel's existing power network and the second to support planning and designing new infrastructure. The model may help reach conservation goals for the Israeli Bonelli's Eagle and the modeling approach may also be useful in prioritizing pylon retrofitting in other arid landscapes. [ABSTRACT FROM AUTHOR]

Studying the impact of renewable energy sources planned to be connected to the grid, requires the preparation of expert opinions. The task of this opinion is to verify that there are possibilities enabling the connection of the considered source to the network. Each opinion is required to take into account other facilities and those sources which were previously connected to the grid or connection agreement were signed with them. The need to take into account such a large number of sources contributes to potential thermal overloads of high-voltage lines. Sometimes these overloads are insignificant, but in certain situations it turns out that their occurrence may be a reason for refusing to sign connection agreements for new sources. According to network operators, their presence may constitute a threat to the operational security of the grid. The article presents the use of the method of tracking active power flows and the DC method of determining power flows to estimate the impact of these sources on thermal overloading of lines. Using of the IEEE-118 test network, selected nodes were analysed where connecting sources might significantly worsen overloads previously observed or would cause new overloads. The proposed approach will enable potential investors to make proper decisions regarding selection of source connection points. Combining the results obtained by both methods at the same time will allow for the indication of appropriate connection nodes for sources from the point of view of minimising the number of overloaded lines and prospective costs of their uprating. [ABSTRACT FROM AUTHOR]

The inspection of power transmission and distribution systems is performed visually by foot patrolling and helicopter methods. These methods have various disadvantages such as time-consuming, high operating cost, safety issues, and improper results. To overcome this issue, power utility companies are searching for the alternatives like Unmanned Aerial Systems (UAS) or drones. UAS are safe, cost effective, and requires less time for power transmission line inspection compared to the regular methods. In this manuscript, a decisive flight path planning for UAS to visually inspect a power transmission line and towers is explained. The objective of this paper is to maximize the performance of three functions such as coverage of transmission tower, quality of captured image, and flight time. Second, proposing an automated inspection strategy for UAS to follow the overhead power transmission lines. These objectives are achieved by formulating a cost function, to convert the path planning into a safe operation for UAS. The results of Particle Swarm Optimization (PSO) and Simulated Annealing (SA) are compared to find the best path for UAS. The experimental finding shows that PSO algorithm has higher efficiency and effectiveness compared to the SA algorithm and benefits the UAS with a safe flight path for the inspection of power transmission towers. [ABSTRACT FROM AUTHOR]

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In the 20th century, there were fewer energy choices. Almost everyone generated their own heating at home, from coal, oil or natural gas, and virtually nobody produced their own electricity. [...]

Developing countries are witnessing rapid expansion of electrical infrastructure to meet increasing energy demands, prompting a critical need to assess the potential impact on avian biodiversity. Leveraging open access data, our study conducted a comprehensive assessment to detect electrocution and collision risk hotspots in Kenya while identifying raptor species highly susceptible to these risks. Through an integrated approach that considers morphological and behavioral traits of the species, environmental factors at the site, and technical parameters of the power lines, we developed risk maps and categorized raptors’ susceptibility into high, medium, and low-risk levels. Applying this framework, we identified three raptor species at high risk of electrocution; the long-crested eagle, the augur buzzard, and the steppe eagle. Meru and Kiambu counties emerged as high-risk areas due to substantial overlap between high-risk buffer zones and areas with high raptor species distribution. It is worth noting that this framework only accounts for thirteen raptor species, and there is scope to expand it in the future to include other avian species, such as storks, bustards, pelicans and flamingos, which are also susceptible to electrocution and collision incidents and measures to mitigate electrocution of raptors may not be sufficient for these other group of birds.

. It is a very challenging task to correctly use weather data to calculate the active power loss due to corona in overhead power lines. One of the significant reasons for this was the problem of accuracy of determining weather conditions and the use of the forecast for calculating extended overhead lines. In the USSR (Union of Soviet Socialist Republics), based on field tests and experimental data, recommendations were developed for accounting for losses of electric energy due to corona and interference in overhead lines, the average values of which were given in the relevant instruction for the regulation and justification of the norm of electricity consumption for its transmission over electric networks. According to this regulatory document, the specific cost of active power due to corona in overhead lines, averaged by design, was determined depending on weather conditions, which were divided into four groups. In this paper, the effect of active power losses on corona is estimated using various factors on the example of high-voltage overhead lines in the main electrical networks of the Republic of Belarus of various rated voltages. Dependences of active power losses due to corona have been constructed and modeled, taking into account different climatic and weather conditions observed in the country. The determination of metrological parameters was based on the analysis of weather data and patterns of types of weather conditions. In order to improve the accuracy of calculating the specific losses of active power due to corona, all possible weather conditions were considered, as well as their combinations. Afterwards, the data on weather conditions were processed and their types were reduced to one of the four existing types of weather. A method for determining electric power losses due to corona in overhead lines based on the average relative air density and geometric parameters of the predominant section of overhead lines has been proposed and presented. It is shown that the usage of exclusively rated voltage can cause errors in determining both the specific and actual values of active power losses for corona.