Drones and Electric Line Inspections: The Future

Drones and Electric Line Inspections: The Future

by Matt Searels, Regional Manager & Seth Reid, Technical Applications Manager

The evolution of technology is swift and merciless. The rate of change is not constant, but seems to follow the evolutionary theory postulated by evolutionary scientists Stephen Jay Gould and Niles Eldredge in 1972, called “Punctuated Equilibria.”

In this theory, evolutionary development is marked by isolated episodes of rapid speciation among long periods of little or no change. Unlike the biological realm, long periods of stability in the technology sector may only last four or five years or as short as a couple months. Technology operates faster and everything related to technology gets smaller in size (processors, memory storage, etc.). Cutting edge technology may be antiquated in less than six months and its 30 seconds of fame may be shorter than its Twitter handle.

Enter: UAS

The use of Unmanned Aerial Systems (UAS), also commonly referred to as drones, will be the next step in the adaptation of remote sensing technologies to the utility vegetation management (UVM) industry. The recent Edison Electric Institute (EEI) and Sharper Shape Inc. partnership formation, to develop commercial UAS beyond visual line of sight (BVLOS) flights for electric companies, plays a big role in those next steps. As a participant in the EEI Sharper Utility project, CN Utility Consulting, Inc. (CNUC) has discovered much more about the current capabilities of applying drones to UVM inspections. While UAS can not eliminate the need for other types of comprehensive vegetation patrols, they could improve safety and cost effectiveness for gas and electric companies in our mission to increase the reliability of the grid.

Furthermore, they will enhance the ability for one to detect and measure potential threats that cannot be seen with the naked eye. Applying technology, such as LiDAR, will allow UAS users to make discreet measurements between vegetation and conductors to support the development of predictive growth models from the data that is collected.

Another UAS sensor is hyper spectral imaging, which will allow UAS users to obtain specific visual vegetation information related to the color spectrum not visible to the human eye. One hyper spectral collection process in particular, infrared, can be used to find hot spots caused by defects in conductors or electrical hardware. Certain regional tree species, or dying vegetation, can be detected by unique hyper spectral signatures and the specific data can be isolated and then exploited by savvy users.

drone, drones, UAS

Above all else, safety

While cost effectiveness, speed, and flexibility are major potential benefits of adopting UAS for remote sensing, increased safety is potentially the most significant benefit of drones. Currently remote sensing techniques are deployed on fixed wing aircraft or helicopters, which is a very accurate but expensive inspection process. Consequently, since LiDAR became widely available in the early 2000s, its application has been limited to high priority projects and facilities such as the North American Electric Reliability Corporation (NERC) Alert, new transmission construction, and vegetation near FAC-003 regulated lines. Manned aircraft is still used extensively for aerial patrols rather than Lidar scanning. This technique involves inherently risky work for crew members and significant numbers of helicopter accidents occur in electric company construction and maintenance patrols (Roskop, 2012). Even LiDAR acquisition, which is safer than visual patrols due to flight patterns, still carries risk to the manned crew and bystanders below. UAS will not eliminate all risks but will eliminate some and reduce others.

Enter: LiDAR

In addition to what is currently being done with remote sensing via fixed wing aircraft or helicopter, the theoretical use of UAS with UVM has many possibilities. For example, by mounting a light weight, solid-state LiDAR system, a drone could inspect an entire right-of-way autonomously, similar to autonomous cars that travel from one distinct point to another. The autonomous drone can then use LiDAR to navigate around vegetation, guy wires, birds, or even other UAS as it collects data. If a hotspot in the line is detected with an infrared sensor, or if LiDAR detects that vegetation is inside of the specified trigger distance from conductors, then the UAS could be programmed to take extra measurements and capture photographic or video data of the surrounding area and the vegetation in question. Each substation could even have a small fleet of drones that are automatically deployed to investigate faults in the line and readily transfer the data back to a central server via a cloud data system. The small size and mobility of UAS can provide logistical and temporal advantages over manned flights with the exception that drones may run out fuel or electrical charge more quickly.

Technology and BVLOS

Remote sensing technologies via drones are not new, but even after decades of scientific and military experience, their synergy has been restricted due to size and weight limitations forcing prohibition of implementation due to costs. We have now entered an era where these technologies are much smaller, lighter, and less expensive and can begin to be utilized collectively. With all of the possibilities and opportunities that UAS can currently provide, and these will magnify and expand as technology evolves, there are still non-technological barriers that restrict commercial implementation. Although the technological components have become more reasonably priced in recent years, visual line of site (VLOS) flights are not viable options for long linear inspections, such as overhead lines. This is because the logistical expenses (travel from location to location, set-up and break-down times, etc.) make VLOS cost-prohibitive. Removing the BLVOS barrier, eliminates the compounding embedded logistical expenses; thus, the EEI Sharper Utility partnership’s focus has been to target the BVLOS barrier and work to make safe, commercial, BLVOS possible for the utility industry.

Due to the complexity of US airspace and the unwritten story of societal acceptance, beyond visual line of site (BVLOS) flights with UAVs has not been an option for our industry due to restrictions by the Federal Aviation Administration (FAA). With the recent release of FAA Rule 107 for small UASs, that are proposed to take effect in August 2016, barriers are beginning to be lowered allowing for a waiver of most of the new restrictions associated with Rule 107, if demonstration of safe operation can be conducted. This should alleviate some of the process constraints of the Section 333 exemptions which are currently in place as part of the FAA Modernization and Reform Act of 2012. Rule 107 opens up some opportunities; but, there is still work to do to eliminate the barriers to safe, commercial, BVLOS UAS use in the utility industry.

Consortium Synergies

In partnership with Edison Electric Institute (EEI), Sharper Shape Inc., Partners in Performance, and participating utilities, CNUC recently participated in a comprehensive study of the business case for BVLOS. Wisely, the focus of the content at this stage avoided directly discussing technology and capabilities of various sensors and flights. We worked backwards from the value that maintenance actions and observations currently provide the participating utilities in order then to determine the most effective and efficient data collection tools, methodology, and flight patterns. Through preliminary questionnaires sent to the participating utilities, and workshops hosted by them, we worked to discover a consensus about what observations each utility currently acquires, what actions they take when an observation is obtained, and how those actions provide value to their shareholders which drives how they manage and maintain the physical assets, vegetation, security, storm recovery, etc. for both transmission and distribution systems.

The workshops observations, actions, and values have been collectively harmonized and synergized. As a result, we now have a better understanding of what data needs to be collected, what sensors will best fit the acquisition needs, and which flight patterns will be required for the optimization of the sensors. Consortium participants are working to finalize the vision for flight demonstrations later this year. These flight patterns and observations intend to capture data and provide analyses. The hope is that the results of this collective agreement will be a powerful voice of reason to allow safe, commercial, BVLOS flights to become a possibility for any utility or vendor in the industry.

Although UAS have the potential to provide safer, faster, and agnostic data acquisition, it may be a while before a UAS can negotiate a removal, delicately handle a refusal, or perform a comprehensive ANSI A300 hazard tree assessment. However, this technology will enhance our current understanding of the situations encountered in the field by providing much needed measurement capabilities. It will be an invaluable asset in our UVM tool box.

To read the article where it was originally published, click here.


•Eldridge, N. and Gould, S.J. (1972). Punctuated Equilibria: An Alternative to Phyletic Gradualism. Speciation 82-115. http://www.blackwellpublishing.com/ridley/classictexts/eldredge.pdf
•Federal Aviation Administration (2016). FAA News: Summary of Small Unmanned Aircraft Rule (Part 107). http://www.rtca.org/files/Part_107_Summary.pdf
•Federal Aviation Administration (FAA) and Office of the Secretary of Transpiration (OST), Department of Transportation (DOT) (2016). 14 CFR Parts 21, 43, 61, 91, 101, 107, 119, 133, and 183. http://www.faa.gov/uas/media/RIN_2120-AJ60_Clean_Signed.pdf
•House of Representatives (2012). FAA Modernization and Reform Act of 2012. U.S. Government Printing Office. Washington. http://www.faa.gov/uas/beyond_the_basics/
•Roskop, Lee (2012). U.S. Rotocraft Accident Data and Statistics. Federal Aviation Administration. https://www.aea.net/events/rotorcraft/files/US_Rotorcraft_Accident_Data_And_Statistics.pdf 6/20/2016.

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