Between the Poles

Identifying areas of high risk vegetation encroachment on power lines from satellite imagery

Vegetation is a significant source of outages for many utilities. In some regions from one quarter to one half of all outages can be ascribed to vegetation. Vegetation encroachment initiated the massive North American Northeastern outage of 2003. With the growing incidence of extreme events managing vegetation near power lines is becoming increasingly crucial in tackling potential fire hazards, securing infrastructure increasing resilience. The traditional approach to identifying areas of high-risk vegetation encroachment involves helicopters and ground crews and is time consuming and costly. Drones have been used to reduce the cost of data collection, but it is still a costly process. Now an innovative startup is using satellite imagery together with deep learning to identify high risk areas of vegetation encroachment. By applying machine learning algorithms to high resolution satellite imagery, it is possible to distinguish vegetation from other objects, differentiate trees from grass and bushes and identify trees at risk of encroachment. Comparing a drone-based approach with the satellite imagery methodology reveals that the latter approach is highly accurate in identifying high risk areas and significantly less costly than a drone-based process.

Background

Power line inspections for vegetation management and other purposes are essential in ensuring grid reliability and resilience. They are generally performed by manned helicopters or by a ground crew. Data is collected with cameras and analyzed to detect diseased trees that could fall and hit a power line (fall ins) or trees that are encroaching on power lines (grow ins). These inspections are mandated by NERC in North America and are not optional. Beyond visual line of sight (BVLOS) drones have reduced the cost of collecting line inspection data. Now a new company is reducing the cost of identifying trees at risk by analyzing high resolution satellite imagery to identify high-risk areas, thus reducing the total length of power line that requires more detailed inspection with drones, helicopters, or ground crews.

Evolving machine learning models at Spacept

A Swedish company Spacept has developed a vegetation management solution that applies machine learning models to multi-band satellite imagery to automatically identify areas of high risk for vegetation encroachment on above-ground transmission and distribution lines anywhere on the planet. Spacept develops its own in-house training data for machine learning models which enables follow-up ground inspections of areas of high risk to develop pruning and other response programs. The training data is constantly enhanced with feedback from new projects for continuous improvement of the models.

Satellite-based vegetation encroachment risk assessment

The key business benefit of Spacept’s satellite imagery-based solution is automating the process for identifying the high-risk areas that require ground-based inspection, whether helicopter, drone-based, or ground crew, thus significantly lowering the cost of vegetation encroachment inspections. Spacept’s satellite-based vegetation encroachment technology makes it possible for power grid operators to monitor vegetation encroachment over their entire infrastructure in a cost-effective manner. Spacept uses the most recent, highest resolution (0.50 – 0.30 cm) satellite imagery commercially available which satisfies the requirements for vegetation encroachment detection. Spacept's approach makes it possible to monitor hundreds of thousands of kilometers of power lines every year anywhere in the world.

Workflow

The workflow of identifying and downloading satellite imagery, applying machine learning for feature identification, and the assignment of risk categories to individual trees is currently a semi-automated process. The longer-term objective is to reduce manual intervention and achieve an end-to-end automated workflow. The current workflow proceeds from a geographical layout of the power line to be inspected in the form of a standard GIS file. The most recent available high resolution satellite images satisfying certain criteria are identified and downloaded from data providers. The criteria typically include panchromatic and multi-spectral bands, resolution of at least 50 cm, vegetation capture with leaf on, and minimal cloud coverage. The downloaded images are fed to the current vegetation model which automatically extracts features and distinguishes trees from other man-made and natural objects. One of the important capabilities of the model is that it is very efficient in differentiating trees from bushes. After the automated processing, the imagery and labelling are reviewed by experienced assessors who review each image and make corrections to the labelling for problem areas, for example, for cases of visually distinguishable bushes or edges of trees. After completion of the labelling step, the distance between each tree and the power line is calculated and a risk category is assigned using risk categories provided by the client. The final deliverable is a GIS file containing the location and the corresponding risk categories assigned to the trees.

In-field case study

To assess the potential business benefits of satellite-based analysis Spacept partnered with infrastructure health management platform Sterblue to apply their satellite-based power line vegetation management solution for thousands of kilometres of a French power grid operator grid. Spacept applied their algorithms to selected satellite imagery to generate a risk file for the targeted segment of the grid. Sterblue assigned emergency (risk) levels based on the distance from the power line using a classification of emergency levels provided by the grid operator. Sterblue then carried out in detail inspections of at-risk areas with its drone inspection fleet. A ground inspection team was sent to verify the locations of the trees physically and collect ground truth. A total of 283 locations were identified. The vegetation at each location was manually validated and was compared with the satellite predictions.

The most important conclusion on the business benefit of the satellite imagery-based analysis is that it was able to identify all the trees that the subsequent ground inspection identified as at risk. In a real-world scenario, applying the satellite imagery analysis as a first step in a power line inspection would dramatically reduce the area and trees that would require ground-based inspection using helicopter or drone-based inspection. As a result of this process, Sterblue reduced its operating costs by 80%.

A more detailed analysis of the satellite data attempted to classify trees into detailed emergency levels U0 to U3. Comparing this analysis with Sterblue's classification was used to create a "confusion matrix" showing instances of agreement and disagreement between the two analyses. It was found that there was good agreement between the satellite and ground-based inspections and analyses.

Conclusion

Several companies have recognized that earth observation imagery is of limited value without the application of analytics to interpret the data. For example, Spacept is applying analytics to the huge amount of earth observation data to provide a valuable high risk vegetation encroachment detection service that is safer, faster, and less costly than ground-based approaches to transmission and distribution line vegetation monitoring.

Pilot project to create national map of UK energy infrastructure launched

A proof-of-concept project to develop a National Energy Systems Map (NESM) has been launched by the UK’s electricity and gas networks. The pilot project will give customers information about energy network assets, where those assets are located as well as who owns them. This project is a result of a core recommendation of the Energy Data Taskforce for the development of a digital system map of the UK energy network infrastructure with the overall goal of developing a full digital twin of the UK energy system.

Background

In October 2018, the Department for Business, Energy and Industrial Strategy of the UK government launched the Energy Data Taskforce, led by Energy Systems Catapult and supported by Ofgem and Innovate UK.  The objective of the task force was to determine how to release the power of data within the UK energy system. The final report A strategy for a Modern Digitalised Energy System provided a suite of recommendations on how data can contribute to developing and maintaining a decarbonized, decentralized and efficient energy system.

In most of world's major economies energy is increasingly decentralized increasingly relying on distributed energy resources (DER). Many assets such as electric vehicles, electric storage heaters and home batteries are capable of not only of consuming power but also able to generate it.  Modern assets are smart and able to signal and receive signals from network operators. Reducing the carbon content of power generation is a worldwide objective supported by governments, regulators and the utility industry.  New business models for utilities are emerging which reflect this new grid.  The UK government sees data as the key to unlocking the potential of the new grid. Transparent, accessible, interoperable and accurate data is seen as key to enabling network operators to adapt to and exploit the opportunities created by the new grid.

In the current energy system there are barriers to the effective use of data; no common data standards, no openly shared data repository and a culture of data hoarding rather than sharing.  It is estimated that a smart and flexible system can contribute to cumulative savings of up to £40 billion by 2050.

Development of a national digital energy map

One of the key recommendations of the task force is the development of a unified digital system map of the UK energy system. Such a map is intended to make infrastructure data accessible to all, to lower the barrier to entry and enable developers to create new solutions and validate new business models. Interoperability of network data is intended to provide networks, Ofgem and developers with efficiency benefits reducing data preparation and translation requirements.The digital energy system map will become one of the three data building blocks that will transform the energy system; a data catalogue which will provide a single, searchable location for energy system datasets, an asset registration strategy for identifying assets, and the digital system map that will provide a digital representation of the UK energy system.

The list of actions of the energy digitalization strategy in the recent Digitalising our energy system for net zero: Strategy and Action Plan 2021 includes the procurement of a National Energy System Map, with a proof of concept delivered by Q4 2021. The map will initially present datasets shared by network companies but is intended to grow and evolve with the addition of other energy sector data and potentially data from other sectors. To begin the implementation of this objective the Energy Networks Association has kicked off the development of a National Energy System Map for mainland UK that initially will encompass electric power and gas network data.  It is intended that this energy system data will be made publicly available as a digital map. The Energy Networks Association intends to deliver a proof of concept of a national energy system map in Q4 2021.

It is foreseen that a digital energy system system map will provide significant benefits; more efficient planning of renewable energy projects and future energy system infrastructure, more rapid development of new business models for energy, data standardization and interoperability, and increased energy system resilience through better system visibility.  In addition it will provide a foundation for the development of a digital twin of the UK's energy network.

Digitalizing the as-builting process essential for accurate underground utility mapping

Over the past decades electric, gas, water, and telecom utilities have poured millions into digitalizing the graphic design/work management and GIS/records management processes. But in spite of this the decades-old as-builting process remains marred by manual paper-based processes that have ramifications for industry and society in general. As-builting is characterized by inefficiency that causes critical processes such as outage restoration to require more time than they should and low data quality which leads to incomplete, out of date and inaccurate underground utility records that are responsible for frequent construction delays, injuries and fatalities for workers and the public, and a drag of billions of dollars on national economies.

Dated, paper-based as-builting workflow

One of the biggest and most persistent problems for almost all utilities is the use of paper in the construction as-builting process.  It is a challenging problem that has been with us for decades.  The first post of this blog in February, 2006 discussed this problem and in some respects the as-builting workflow has not changed that much since then.  Over the past decades utilities have spent millions of dollars digitalizing design (CAD) and records management (GIS), but the gap between them has remained filled with paper. The schematic shows a typical design, construction to GIS workflow that's in place at most utilities today. Design is done using a graphic work design system (CAD) in the office that is integrated with a work management system. A paper job packet is sent to the construction crew in the field who attempt to follow the design drawing. More frequently when contractors take the design drawings out into the field, they often find that obstacles, such as existing utilities or other infrastructure even old tram lines or sewer lines, force them to make changes.  After completion of construction paper as-builts are prepared that make their way back to the office to be entered manually into the records system typically a GIS. If the construction crew has had to make some changes, these are supposed to be redlined on the design drawing, but all too frequently the crew simply hit the easy button and check the box that says, "We built it exactly as you designed it." The reality is that 90% of designs change in the field and the changes are rarely recorded. This is a major source of data quality issues and is the chief reason for the general unreliability of utility GIS records. Unreliable underground records lead to construction delays, budget overruns, injuries and even fatalities for workers and the public. 

The as-built workflow is also fraught with inefficiencies because many of the processes are manual.  The result is massive mapping backlogs. Backlogs of 30, 60, 90 days from construction complete to being entered in the GIS are common. The result is that the utility GIS is always out of date and critical processes such as outage resolution require more time than they should. 

If we are to address these issues it is imperative that we improve the way buried assets are designed, constructed, recorded, and managed.

Grid modernization is driving change

As a result of being asked to do many more things than in the past, the grid is being transformed from a centralized to a distributed model. For electric utilities, utility digital transformation is already driven by increased demand for distributed energy resources (DER) such as solar, wind and other renewable technologies. This creates a requirement for an advanced distribution management system (ADMS) which is the intelligence that supports the new distributed smart grid model. These developments are being accelerated due to COVID-19 and the requirement for a more touchless environment for utilities. The bottom line is that for these advanced solutions to provide full value a reliable digital twin of what is out in the field is essential, and right now for most utilities that remains a challenge.

Grid hardening to increase resilience is another major initiative that is contributing to transforming the grid.  When a utility experiences a major storm, flood, catastrophic wildfires, or other natural disaster it has to change its infrastructure plans.  It may have to move overhead wires underground, move transformers out of flood zones, or ameliorate the risk to substations.  The sheer glut of aging infrastructure replacement programs is also increasing pressure on utilities and contributing to a significant increase in construction activity. Grid transformation on this scale with the sheer volume of new construction that it required is forcing utilities to find ways improve productivity by managing construction data from source to consumer digitally.

As-builting remains a persistent problem

However, a major source of construction inefficiency remains. Why, after decades of growing awareness of the inefficiency and data quality issues associated with the traditional as-builting workflow, are construction as-builts still recorded on paper ? First of all, there's resistance to change. Utility construction is managed using a variety of manual, paper-based processes that have been in place for decades. Secondly, there's the aging construction workforce that has always relied on legacy processes and has not seen reason to change. Another problem is that well-established enterprise systems such as asset management and GIS don't provide the comprehensive solution that construction crews need to digitalize the full process. Those systems are designed to support long cycle construction projects which typically require a month of planning and may not be completed for six, nine, or twelve months. 

An important factor that makes this problem so persistent and difficult to resolve is the many personas involved. The as-builting workflow is tasked with taking highly technical engineering output from the designers, translating it into instructions that a construction crew can use to safely build the job to code and to standard, then asking a field engineer to draw up the as-builts, and converting those paper drawings into geospatial data that a GIS technician can use to update the utility GIS. Technically this is a complex process that involves distinctly different personas that work in different teams with different technical vocabularies, different training, different software systems, and who are measured by different goals and performance indicators. It is further exacerbated by a lack of clarity as to who owns the as-builting process, engineering, construction, or records/GIS. The designer may point to the contractor as the owner. The contractor might think the GIS technical team is responsible and records/GIS group may think that the designer owns it. Often the real answer is that no one owns as-builting and that is the operative reason the problem has been so persistent for decades.

Digitalizing the as-builting workflow

To improve the efficiency and data quality of the as-builting process digital tools are required to help utilities bridge the gap between the design and the system of record. The key technologies making this possible are mobile applications and mobile devices, cloud technology, and the availability of economical high accuracy GPS. To be successful the tools need to be adapted to the different personas. For the construction crew end user persona a mobile first philosophy is essential to enable real-time data capture in the field. This requires easy to use mobile apps supplemented by high accuracy GNSS and devices such as bar code scanners.  Together these make possible the efficient capture of survey grade data and associated metadata greatly enhancing the speed, accuracy and fidelity of the data feeding the utility systems. In addition a digital data stream makes it possible to update the system of record more rapidly.  This result is the records/GIS to become more effective in producing reliable as-built records that locate and construction crews can rely on.  For utilities that have adopted this approach, enabling field crews to digitally capture construction data is now a best practice.

Example: Digitalizing the mapping of underground duct banks

As a real world example a contractor serving some of the largest utilities in the West Coast of the U.S. was faced with new requirements for the construction project they were working on for a utility customer.  They were now required to capture GPS locations real-time during construction.  Precision was required to be two-tenths of a foot (2.4 inches) or better and location data points were to be collected every 25 feet for linear assets. The contractor had not had to meet requirements like this before on a major project. The scale of this project made the new requirements even more challenging; 35 sites throughout the Central Valley of California, 35,000 feet of trenching, auger bores under highways and railroads, and many primary enclosures.

Fortunately the contractor had had experience with digital construction processes on smaller projects. Based on their previous experience, they were convinced that a member of their own construction crew already on site could capture the location data with the required precision. Having in-house capability for capturing survey grade construction data would allow them to deliver the data without having to have a survey crew on-site or managing outside survey crews. The benefits they hoped to realize were cost savings associated with not having to hire an outside survey crew and related intangibles such as not having to coordinate schedules for survey crews and holding up construction while waiting for survey crews to arrive. However, they were concerned that the the additional training and work load required to capture location data could potentially disrupt their construction crews' schedules.

Key project achievements of digital construction workflow

The implementation of the digital workflow by construction crews actually proceeded rapidly. Crews were capturing survey grade GPS data within days.  Over a period of six months using the solution at 23 active construction sites, over 16,000 feet of buried linear assets, including duct banks and tracer wires, were mapped and some 5,000 supporting photos along the way were captured. The median GPS accuracy of the data captured by their construction crews was 0.14 feet, a remarkable achievement that exceeded the project precision requirement.  Their customer even requested them to go back to pothole and capture accurate locations for trenches that had already been covered over before they began using the new digital process. The many photos that were collected along the way and geotagged to specific locations provided a valuable record of everything that was done in the field for future reference.

Benefits of digital construction workflow

One of the important results of the project was that their initial concern that digital capture in the field by construction crews might disrupt the crews' daily routines never became a problem. Construction crews were able to collect as-built data from open trenches using mobile devices with high accuracy GPS without disrupting their normal processes or impacting their schedules. An important cost benefit was that they didn't have to employ and coordinate survey crews.  Instead of calling in a survey crew they were able to employ one of their own crew members who was already on site to capture survey grade location data. This resulted in an estimated project time savings of around 20%.

An important advantage of the the digital construction process they used enabled them to spot when crew members' shots did not achieve the required project precision. The ability to identify and flag data that exceeded the 0.2 foot accuracy requirement and needed to be repeated was an important factor in achieving the overall project precision goal. Flagging low precision data also avoided the costly process of having to send a vac truck out after the trench was filled to do potholing and retaking shots. Another benefit was automated close out enabling them to receive automated data exports without having to do any paperwork.

The major achievements of digitialization were that survey grade as-builts could be captured in near real time with no disruption to construction crews' schedules, the utility GIS rapidly updated and able to provide up to date, high accuracy underground utility records and all of this at lower cost. Overall the project realized an estimated cost savings of around 50% mainly because fewer man hours were required.

This post is based on Danny Petrecca's talk at the Canadian Underground Forum (CUF). You can listen to all the talks at CUF on the GeoIgnite CUF Youtube channel.

Canada plans to allow BVLOS drone operations in remote areas without a waiver

Canada plans to introduce in 2021 certification that would allow pilots to undertake beyond visual line of site (BVLOS) flights in isolated areas without the need for a waiver. This opens the possibility of more frequent, low cost inspection possibilities for transmission utilities with large stretches of line running through vast open areas or forest corridors.

Background

Transmission line inspections for vegetation management and other purposes are essential in ensuring grid reliability and resilience.  They are generally performed by manned helicopters or by a ground crew.  Data is collected with cameras and analyzed to detect diseased trees that could fall and hit a powerline (fall ins) or trees that were encroaching on power lines (grow ins).  These inspections are mandated by NERC in North America and are not optional.  Beyond visual line of sight (BVLOS) drones (UAVs) and software analytics using machine learning has made it possible to approach completely automating this expensive process.  Electric Power Research Institute (EPRI) has estimated that the reduction in cost with using an automated UAS compared to a helicopter inspection is between 55% and 28%. Automating transmission line inspections for vegetation management using BVLOS drones not only saves money but also could improve the resiliency and reliability of the transmission grid.

There are other important use cases as well including precision agriculture, public safety for search and rescue missions and delivery services to remote and rural communities.

Currently, there are two levels of drone pilot certification in Canada – basic and advanced – which roughly correspond to the FAA’s Part 107 waivers in the US. New rules for commercially operating UAVs in the U.S. were published in 2017 by the FAA as Part 107 of the Federal Aviation Regulations.  For non-standard flights, such as BVLOS missions, Canada require operators to acquire a Special Flight Operations Certificate (SFOC) which requires operators to fly their drones beyond visual line-of-sight in isolated areas outside of concentrated population centres and not near restricted airspace such as airports.  In addition there are special provisions for drones with onboard detect-and-avoid (DAA) solution which allows them to fly safely without human intervention even in populated areas.  For example, in March 2020 first approval for BVLOS drone flights was granted in Canada for Iris Automation’s Onboard Detect-and-Avoid technology.

However, Canada plans to introduce in 2021 a tier of certification that would allow pilots to undertake BVLOS flights in low-risk conditions without need for a waiver. This opens possibilities for transmission utilities with large stretches of line running through vast open areas or forest corridors.

Proposed routine BVLOS flights without a waiver

In January 2019, Transport Canada (TC) published new RPAS regulations for operations within visual line of sight (VLOS), and these regulations permit BVLOS operations under low-risk conditions with the issuance of a Special Flight Operations Certificate (SFOC). In April 2020 Transport Canada posted a new Notice of Proposed Amendment (NPA) to update Canadian regulations to allow for routine beyond visual line of sight (BVLOS) drone operations in “Low Risk” environments. The proposed regulatory amendments would be the first of a series of steps towards allowing more routine BVLOS operations. These amendments will not address more complex and higher-risk BVLOS operations in populated areas. Higher risk BVLOS operations will be subject to a separate regulatory process at a later date.

This proposal aims to begin to unlock the potential for beyond visual line-of-sight operations in Canada. Specifically Transport Canada is proposing the following amendments for isolated areas.

• 250 g to 25 kg BVLOS operations in isolated areas; within 1km of an area with a population of more than 25 people per square km; over an area with a population density of more than 25 people per square km; and, in controlled airspace;
• 25 kg to 150 kg BVLOS operations in Isolated Areas, and within 1km of an area with a population of more than 25 people per square km; and,
• 150 kg to 650 kg BVLOS operations in Isolated Areas with a max altitude of 400 feet above ground level.
  

Growing gap in electric power infrastructure investment in the U.S. will decrease reliability and resilience of the grid

Last week the American Society of Civil Engineers (ASCE) released a new report in the Failure to Act series "Electric Infrastructure Investment Gaps in a Rapidly Changing Environment" that estimates the investment gap through 2039 for electric power infrastructure in the U.S. and assesses the impact of under investment in electric power infrastructure on the U.S. economy.  Modern economies are increasingly dependent on "chip technologies" powered by electricity. Recent projections suggest that ICT consumption of electricity could reach over 20% of total demand by 2030 with data centres consuming over a third of that.  It is estimated that the average cost of an outage at a data centre is about $8,851 for every minute the electricity grid is disrupted,

Background

Just about everything that we use daily from phones and the internet to water and wastewater rely on electric power. In addition as we reduce the carbon footprint of the economy, electric power becomes increasingly important because in most jurisdictions electric power has a low or decreasing carbon footprint compared to other sources of energy.

The U.S. electric power grid is composed of the bulk power system including large-scale generation facilities and the transmission network. 10,000 power plants comprise the generation capacity of the U.S., not including residential solar panels or small-scale wind farms.  More than 600,000 circuit miles of transmission lines, of which 240,000 are high-voltage, carry power from generation plants to the distribution nrtworks. An estimated 5.5 million miles of local distribution lines (including underground cables) carry the power to end users.

Increased ICT consumption of electricity

One of the sectors that is projected to consume an increasing share of the U.S. electricity supply is information and communications technology (ICT).  Currently it is estimated that the share of electric power consumption by ICT is between 5 and 9% of total power demand. Currently  ICT’s electricity consumption has plateaued.  Increasing load from growing Internet traffic and chip technologies has been balanced by increased efficiencies. But this may change in the next few years. Forecasts suggest that the total electricity demand by information and communications technology (ICT) will accelerate and that of the ICT pie data centres will take a larger slice. The chart shows an "expected case" projection which shows that ICT consumption of electricity could reach over 20% of total demand by 2030.  ICT requires a reliable and resilient power grid and will be one of the most important drivers to address the gap in investment in electric power.

A related aspect of the U.S. economy is a structural shift away from energy intensive industries such as heavy manufacturing. A measure of this is energy intensity which is the amount of energy that is required to produce one dollar of GDP.  In 1980 12,100 BTUs were required to create one dollar of GDP.  By 2014 this had declined to 6,100 BTUs per dollar. About 40 percent of the improvement in energy intensity was attributed to structural shifts, and the remainder to improved efficiency.

Gap in investment in electric power

Over the period 2011-2020 demand growth estimated at about 8% has been net with increased generation capacity. But for the period 2021-2040 the report projects increasing divergence between demand and capacity. If current trends are projected into the future the U.S. is facing a $208 billion (in 2019 dollars) shortfall by 2029 and a $338 billion shortfall by 2039 in what is needed to ensure a reliable energy system.  Most of this shortfall is attributed to under investment in generation and transmission. For transmission the largest challenge is not so much attracting investment in transmission, but that regulatory approval from all levels of government averages about 10 years for a new transmission line and can amount to 50% of the cost. Unlike Germany where the Bundesnetzagentur has national authority over long distance transmission lines, for bringing wind power from the North Sea to the south, for example, in the U.S. states are the top level regulatory authorities for transmission lines and a rule of thumb that has emerged is that to build a transmission line as rapidly as possible, don't cross state boundaries.  The demand for new transmission is exacerbated by the growing sources of renewable energy generation in the West that require new transmission lines to bring the power to the East and the Pacific Coast.

Impact on the economy

For consumers electricity system outages, voltage surges, and brownouts represent a direct cost to their households and businesses, and indirectly through impacts on the national economy. It is estimates that the cost to residential customers from each electric interruption event was $6.68 (2018 dollars).   This is about twice as high as it was five years earlier partly because or our increasing reliance on chip technologies in out daily lives.

When the grid fails businesses experience downtime, lost labour and productivity.  The report found that outages have the biggest impact in the manufacturing sector, costing almost $42,000 per event on average in 2008. As a result of the growing importance of ICT, data centres have become essential for many different industries. It is estimated that the average cost of an outage for a data centre increased from $505,000 in 2010 to $740,000 in 2016, or about $8,851 for every minute the electricity grid is disrupted.

Furthermore, disruptions to the grid add to costs and can result in U.S. manufactured products becoming less competitive in international markets. Between 2020 and 2039, it is estimated that the gap in investment in electric power will result in the loss of $271 billion in the value of U.S. exports.  In addition businesses and households will have to pay an additional $142 billion for foreign imports.

Innovative solution efficiently captures accurate underground utility as-builts during construction

Most of underground utility damage during construction is attributable to incomplete, inaccurate and out of date records and network documentation. This data is the result of an inefficient, error-prone, and paper-based information flow from engineering, through construction crews, and resulting in "as-builts" of uncertain quality which eventually form the utility's repository of record, typically in a GIS.  Recently a mobile solution has been developed that ensures that centimetre-level accurate as-builts are efficiently captured in the field in real-time. By digitalizing and automating the collection and validation of all construction data, accurate and up-to-date as-builts become the new normal.  Already used by over half of the 20 largest energy companies in the US, the Locusview system is being extended to support natural gas utilities, electric power utilities and telecom.

Background

Without accurate maps of underground infrastructure, every construction project has the potential to become an expensive disaster site. In the U.S. there are between 400,000 and 800,000 incidents of underground utility damage every year. Every year there are injuries and fatalities attributable to underground utility damage during construction. According to the Federal Highway Administration (FHWA) missing or inaccurate location information about underground utilities is a major source of highway construction project delays. The drag on the U.S. economy resulting from underground utility damage is estimated to be at least $50 billion annually.

Inefficient, error prone construction information flow

90% of underground utility damage during construction is attributable to incomplete, inaccurate and out of date records maintained by utilities and telecoms as well as data format issues including paper and digital ink (pdf).  The reason for unreliable records of network infrastructure can be found in an information flow that is found at every utility and telecom.

The design-build-maintain information flow begins with an engineer and drafter producing a design, typically a CAD drawing, which is printed for construction contractors to use in the field in installing new underground network infrastructure. Typically the design is based solely on above-ground surveys because information about existing underground infrastructure is unreliable or missing. The construction contractor may attempt to follow the paper design drawing, but for a variety of reasons what actually ends up in the ground differs from what was designed.  The design drawing, nominally an "as-built" but typically an “as-designed”, is then returned to the records management/network documentation group who enter it into the utility's GIS where it forms the permanent record of the utility or telecom's network infrastructure. This process is slow and error-prone and backlogs of as-builts waiting to be entered into the GIS stretch into months. The result is that utility and telecom GIS data is often inaccurate, out-of-date and incomplete.

Accurate as-builts are becoming mandatory

To address the problem of unreliable as-builts and the associated human and economic consequences several governments have enacted legislation and regulations requiring the submission of accurate as-builts.  Montana has recently revised its statutes governing the installation of utilities on state highway right-of-ways.  An updated Administrative Rule mandates that as part of a new permitting process accurate electronic as-builts must be submitted to the Montana Department of Transportation (MDT) upon completion of construction.  To ensure accuracy the regulations require that the as-builts be stamped by a licensed professional engineer (PE) or professional land surveyor (PLS). 

In 2017 the Singapore Land Authority (SLA) released a standard and specifications for the procedure and practice of utility surveying in Singapore.  The standard specifies that after installing utilities and prior to filling the trenches an as-built survey must be performed by a registered surveyor to capture the location of the utilities with horizontal accuracy of ±100mm and vertical accuracy of ±100mm.  In addition the standard specifically identifies the survey equipment to be used; total station, GNSS Real Time Kinematic (RTK), or 3D laser scanning.  This standard is not mandated, but provides a baseline to be incorporated in all government construction contracts.

In response to the requirement for accurate as-builts, the challenge for contractors is to capture accurate as-builts without adding to field crew workload and without impact to project schedules.

Digitalizing the construction information flow

Locusview was founded in 2014 as a spin-out of the US Gas Technology Institute (GTI) with industry funding to develop next-generation digital construction technology for the energy and telecom industry

Locusview has adopted a paperless, digital approach based on a mobile app that makes field crews the nexus for efficiently capturing accurate as-built information.  The user-friendly mobile application makes it easy and even attractive for crews in the field to move from a manual, paper-based process to one in which all construction data is digitally captured and validated in real-time during construction.  In addition to ensuring that as-builts accurately represent what was actually built in the field, this approach reduces time and costs in field data collection, reduces the time required to prepare as-builts for submission, and ensures that data gets into the GIS faster.

During construction field crews use the Locusview Mobile app with high accuracy GPS and barcode scanners to capture as-builts, track material usage, capture photos and support other field operations such as joints, splices and welds. But the app doesn’t just capture the asset information, it also validates that the information is complete and accurate according to the company’s data requirements and construction standards. Locusview captures material data faster and more accurately with automated feature creation and attribute generation using barcode scanning. In the case of gas utilities information on all welds and joints needs to be recorded because if done incorrectly welds and joints can lead to leaks and other problems. Locusview helps ensure that these processes are carried out correctly by capturing real-time pictures and by validating welder qualifications (OQ).

High accuracy GPS is implemented in several ways.  RTK base stations can be used for real-time high accuracy GPS. In GPS denied areas a laser range finder can be deployed. Alternatively control points can be used to ensure accurate georeferencing.

Back in the office the Locusview Web application enables visibility into the real-time status of projects, making it easier to assess progress and to project revenue streams. It also provides for data validation with automated warnings and notifications of violations; review and approve pre-configured check lists; exporting data to GIS, ERP and asset management applications; reports generation and project closeout.

Benefits

There are several critically important benefits that Locusview provides.  Most critically it provides for real-time reality capture, ensuring construction quality by enabling survey-grade accurate location, attributes and material data to be recorded by construction crews as new infrastructure is installed.  This ensures that as-builts are accurate and material usage is verified and traceable. It reduces the time to prepare as-builts for submission and speeds up the process of getting the as-built information into the utility's GIS by up to 70%, which is also crucial for emergency repairs. Having full visibility over the project’s status information in real-time using Locusview’s web tool makes it easier to track project progress and to project revenue streams. The field visibility also enables supervising the work remotely, which is helpful during Covid-19 times. In addition, time and costs are reduced for capturing and managing construction data by eliminating manual paper-based processes.

Just as importantly Locusview ensures that field construction information is captured efficiently. Maintaining a survey team on site to survey newly installed pipes and cables can be prohibitively expensive especially for smaller projects.  In actual projects it has been found that Locusview can reduce surveying costs by 50%.

In summary, utilities and telecoms use the technology to build a high-quality digital twin, to support asset management strategies and to ensure regulatory compliance.

Electric power case study

VPI, a Charge company, specializes in the construction of utility-grade electric power distribution infrastructure. During a recent major project involving 35,000 feet of open trenches and 35 construction sites for a large electric power utility in California the as-built requirements changed for both above and below-ground distribution infrastructure. Among the new requirements: as-built locations had to be accurate to ± 0.2 feet (± 6 cm).   One of VPI's major concerns was the cost of keeping a professional survey crew on-site at all times to capture the location of infrastructure to survey accuracy.

VPI looked for an alternative that would lower costs and provide the flexibility of not having to coordinate with outside survey crews.  VPI's main concerns were how to efficiently meet the high accuracy requirements, how to optimize the training and education of field staff, and avoiding adding to the work load of their field crews.

Locusview implemented their solution for VPI to meet the new high-accuracy GPS as-builting requirement that included the mobile app, web app and additional RTK base station coverage. The mobile app was found to be easy-to-use after only four hours of training for field crews. Most importantly using the mobile app instead of a traditional survey crew did not add to field crew workload and was able to be implemented without impact to schedule. Remarkably for this type of project the process only required 10 days from first contact to beginning data collection. 

It enabled 16,362 feet of linear electric power assets to be mapped with a median accuracy ± 0.14 feet (4 cm).  Nearly 5,000 photos were captured for future reference. With the web application crew foremen were able to monitor construction progress in real-time to ensure data collection was complete and met their requirements before back filling trenches.  Avoiding the need to coordinate with outside survey crews resulted in a time savings of ~20% in project management for closeouts and reduced time in the field. Overall VPI realized cost savings of ~50% from reduced man-hours.

Conclusion

This remarkable application provides a solution to the decade-old challenge of efficiently capturing high accuracy as-builts in real-time and eliminating the problem of as-built backlogs.  Gas is the most dangerous underground utility and it is not surprising that the development of the Locusview solution was fostered and heavily adopted by the gas distribution industry.  Jurisdictions are beginning to require high accuracy as-builts from energy companies, electric power utilities, water utilities and telecom as a basis for a digital twin. To capture accurate as-builts efficiently is the challenge that Locusview addresses. The VPI case study shows that Locusview is able to provide efficient solutions for capturing accurate as-builts without adding to field crew workload and without impact to project schedules. This solution offers important benefits for any field constructed linear asset.

Using satellite imagery to prioritize vegetation management for utilities

A recent startup LiveEO is focusing on the digitalization of energy and transportation network assets using satellite imagery. LiveEO uses current multi-band imagery including radar and hyperspectral data at various resolutions from earth observation satellites to provide services to railway, electric power and pipeline operators.  The services include vegetation, third party encroachment, and ground distortion monitoring. I recently had the opportunity to chat with Sven Przywarra, co-founder of LiveEO.

Transmission line inspections are essential in ensuring grid reliability and resilience.  They are generally performed by manned helicopters often together with a ground crew.  There are serious safety issues when inspections are conducted by helicopter. Data may be collected with cameras and analyzed to detect a variety of conditions including corrosion, evidence of flash over, cracks in cross arms, and right-of-way issues such as vegetation encroachment. in North America annual inspections are mandated by NERC  and are not optional. With over 200,000 miles of high-voltage transmission lines and 5.5 million miles of distribution lines in the United States, improving the efficiency and reducing the risk of inspections would have a major impact on the reliability of the power grid. 

Vegetation is a significant source of outages for many utilities. In some regions from one quarter to one half of all outages can be ascribed to vegetation. Vegetation encroachment initiated the massive North American northeastern outage of 2003. It is so critical for utility operations that some utilities have a vice president responsible for vegetation management. It can be costly for utilities to identify areas of high risk vegetation encroachment. Previously I have blogged about an electric power utility in Brazil that used Airbus Pléiades satellite imagery combined with GIS data to identify high risk areas for vegetation encroachment in a power grid.

A recent startup LiveEO is focusing on the digitalization of energy and transportation network assets using satellite imagery. LiveEO analyzes current multi-band imagery including radar and hyperspectral data for vegetation, third party encroachment, and ground distortion monitoring. LiveEO uses multi-band imagery at various resolutions to distinguish vegetation and network assets, stereo imagery to estimate tree heights, difference detection to identify changes, and interferometry to detect subsidence and other ground distortions at the cm level.  LiveEO is developing its own inhouse training data for machine learning algorithms. 

For electric power utilities LiveEO applies machine learning multi-band satellite imagery from multiple sources to automatically identify areas of high risk for vegetation encroachment and fallover anywhere on the planet. The results of these analyses are available to clients over the web on handheld and other devices.  This enables follow-up ground inspections of areas of high criticality to develop pruning and other response programs. LiveEO has applied this approach to transmission as well as distribution circuits.  To demonstrate the wide ranging capability of their approach LiveEO is offering a demonstration of the analysis of 50 km of line anywhere in the world.

A number of companies, realizing that earth observation imagery in itself is of limited value, are not in the business of selling imagery, but the results of analytics applied to the imagery.  I have blogged about a new company GHGSat who use their own nanosatellite to estimate emissions from industrial plants, leaks from flow and gathering infrastructure in natural gas fields, and even livestock.  LiveEO is another example of a company who apply analytics to the huge amount of earth observation data to provide a valuable service that is safer and less expensive than the traditional approach to transmission and distribution line vegetation monitoring.

Automated drone systems improve power line inspections and reduce costs

Transmission line inspections are mandatory in North America. Traditionally helicopters are used for these inspections, but with helicopters the risk of accidents is significant and helicopters are costly to maintain and operate.  Drone inspections dramatically reduce the risk of accidents.  Aeriosense Technologies has developed an automated drone inspection system that can reduce the cost of inspections by up to 55%. 

Background

Transmission line inspections are essential in ensuring grid reliability and resilience.  They are generally performed by manned helicopters or by a ground crew.  Data may be collected with cameras and analyzed to detect a variety of conditions including corrosion, evidence of flash over, cracks in cross arms, and right-of-way issues such as vegetation encroachment. Inspections every year or 18 months are mandated by NERC in North America and are not optional. 

With over 200,000 miles of high-voltage transmission lines and 5.5 million miles of distribution lines in the United States, improving the efficiency and reducing the risk of inspections would have a major impact on the reliability of the power grid.  Drone technology, legislation and regulations enabling beyond visual line of sight (BVLOS) flights, software for planning flights and analytics for feature identification are making it conceivable that the expensive process of inspections could be completely automated.  Even now current technologies make it possible to dramatically reduce the cost of power line inspections. According to Navigant Research, globally electric utilities are expected to spend over $13 billion a year on drones and robotics by 2026, a dramatic increase from about $2 billion currently. 

Automated drone inspections

Flight plan for transmission tower inspection

Using automated unmanned aerial systems (UAS) Aeriosense Technologies can reduce the cost and improve the safety of vertical infrastructure inspection.  Unlike many other companies which offer drone services to many different industries, Aeriosense focuses only on the electric power sectors, currently transmission but in the future distribution.  I had a chance to chat with Alex Babakov, a co-founder of Aeriosense, who has many years of experience in the electric power sector, including working for BC Hydro Research/ Powertech’s High Voltage Laboratory (HVL). 

Alex explained to me that Aeriosense provides a complete visual inspection of pylons and poles, cables, and right of way including vegetation encroachment using a UAS typically with a photo camera.  Examples of the types of problems that can be identified include broken strands in lines crossing canyons and rivers, corrosion on insulators and other equipment, evidence of flash over, cracks in cross arms, and problems in the right of way such as human or vegetation encroachment.  Aeriosense also conducts inspections as part of storm response to identify damage resulting from extreme weather conditions.

Flight plan for transmission line inspection

Automation enables Aeriosense's drone systems to provide higher quality inspections at lower cost. In preparation for an inspection flight, the available GIS and LiDAR data is analyzed with the aid of machine learning algorithms to create an optimal flight path.  With a flight path optimized in this way cost reductions of about 36% can be achieved compared to manually operated drone-based inspections.  Furthermore compared to manual drone inspections automated inspections reduce pilot fatigue and safety risks while conducting inspections.

Aeriosense is also active in distribution inspections. The sheer size of the distribution network in terms of total number of kilometers and number of pieces of equipment makes it clear that an automated approach is required. With current technology and regulations, automated inspections can be applied to some but not all distribution circuits. In the future with new technology developments and regulations automated inspections will be able to be applied to more distribution circuits.

Cost reduction

Based on data of inspection efficiencies from our past projects and the data coming from the field trials done by Electric Power Research Institute (EPRI) the reduction in cost with using an automated UAS compared to a helicopter inspection is between 55% and 28%.  The challenge is doing these cost comparisons is that there are intangibles that are difficult to quantify. Safety is one of these. Helicopter accidents are not infrequent in the electric utility industry and more often than not they lead to fatalities.  BC Hydro, for example, has a requirement for helicopters to be dual engine for redundancy and rates for this equipment are much higher.  Other utilities may not be willing to pay for the extra security whichl reduces the rates of the helicopters.

Improved safety

One of the most important benefits of Aeriosense's automated UAS approach is safety. Because of the relatively high risk of helicopter inspections, utilities have been looking for alternatives. Drone-based inspections are much safer and this provides additional motivation for utilities to move toward adopting drone-based inspections.

Development of training datasets for machine learning

Another benefit of the drone-based inspections are that utilities get a historical, unbiased record with the imagery that is captured by the drones. This enables engineers to go back and review the condition of assets not from a written record but from photos.  This provides a more objective view of how the condition of an asset has changed over time.

Collecting historical data has another important benefit in that it can provide a body of imagery that can be used to train machine learning algorithms. Collecting the data now will allow them to apply the AI tools currently being developed in the future.

Future applications of automated drone systems

The impact of more frequent, less costly inspections is improved reliability. Combining the efficiency of automated UAS inspections with defect detection using machine learning will allow utilities to get a very clear, timely situation assessment of their distribution system.  Aeriosense is currently working with the Centre for Energy Advancement through Technological Innovation on a project to help utilities identify current opportunities of automated drone applications and to develop best practices in implementing automated drone inspection programs.  Aeriosense is currently working in the transmission and distribution sector, but is actively exploring applications in the substations and generation verticals.

Another area that Aeriosense is currently piloting is the use of beyond visual line of sight (BVLOS) UAS flights for transmission inspections. FAA rules permit beyond visual line of sight (BVLOS) UAVs through Part 107 waivers.  I have blogged about Xcel Energy which obtained one of the first three waivers to fly UAVs for beyond visual line of sight operations. Xcel Energy estimates that flying drones beyond line of sight will eventually cost between $200 and $300 per mile, compared to helicopter flights that cost an average of $1,200 to $1,600 per mile.  More than 30 of these waivers have been granted and more than 20 companies are operating beyond BVLOS drones, still with some restrictions.  FAA very recently began allowing BVLOS operation using radar to track the location of the UAV.

Summary

Automated drone technology is already impacting transmission line inspections by improving safety, reducing the cost and time required to complete inspections, and by collecting an objective historical record that can provide training data for future machine learning applications. It not only enables more frequent inspections and improved reliability, but it also enables more rapid inspections, which is especially critical after a storm or other emergency situation. Research is underway at Aeriosense to determine the applicability of automated drone technology in other sectors, such as substations and generation, of the electric power industry.

Automating scan-to-BIM for brownfield substations

With about 55,000 substations in the U.S. and the average age of the transformers in these substations over 40 years old, many substations are going to be refurbished, retrofitted, extended or upgraded. Utilities are opting to create digital twins of their existing substations as part of this process to enable maintenance and upgrading activities to be performed more efficiently. For older substations records may consist in outdated 2D paper drawings or documents may be missing altogether.  New digital scanning technology together with machine learning is making it possible to semi-automate the process of creating intelligent BIM models from point clouds derived from laser scanning or photography.

primtech is a CAD-based design tool for designing high voltage substations.  An important recent enhancement Optical Symbol Recognition (OSR) allows point clouds from laser scanning or photography to be imported and then to apply machine learning to semi-automate the process of creating an intelligent BIM model. 

The software includes an extensive library, which contains more than four thousand intelligent 2D and 3D electrical devices from different manufacturers, steel structures, foundations, and wires and tubes.  The library has been growing for over 15 years and includes new equipment and elements as well as for legacy assets.  Each symbol (device, steel or foundation, etc.) has a specific geometric signature in the database in addition to meta data, file links, connection points and defined object behaviours. Together these comprise smart objects that enables objects in point clouds to be recognized and converted into an intelligent substation information model. The resulting intelligent model provides the basis for the calculations required in the substation engineering process.

The OSR process consists of two phases; first conductors are created and then equipment is added. A wire can be created by simply selecting three points, first anchor point, maximum sag point and end anchor point. For tubes, two or more points can be selected. Wires and tubes are available in the library for different conductor types according to international standards.  After conductors has been created and placed, the OSR tool provides a list of compatible library symbols for each symbol type. It is up to the user to choose which symbol should be selected. The user can select the perfect matching symbol or another one in the list. A similar workflow applies to all the other symbols like support structures and foundation heads. The system then combines the symbols to create assemblies (electrical device, support structure, foundation head) and places them in the model. Once an assembly has been created, the OSR tool will recognize identical assemblies in the point cloud and propose it for those positions in the substation. The wires are automatically attached to the respective electrical connection points on the equipment upon the insertion of the assemblies.  After the OSR tool has examined all objects in the point cloud and they have been mapped to an assembly in the model, a logical and intelligent primtech BIM model has been created. The model can be used as a full-fledged template for extension or retrofit - to create parts lists and plans as well as to carry out calculations including phase checking, clearance calculation, lightning protection calculation, sag and short-circuit effects calculations.

The new OSR technology is not fully automatic but drastically improves efficiency and reliability of converting point clouds into intelligent 3D models.This is an important advance that could dramatically improve the process of scanning brownfield substations to intelligent models by making the process more efficient and less error-prone.

M. Kokorus, F. Pizarro, W. Eyrich and S. Heuser, "From Optical Symbol Recognition (OSR) of Point Clouds to the Substation Information Model," 2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D), Denver, CO, USA, pp. 1-4., 16-19 April, 2018

First substation built using full life-cycle BIM construction goes live one month early

Hubei Electric Engineering Corporation (HEEC) was this year's winner of the Bentley Year in Infrastructure Communications and Utilities award.  One of the key objectives of the ground-breaking CNY 120 million (US$16.8 million) Miluo Western 220kV substation project was to reuse the design BIM model and data during construction and to provide a virtual reality BIM model to the owner on completion of the project to improve operations and maintenance procedures. As a result of the application of digital technology including reality modeling using UAVs, full life-cycle building information modeling (BIM), integrated BIM and geospatial, construction monitoring, and construction simulation, construction was completed 30 days ahead of schedule saving CNY 6.3 million (US$ 895,000).

Hubei Electric Engineering Corporation (HEEC) began applying 3D design to projects beginning in 2013. In 2017 the State Grid Corp began to promote 3D design and held a competition to select the best design companies to carry out 3D demonstration projects. HEEC came in first in this competition and was awarded the Miluo Western 220kV substation project. In addition 3D design standards for China's electric power industry had been developed and HEEC was a leading contributor to six of these standards. On this project HEEC strictly implemented these standards during design.

The Miluo Western 220kV substation supplies power to 160,000 customers in a 16 km² area. The total investment in the 10 month project was CNY 120 million ($16.8 million).

Digital technology including reality modeling using UAVs, building information modeling (BIM), integrated BIM+geospatial, construction monitoring, and construction simulation, enabled collaboration between site preparation, mechanical design, electrical design, protection, and communications design teams.  The challenges that HEEC targeted on this project were several.

First of all, the site was constricted because of existing houses and a key objective was to minimize impact on the existing buildings. By scanning the area and using geospatial reality modeling techniques, the area occupied by the substation was reduced by 22% saving CNY 2.5 million and avoiding the demolition of six houses.

Secondly, the project was the first to apply the 3D standards mandated for the entire Chinese utility industry. The Miluo Western 220kV substation is among the first batch of 3D demonstration projects based on 3D standards.  This is the first of the 3D demonstration projects to go into operation, in June 2019.

Third, because the site chosen for the substation was constricted, cables and equipment were closed together than in other substations. HEEC reengineered the design process and developed a series of system processes to ensure the quality of 3D design by collaborative design between mechanical, electrical, protection, communication, and site preparation teams. During design, clash detection between these different elements avoided 30 instances of rework during construction saving CNY 800,000.

Fourthly, from the beginning the objective was to find a way to reuse the design BIM model during construction. Typically a separate BIM model is developed by construction contractors to be used during construction. HEEC investigated ways that 3D pdfs, mobile handhelds, cloud storage, and other technologies could be used to enable the 3D design BIM to be used to schedule construction.

Fifth, HEEC used reality capture techniques including UAVs to monitor construction progress on a daily basis. Due to uncertain factors factors in the construction process, there will necessarily be deviations between planned and actual construction. By monitoring these on a daily basis ensured that these do not hold up the project. At YII2019 HEEC showed an amazing video with actual and planned construction side by side where each frame represented a day.

Finally, an important goal was to use digital technology to improve operations and maintenance procedures. At the end of the project HEEC was able to hand over to the State Grid a virtual reality BIM+geospatial model designed to improve operations and maintenance procedures.

In summary digital technology including reality capture, construction simulation, and full-lifecycle BIM resulted in tangible benefits; avoiding the demolition of 6 houses and reducing the area required for the substation by 22% for a saving of CNY 2.5 million; significant savings in materials saving CNY 210,000; avoided rework saving CNY 800,000; reducing design time by 65 days; and completing construction 30 days ahead of schedule generating economic benefits of CNY 1.5 million. Taken together the total investment was reduced by CNY 6.3 million (US$ 895,000). In addition by providing a virtual reality model to the owner on completion of the project it is expected that substantive savings will be achieved during operations and maintenance.