Between the Poles

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such as outage restoration to require more time than they should and low data quality which leads to incomplete, out of date and inaccurate underground utility records that are responsible for frequent construction delays, injuries and fatalities for workers and the public, and a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.
  

Chattanooga quantifies major benefits from smart grid investment

Chattanooga's power company Electric Power Board (EPB) is one of the most advanced with respect to adopting smart grid technology in North America. At HXGNLive in Las Vegas, Ken Jones reported quantified benefits that EPB has found from its investment in smart grid technology. These include 65% reduction in customer outages and 52% reduction in outage minutes and savings of $23 million in restoring outages after a recent severe storm.

About five years ago I first heard about the remarkable transformation of the power grid in the Chattanooga, Tennessee, a city with a population of about 180,000. With the help of the Department of Energy and other partners the local power company Electric Power Board (EPB) saw the smart grid as not only benefiting the utility and improving the quality of life of its cusomers, but also as a driver of economic development. Early on EPB decided to deploy one of the country’s highest capacity fiber-optic networks to improve power quality, reliability, customer service and energy efficiency. Chattanooga is one of the few municipalities anywhere with 10 Gbit/sec internet speeds for both urban and rural customers. Currently over 50% of EPB customers subscribe to the fiber service.  EPB has estimated that the incremental economic and social benefits of the high capacity backbone for Chattanooga lie between $865.3 million to $1.3 billion. Furthermore, somewhere between 2,832 and 5,228 jobs have been created linked to EPB's infrastructure investment.

In addition to the fiber backbone, EPB has installed 1400 automatic switches, an AMI management system, a distribution management system (DMS), and support for demand management (DM) and distributed energy (DRE).

At HxGNLive in Las Vegas Ken Jones of EPB presented some of the very impressive quantified benefits that EPB has realized as a result of these investments in fiber and smart grid technology.

Reliability

Reduction in customer outages	65%
Reduction in outage minutes	52%

Annual operating savings

Meter reading	$2.0 million
Field services	$0.7 million
Demand charges	$3.0 million

Environmental benefits (CO2 emissions reduction)

Reduced truck mileage	400 tons/year
Demand management kWh reduction	1000 tons/year
Power factor improvement	2000 tons/year

In addition EPB has developed a solar farm of 4,400 panels generating about 2 million kWh/year. Anyone can buy into this starting at just $5/month. Ken gave examples of local firms that completely offset their power usage with solar power.

One of the interesting steps that EPB has introduced to help customers monitor their power usage is a mobile app MyEPB. The app provides real-time energy usage and usage comparison by day, week, and month, real-time outage reporting for the EPB service territory, support for customers to report outages, and billing alerts, for example, notify me when my monthly bill reaches $50. To date there have been 30,000 downloads of MyEPB.

Progress of outage restoration after a recent storm showing areas automatically restored (violet) and manually restored (green)

An area where the investment in smart grid technology has realized a major savings is resilience. Ken presented a map showing the areas in the EPB service territory where power was automatically restored by the automated distribution switches after a recent severe summer storm. The outage and restoration statistics were equally impressive and showed that automation resulted in an estimated savings of $23 million for this storm.

	W/o automation	W/ automation	Difference	Improvement(%)
Customers with an outage	72,622	32,043	40,579	55.88%
Cost of all outages	$69.3 million	$46.1 million	$23.2 million	33.48 %
Outage minutes	16,986,240	12,059,524	4,926,716	29.00 %

One of the important steps that the EPB has taken with its partners is to implement a microgrid testbed at the Chattanooga airport comprising a solar farm, batteries and supporting infrastructure.  This is one of the few airports anywhere that is able function completely off the grid.

These quantified benefits provide tangible evidence of the benefits of smart grid technology deployment.  I would recommend that any power utility operating in a small to medium-sized city seriously consider the Chattanooga experience.

Power utility identifies 60-70% productivity improvement by integrating engineering design, GIS and enterprise systems

In the last few years strong business drivers for improving power distribution design productivity including an aging and shrinking workforce, an accelerating transition to the smart grid and a rapidly changing utility business model have emerged which are motivating utilities to transform their century old business practices.  With new technologies utilities are finding that they can improve productivity by up to  60-70 % by integrating graphical design, engineering calculations such as flicker, voltage drop, guying, enforcement of engineering standards, and integration with enterprise systems to automate bill of materials generation and job estimating.

Distribution design in the power industry

Designing electric power distribution systems involves CAD drafting, engineering calculations such as sag, flicker, voltage drop, guying, wind loading, pulling tension and clearance and checking them against engineering standards to avoid under-engineering, using compatible units to compute jobs estimates, and comparing costs of different equipment to limit over-engineering.  In many utilities distribution design remains a laborious error-prone process with redundant data entry, back of the envelope engineering calculations and manual lookups.

Furthermore once a design is completed it undergoes a typically paper-based workflow (especially for major jobs) that is inefficient and error-prone.  The CAD design is printed for construction contractors to use in the field.  After construction is completed the paper "as-built" comes back from the field to records possibly with red-lines that indicate what was actually constructed.  The key metrics for this workflow are the as-built backlog and the accuracy of asset location in the utility GIS.  These metrics are important for utilities because they directly affect key statistics such as average outage duration (SAIDI) reported by utilities to regulators.  As examples: I remember a small utility in upstate New York where an engineer told me he spent two hours in the snow and darkness looking for a failed device and ultimately had to come back in the morning light to finally locate it.  A large telecom I worked with could not locate some assets to within two city blocks which not only added to the time locating equipment that required maintenance but reduced the reliability of availability of services calculations.  Fashioning AEC and geospatial data into an efficient data flow from planning through design and construction to operations and maintenance represents a challenge that remains a problem for utilities.  The result of this broken workflow is an out-of-date, unreliable GIS that inhibits field workers from optimal productivity and complicates reporting of operational performance.

Business drivers for improving productivity

Utilities are facing business drivers that are motivating them to improve the productivity of their business processes and improving data quality including locational accuracy of assets to provide a near real-time digital twin of their assets.  These drivers include an aging work force, the replacement of older workers by younger less experienced workers, a reliable near real-time GIS as the foundation for developing a smart grid, and a rapidly evolving utility business model that changes utility priorities.

With the new business models emerging in New York and other jurisdictions, utilities' focus is shifting from selling energy to maintaining a reliable and resilient grid which makes reducing the frequency and duration of outages more critical.

Benefits of integrating engineering design, GIS and enterprise systems

In the last decade or so technology advances have provided a solution for low distribution design productivity and out-of-date and unreliable utility GIS.  I have described the system developed by Southern California Edison (SCE) to integrate distribution and transmission graphical design (AutoCAD), utility GIS (Smallworld) and back office systems including ERP (SAP), customer service system, crew scheduling (Clicksoft), field operations (eMobile) and finance (SAP and PowerPlant).  One of the workflows SCE focussed on was compatible units (CUs). CUs represent the cost of equipment together with the cost of labour to install the equipment. When combined with a bill of materials (BOM), CUs allow the designer to generate job estimates. The compatible unit workflow involves many systems including design, crew scheduling, materials ordering, and fixed asset accounting. As an example, at SCE designers were required to manually list the bill of materials on the design drawing and reenter it, again manually, in the materials ordering system.  SCE's integrated system was successful in improving productivity by bringing consistency and efficiency to distribution and transmission design, eliminating manual lookup, enforcing engineering standards to reduce the risk of under-engineering and avoiding the costs of over-engineering, and reducing or eliminating redundant data entry. The integrated system enables experienced workers to work faster with fewer errors and younger workers to become productive sooner.  It sped up the design to GIS workflow and resulted in improved quality of the data in the utility GIS.

However, while the system implemented at SCE demonstrated the success of an integrated approach, it was a bespoke integration of design, enterprise GIS, ERP and other products and is beyond the reach of small and medium size utilities. 

Benefits of a productized integrated solution

At Distributech 2019 I linked up with Dennis Beck of Spatial Business Systems (SBS), which took over responsibility for future development, support and licensing of AutoCAD Utility Design (AUD) software in 2016. He explained that SBS has transformed the architecture of the SCE integrated solution into off-the-shelf products that enable it to be cost-effectively implemented at any size utility.  One of SBS's customers has determined in detail the productivity benefits of an integrated architecture with SBS components for their engineering design workflow.

Nashville Electric Service (NES) is a publicly owned, nonprofit company that serves more than 355,000 customers in a large service area in Tennessee.  As part of a major upgrade to their business processes NES benchmarked an integrated automated design, utility GIS and enterprise systems solution for two engineering design jobs using SBS components.  NES performed the two jobs four different ways and assiduously recorded the time required for each step of the design process.  This allowed them to estimate the quantitative benefits of different aspects of the integrated solution.  The major components of the NES solution architecture were

• Automated design -  AUD is an AutoCAD-based desktop application that provides a model-based approach to design and bill of material generation along with a comprehensive set of engineering tools, including flicker, voltage drop, guying, and pulling tension and clearance checking.  It supports both overhead and underground distribution design.

• GIS integration - Integrating graphical engineering design with the utility GIS helps reduce as-built backlogs which are a major contributor to out-of-date utility GIS.

• Enterprise integration - Integrating engineering design and utility GIS with the utility's work order system, material management and financial systems makes it possible to automatically enforce engineering standards, generate construction work orders, layouts, bills of materials, design scenarios and estimated costs.

NES calculated the benefits of each level of improvement as applied to overhead and underground residential distribution design.

	Overhead Time (mins)	Overhead Time saved (%)	Underground Time (mins)	Underground Time saved (%)
AutoCAD	173		81
Automated design (AUD)	145	16 %	63	22 %
AUD with GIS integration	132	8 %	50	14 %
AUD with GIS and enterprise integration	69	36 %	23	34 %
Total savings	104	60 %	58	70 %

The analysis revealed important benefits from model- and rule-based approaches to engineering design. It enabled behind-the-scene calculation of physical things like wire sag, flicker and voltage drop. An important contributor to productivity improvement was to completely avoid the need to lookup or manually find engineering and drafting standards. The largest benefits from a productivity perspective were found by integration with enterprise systems especially compatible units which enabled automated bill of materials generation and job estimation.

NES further broke the overall workflow into subtasks including drafting, annotation, job estimating and enforcing engineering standards and analyzed the productivity improvements for each of these subtasks.

Overhead residential design	AutoCAD	Automated design (AUD)	AUD with GIS integration	AUD with GIS and enterprise integration
Drafting	60 mins	95 mins	82 mins	61 mins
Annotation	36	36	36	8
Job estimating	24	14	14	0
Engineering standards	53	0	0	0

 

Underground residential design	AutoCAD	Automated design (AUD)	AUD with GIS integration	AUD with GIS and enterprise integration
Drafting	25 mins	31 mins	18 mins	18 mins
Annotation	22	22	22	5
Job estimating	24	10	10	0
Engineering standards	10	0	0	0

The analysis revealed that while an integrated approach to design did not significantly change the time required for actual graphical drafting, it dramatically reduced the time required for annotation, applying engineering standards, and job estimating (including BOM generation).  These improvements in productivity were derived primarily from eliminating redundant data entry and manual lookup.  Another significant point is that these timings only represent the time savings to engineering design – they do not include savings on re-entry of data into the GIS from as-builts.

Other benefits that NES did not quantify include avoiding the risks associated with under-engineering, reducing the costs of over-engineering, increased quality of the utility GIS by recording engineering designs directly in the GIS rather than re-entering it from paper as-builts, and enabling less experienced workers to come up to speed faster without increasing the risk of errors or significantly reduced productivity.

Improving productivity of distribution design by up to 60-70% is a huge benefit.  SBS is finding that other customers are reporting similar experiences, although they haven't documented their productivity gains as meticulously as NES has done. For utilities that are facing a significant portion of their workforce retiring, this improvement in productivity can free up experienced engineers and others to accelerate the transition to the smart grid and to adapt to a rapidly changing utility business model.

Bringing reliable near real-time GIS within reach of every utility

Workflows for ensuring utility GIS quality are fundamentally broken and have been for decades.  Integrating CAD and GIS into an efficient workflow has been a challenge and it has simply not been a priority in the utility industry and in some parts of the communications sector to ensure real-time, high quality asset GIS data. Recently business drivers for high quality GIS data such as implementing a smart grid, estimating service availability and other applications have made GIS quality a top priority.  And now non-traditional geospatial companies are offering geospatial-based technologies that are revolutionizing the capture and maintenance of GIS information about utility and communications assets that can provide a foundation for the real-time network digital twin that is essential in the era of the smart grid and our increasing dependence on communications and utility networks. 

Broken business processes degrades GIS data quality

Maintaining accurate, up-to-date asset data has been a challenge for utility and communications firms for decades.  Over the years the lack of CAD/GIS interoperability has cost communications and utility companies hundreds of millions of dollars trying to cleanup their GIS data and streamline their CAD+GIS workflows.  One of the persistent themes from the very beginning of the Between The Poles was the challenge of integrating CAD and GIS data in a common workflow (some examples; 2006, 2007, 2008 ).  Critical metrics for utility readiness for the smart grid is the as-built backlog, field update backlog and the location accuracy of the assets in the utility's GIS.  It is not uncommon for as-built backlogs to stretch into months even years, for updates from the field to take months to be entered into the records database if they are entered at all, and for the location of assets as recorded in the GIS to be city blocks from its actual location.   The challenge is to fashion workflows that include both engineering and geospatial data and applications into an efficient data flow from planning through design and construction to operations and maintenance with feedback loops that ensures an accurate, near real-time GIS.  For many utilities and communications firms traditional GIS, which has been the standard platform for utility GIS for the past few decades, has simply not delivered cost-effective, real-time, high quality asset location and associated data.

A key workflow found at all utilities and communications firms is the field maintenance process.  In many utilities this is a broken feedback loop which results in the quality of GIS data degrading over time.  When a field crew performs maintenance on network infrastructure, which includes routine and emergency maintenance, or encounters equipment incorrectly located or described in the GIS, the changes or the corrections to the GIS data from the field need to get back into the GIS quickly.  Too frequently this is still a paper-based process typically involving redlining as-builts, which get to sent to records for updating in the GIS.  The backlog associated with field updates can stretch into months.  The slow turnaround of field updates discourage field staff from reporting corrections and changes further exacerbating the GIS quality problem.  The result of this and other broken workflows such as the as-buillt workflow is that not only is GIS data incomplete, inaccurate and out-of-date, but that its quality degrades with time.

Business drivers for accurate, real-time GIS

For communications companies a major driver for an accurate and up-to-date GIS is providing rapid availability of service estimates to prospective customers.  I remember a large U.S. telecom that because it could not rely on the information in its GIS had to resurvey all the locations of its fiber terminations in order to respond to potential ADSL customers indicating whether they were close enough to a fiber termination for the service.

For electric power utilities a powerful business driver that has emerged in the last few years is the smart grid.  Digitalizing the grid has made the role of geospatial data and technology strategic for utilities. As a Navigant Research report stated the smart grid is all about situation awareness and effective anticipation of and response to events that might disrupt the performance of the power grid. Since spatial data underlies everything an electric utility does, GIS is the only foundational view that can potentially link every operational activity of an electric utility including design and construction, asset management, workforce management, and outage management as well as supervisory control and data acquisition (SCADA), distribution management systems (DMSs), renewables, and strategy planning. As John Simmins of EPRI has reiterated on a number of occasions a prerequisite to implementing a smart grid is cleaning up GIS data and developing business processes (feedback processes) to ensure that it remains accurate and up-to-date.

Technology enablers: Open standards, open source geospatial and handhelds

Recent technical advances have made it possible to implement cost-efficient processes for ensuring that utility asset data including GIS data is accurate and up-to-date.  There are now many widely adopted geospatial standards; Simple Features for SQL, WMS, WFS, GML, KML, and InfraGML to name just a few from the OGC that were not available two decades ago.  Secondly, since the founding of the Open Source Geospatial Foundation (OSGEO) in 2006 there has been rapid development of open source geospatial projects including PostGIS, GeoServer, MapServer, Leaflet and others.  This open source code-base has enabled entrepreneurs to rapidly develop low cost geospatial applications because the cost of maintaining most of the code is shared across a broad developer community.  Thirdly the advent of the handheld touch screen computer and phone provides a low cost universally accessible hardware platform for field staff to access geospatial and other information stored in a utility's databases.  With the appropriate software smart phones and tablets make it possible for field staff to see all of the information about an asset in the field at the touch of a finger.  For example, I blogged about how Duke Energy field staff are using an open source based mobile application which provides a single, common easy-to-use web tool for viewing geospatial asset data stored in GE Smallworld, ESRI ArcGIS, Intergraph GTechnology, spatialNET and Google Maps as well as non-GIS data in Maximo, SAP, three different outage management systems, four or five customer information systems, CAD drawings and photos and images.

Shifting the paradigm: GIS data maintenance from the field

The paradigm shift is empowering field staff to take responsibility for the quality of data in the utility GIS. Since they have direct knowledge about the location and condition of utility infrastructure, the key to revolutionizing data maintenance and enabling near real-time, accurate GIS and other data is "cutting out the middle man" and enabling field staff to maintain the utility GIS and other data in the field as they are working. Enabling field folks to do this without adding significantly to their workload (and over time reducing their workload as the quality of the GIS improves) requires a simple "touch and go" user interface which minimizes typing, responsive applications running on handhelds, and workflows that enable field staff to see their changes with a minimum delay measured in hours or days at the maxium.  Of course, operational data can be protected from problematic updates using data versioning technology (long transactions) which provides a rapid way for records folks to review and identify potentially problematic updates.

At Distributech 2019 a new entrant IQGeo emerged into the utility and communications space and announced an alternative to traditional GIS.  myWorld Capture is a mobile solution that prioritizes direct data maintenance from the field.  Building on an open source geospatial platform that supports data versioning and interfaces to legacy utility/communications GISs such as ArcGIS and Smallworld, myWorld provides tools that make it possible to develop and maintain a high quality near real-time GIS with the information that is required for a complete network asset data model including equipment location, descriptions, connectivity, condition, and status. 

The key to ensuring that the data is high quality and up-to-date is empowering field workers to make updates at the source as the work happens and to automate the data maintenance workflow as much as possible.  This approach can eliminate backlogs in field updates, encourage field staff to take responsibility for ensuring the quality of the utility GIS and enable an effective feedback loop that improves GIS data quality over time.   With the promise of near real-time updates directly from the field this approach provides a key foundation for the digital twin of the grid that integrates sensors reporting in real-time with simulation and analytics that makes it possible to create a accurate real-time situation assessment and to model the electrical state of the grid and possible future states based on reported or forecast outages and planned expansions and other changes to the electric network.

Operationalizing the new paradigm

How does this work in real world practice? I had a chance to chat with Dick Rohm, Director of Engineering at Cable One about how they are progressing toward their goal of no backlogs for field updates or for as-builts.  The business driver for this initiative, which they have been working on for the past several years, is service availability - being able to tell a customer immediately whether a fiber service is available at the customer's location or whether it will require an addition to the network.

Cable One provides commercial fiber services to businesses as well as cable services in 21 states, primarily in small cities and big towns.  Sales success requires being able to respond rapidly to potential customers requests for business fiber service, and say yes we already have the fiber capacity in your neighbourhood or no we have to build out a fiber line to support you.  Improving the quality of the data in their GIS is an important business driver for Cable One.  

By prioritizing as-built and update workflows Cable One has managed to ensure that as-builts and updates are in the GIS quickly, typically within 2-3 business days.  To achieve this, they first changed the as-built process, making the design process paperless about five years ago. Their engineering GIS allows engineers to use AutoCAD to design fiber and RF networks directly into GIS .  For construction, contractors are provided with AutoCAD drawings (DWG) on thumb drives and it is up to them if they wish to print them.  For small jobs, contractors can work completely electronically. For large jobs, contractors still use paper, but they print the DWG files themselves. Contractors must register with Cable One's Project Central which is used to track all projects. When paper as-builts are returned, they are spot-checked, and the GIS is updated based on any redlines. A project will not be closed out (and contractors paid) until redlines are in the GIS.  The GIS is used by Marketing and Sales as an added application to myWorld.

For updates from the field the initial idea was to use a web extension to their GIS, but they found that it was too cumbersome and slow.  It was replaced by myWorld on a handheld working with Google or Bing Maps which provided front end for viewing all engineering geospatial and associated data in the field. The myWorld solution only requires about an hour training time using a video. 

Based on the success of the myWorld implementation, user acceptance testing of myWorld Capture is currently underway. myWorld Capture enables field staff to update GIS and other data as they work.  Ease-of-use and rapid response are its key features. It makes it possible for field validators to do most of their work by tapping and drag and drop with very little typing.  Field engineering staff have to do more typing but even for them it is minimal.

The objective of the myWorld Capture implementation is 24-hour turnaround for updates from the field. It could even be less, but it is currently limited by the process of posting updates to the GIS and to the MyWorld database, which occur every night.  myWorld Capture will roll out to all field staff by July 1 of this year.
Dick Rohm emphasized that the key to making a transformative project, such as this at Cable One, successful is changing thought processes in the field. Data needs to be treated as just as important as physical assets.  When something changes or an error is found, the priority for field staff is to update it.  To encourage field staff to make changes in the GIS, tools need to be provided on handhelds that are fast and easy to use. Update processes must be fast so that their changes can be seen by field staff quickly in the GIS. Over time, field folks will increasingly rely on the GIS because they will see corrections that they make from the field appear in the database within 24 hours or sooner.  As data quality improves as a result of this feedback loop, field staff will find that they can rely on the GIS for locating and accessing up-to-date information about assets.

Conclusion

Prioritizing updates from the field to reduce the field update backlog to 24 hours or better together with an as-built backlog on the order of two to three days is a remarkable achievement.  It shows that with a business perspective that prioritizes a near real-time, reliable digital twin of utility and communications networks and geospatial technology supporting open standards and based on opensource and implemented for handhelds in the field, a cost-effective solution to the decades old GIS data quality challenge is within the grasp of any utility or communications firm.

Machine learning cost-efficiently creates high quality utility GIS data for smart grid applications

Many utilities' GIS contains only a small part of what is required for managing a smart grid.  Often even the data in the GIS is too unreliable to use for smart grid applications.  For example, utility GISs may not include which customers are connected to which transformer, or if they do include this information it is incomplete or incorrect.  Many utility GISs cannot identify the phase(s) each customer is using and they may not include network topology - what is connected to what.  Other missing data may includes street lights, distributed energy generation such as rooftop PV panels, the type and condition of poles, joint use of poles, and encroachment.  To correct these problems typically requires a foot survey which is expensive.  For example, a pole inventory costs at least $20 per pole.  At the Open Geospatial Consortium (OGC) Energy Summit at EPRI in Charlotte, John Simmins of EPRI described the research he is leading at EPRI to use modern technology including machine learning to reduce this cost to pennies per pole using available imagery such as Google Streetview.

I began working in the utility and telecom sector in 1993, specifically in developing software for records management (called network documentation outside of North America), and at that time the magnitude of the AEC+geospatial cultural mismatch was just beginning to be appreciated by utilities and telecoms. Planners tend to use GIS tools, engineers and designers CAD tools, construction folks in the field paper CAD drawings, and asset managers FM, GIS or integrated tools. Fashioning AEC and geospatial data into an efficient data flow from planning through design and construction to operations and maintenance represented a challenge that remains a problem for utilities.  For many utilities the backlog of as-builts and updates waiting to be entered into the GIS stretches into months, with the result that GIS data is permanently out of date inhibiting management and field staff from relying on this data operationally.  The Between The Poles blog is over ten years old and one of the persistent themes from its very beginning in 2006 was the challenge of integrating CAD and GIS data in a common workflow (some examples; 2006, 2007, 2008 ).

There are signs that modern technology is beginning to offer a solution to the problem of developing and maintaining an accurate digital model of electric power grids.

I wrote recently about a utility in western Pennsylvania that intends to implement an Advanced Distribution Systems ( ), but realized that to this requires a network data model. Duquesne Light is typical of many North American small to medium electric power utilities.  It does not have an outage management system or an electrical data model which means it is difficult to connect customers to transformers and to determine upstream devices when customers report power problems.  Currently Duquesne Light's circuit maps are AutoCAD drawings.  Duquesne Light is moving to modernize its grid and plans to deploy an Advanced Distribution Management Systems (ADMS) including outage management (OMS), DMS and DSCADA.  But the ADMS will require developing a complete distribution electrical data model and to that in the traditional way can be expensive.

To quickly, safely and cost efficiently develop a network data model, Duquesne Light looked at several alternatives including reality capture technology.  A pickup truck was equipped with with side mounted photo and IR cameras and LiDAR laser scanners. The reality capture survey could be completed rapidly and safely, with no boots on the pavement  Actual development of the data model was completed in the office without the necessity of going to the field for quality checks because the imagery provided all the data that was required to create and verify the data model.  Duquesne Light found several significant advantages of the reality capture approach.  The first was asset accuracy - both location and asset attributes.  In addition the captured imagery could also be used for other purposes.  For example, it could be used for a joint-use audit.

But this is still basically a manual process requiring a human being to scan images.  At the Energy Summit John Simmins described his research using neural network technology to automatically identify poles and attached equipment from available imagery such as Google Streetview.  Normally applying neural networks requires large quantities of training data.  To reduce this requirement, John has evaluated "biologically inspired", forward pass, neural networks.  In this approach the algorithm first looks (foveates) for vertical things that have the characteristics of a pole, and then for the characteristics of equipment attached to the pole, for example, cross members, street lights, transformers and large cables.  From this analysis is possible to determine pole location, height and width, cross member position on the pole and projected length, street light support strut position and length, position of transformer and large cable connection locations.  The ultimate goal of the research is in addition to automatically detecting each element of equipment to identify the type, size and manufacturer of each piece.

This is not a simple problem and there is no silver bullet.  Using a standard neural network approach requires large volumes of training data.  For poles it requires images of poles with different types of damage under different lighting conditions and in different types of weather.  An Australian company SiteSee claims to be able to do this for communications towers and transmission pylons - identifying the type and manufacturer of each antenna or insulator on a tower or pylon and comparing it to the manufacturer's specification to detect signs of corrosion and other types of damage.  When what you are looking for has a distinctive geometry that differentiates it from the surroundings, a biologically inspired approach may provide a way of identifying equipment without large volumes of training data.  Another area where several different approaches have been applied to automate feature extraction is electric power transmission lines for vegetation management.

Creating a digital twin of an electric grid is essential for developing and maintaining a smart grid.  Utilities have been wrestling with this challenge for decades and in many cases their GIS data is still not much closer to what is required.  If it would be possible to use the technology that John Simmins is investigating or other technology to reduce the cost of improving the quality of their GIS data, it would accelerate the adoption of smart grid technology at many utilities.  In his presentation at the Energy Summit Jared Green described his research in using smart meter and AMI network data to map secondaries from the transformer to the home, identify sources of unmetered load, and use impedance data from smart devices to correct utility GIS data.  Given the history of the challenge to develop and maintain accurate GIS data at many utilities, these approaches represent a beacon of hope which may enable utilities to cost effectively develop a digital twin of their networks that is an essential prerequisite for a  smart grid.

Regulators encourage utilities to invest in cloud-based software

Utilities have in general not been IT innovators.  But the accelerating adoption of smart-grid technologies by utilities is resulting is driving the need for greater IT awareness and skills in the electric power industry.   Large utilities have the requisite IT skills in house.  Small utilities typically don't and outsource their IT development or adopt SaaS solutions.   Medium-sized utilities fall in between.  Now regulators appear to be ready to provide financial encouragement to push utilities to improve their IT capacity.  Cloud-based computing is perceived by regulators as providing a way to future-proof IT investment in the rapidly changing smart grid world. 

At Distributech 2017 Oracle released the results of a survey of utility industry regulators.  Oracle Utilities and Zpryme surveyed 76 utility regulatory staff and commissioners in the U.S.  What they found was that more than three quarters of the respondents believe that regulators should play some role in determining whether utilities use the cloud. 69% of U.S. regulators support capitalizing cloud-based software, which is a way to use accounting to encourage utilities to invest in cloud-based software.  A third of the regulators have a specific and comprehensive strategy for utility cloud investment.  The most significant benefit of cloud computing the respondents identified was improved flexibility.

Utility industry vendors urged to adopt data model standard

Software comes and goes, but a utility's data model persists. A shared electric power data model enables electric power utilities to move away from incompatible point solutions toward tightly integrated solutions which are essential for real-time monitoring, situational assessment and decision making.  Based on today's smart devices and sensors and utility-wide communications network, decision making in a real-time, big data world requires tight integration between applications.  To realize the full potential of the smart grid, utility industry vendors need to move rapidly to adopt data model standards, that's the recommendation of Geoff Cameron of AGSI. which has developed a platform based on a utility data model standard that provides real-time access to critical infrastructure, customer and operational information. 

 

Traditional electric utilities are typically departmentalized and rely on manual, paper-based processes. Sharing knowledge is relatively slow, cumbersome, and reactive in nature and characterized by redundant data, many incompatible point solutions and non-real-time.  Facilities are inspected periodically, data is accumulated and analyzed, a report is written and sometime in the future do something is done.  Today's intelligent electronic devices, bidirectional communications networks, and automation provide the basis for dramatically improving a utility's SAIDI and SAIFI outage statistics.  It also provides a foundation for transactive energy.  What is required to realize the full potential of the smart grid is a platform that enables real-time integrated applications.

 

At Distributech 2017 Dan Guatto, COO and VP of Engineering and Operations, described how Burlington Hydro (BHI), a distribution utility with 65,500 customers, has evolved from a point solution environment to an integrated, secure, and real-time utility.  As is typical of many distribution utilities, BHI was facing increased technology sophistication, the need integrated business workflows (operations, engineering, customer engagement, financial) to improve efficiency.  BHI had to address siloed legacy systems and business processes.  Many industry solution offerings fixed individual problems but were expensive and did not take into account integration and long term data management.  Many “enterprise” offerings in the marketplace were proprietary black box solutions with little flexibility that made BHI feel that it was surrendering control of its data and processes.  One of the major problems BHI identified was the lack of O.T. / I.T. convergence for true enterprise efficiency.   Solutions required quite expensive capital outlay and deployment.  Projects became too big and and bogged down and were unable to address fast paced industry change.  In Ontario some of the larger utilities made significant technology investments, but at the end of the day these projects were extremely expensive, disjointed and largely underutilized (or even abandoned). BHI was also concerned about the infancy of smart grid technology and rapid future changes and didn't want to be tied to an inflexible system as the speed of industry changes accelerated.  BHI was convinced that a sound system architecture had to be based on electric industry standards and was aware that AGSI had been working with EPRI on a real-time platform based on Common Information Model (CIM) and Open Geospatial Consortium (OGC) standards.

 

Over the past decade open electric power data model standards have been developed for transmission, distribution, smart substations and other electric power functions.  Worldwide the Common Information Model (CIM) has become the standard for transmission.  CIM is also widely used outside of North America for distribution.  In North America the Multispeak standard is the most widely used distribution data model standard, although CIM is used by larger utilities.  These data models are mature and cover virtually all aspects of electric power utility operations.

CIM was originally developed for standardizing electric utility information exchange.  It was designed by electrical engineers, adopted by the IEC and supported by EPRI and multiple electric utility partners, vendors and organizations.  The IEC, EPRI and partners continue to extend the model to cover asset health, station design, work, smart grid integration, IoT Integration, and network operating protocols.  CIM is able to support all aspects of electrical operations (OMS/DMS), electric analysis / smart grid, distributed energy (DER), work orders, crew management, and assets.  AGSI has implemented the CIM Core, Topology, Wires, & Assets object models in a relational database (Oracle Spatial).  Its implementation represents a real-time network model of the CIM electric system data model and provides a centralized view and interaction with the network in real-time.

 

Today this technology connects and integrates engineering, SCADA, AMI, GIS, load analysis, other smart grid deployments such as EV charging, customer, and asset databases into a single accessible platform and enabled BHI to evolve from a point solution environment to an integrated, secure, and real-time utility.  Real-time data unification provides a basis for transparent workflows and a centralized reliable source of truth enables advanced analytics for optimized investment planning.  An open architecture based on industry standards provides the flexibility to adapt to rapid changes in technology as the smart grid evolves. Real-time information sharing enables faster decision making and increased customer satisfaction via real-time situational awareness about outages and planned work.  Don Guatto believes that it provides the foundation for transactive energy which is looming on every utility's horizon.

U.S. governors urge Trump to support renewable energy and grid modernization

The Governors' Wind and Solar Energy Coalition (GWSC), representing 20 U.S. state governors, both Democratic and Republican, sent a letter to President Trump presenting the benefits of renewable energy, arguing for a Federal commitment to support renewable energy and grid modernization, analytics and simulation and to streamline regulation of the grid.

The letter outlines how renewable energy is providing jobs and investment to low-income U.S. counties. For example, U.S. wind facilities pay rural landowners $222 million a year, with most of it going to landowners in areas with below-average incomes. $100 billion has been invested by companies in low-income counties, where some 70 percent of the nation’s wind farms are located.  Wind energy currently generates five percent of U.S. power demand. Last year, the country’s solar industry employed over 200,000 and added 31,000 new  jobs. Most of the installations are in rural areas and have provided landowners another income option.

Furthemore, the letter argues that any national infrastructure legislation introduced in Congress should provide significant funding for grid modernization. The complexity of the U.S. aging, multi-state grid makes the need for sophisticated modeling and analysis critically important. The GWSC asks the President to create a new state-federal task force, in conjunction with the Federal Energy Regulatory Commission (FERC) and the National Laboratories, to examine options to  modernize and streamline state and federal regulatory processes.

The GWSC suggests that if the United States does not continue robust federal research and development programs in wind  and solar energy, China will assume leadership and see most of the economic benefits in these critical technologies. The Governors make the case that the growth of the renewable energy industry is an American success story built on federal research and development, state policy leadership, private sector investment, and ingenuity.

Canada prices carbon

The Canadian government has announced a a pan-Canadian policy on climate change including a floor price on carbon beginning in 2018.  The Paris agreement commits Canada to a 30 per cent reduction in greenhouse gases from 2005 levels by 2030.  The floor price of carbon starts at a minimum of $10 per tonne of GHG emissions in 2018, rising by $10 each year to $50 per tonne by 2022. All of the money raised will be returned to the respective provinces, who can, in turn, distribute those funds to their citizens in the form of tax cuts.  The federal program will be compatible with existing provincial carbon pricing programs.  Ontario and Quebec already have a cap-and-trade program.  British Columbia already has a carbon tax of $30 per tonne.  Alberta has announced it will have a $20 per tonne carbon tax beginning in 2017, rising to $30 a tonne in 2018.  Eight of ten provinces have signed onto the agreement.  The federal government said it will impose a carbon price on the two non-signatory jurisdictions, Saskatchewan and Manitoba. The final agreement includes a list of already announced measures including new building codes to improve building energy efficiency, more charging stations for electric cars, expanding clean electricity sources and upgrading power grids.