Between the Poles

Developing a subsurface digital twin for Singapore requires data quality management

Singapore has severely limited land, but unlimited space and has started to build many types of activities underground to save the land above ground for the better living of citizens. Many of the traditional utilities such as electric power, water, wastewater and others, as well new type of utilities, such as the Pneumatic Waste Conveyance System are almost one hundred percent underground. Parts of the transportation network, such as the metro, are also underground.  In addition some storage, waste disposal and national defence facilities are underground.

Data quality

As underground development expands in Singapore reliable data about the location of underground infrastructure becomes increasingly essential. Data quality is a huge issue. Virtually all stakeholders are aware that much of the available information is unreliable and that this has repeatedly led to losses of time, money and opportunities.  From the perspective of planning and land administration, infrastructure development, and planning and design there are important benefits in the form of reduced uncertainty and risks to be derived from reliable underground data.  These include reduced costs, avoiding unnecessary rework, minimizing destruction to the environment, avoiding disruption of consumer services, and greater safety for people working in the environment as well as the general public in general.

To address this issue the Digital Underground (DU) initiative was started in 2017. The objective of DU is to develop a reliable map of Singapore's subsurface infrastructure for planning and land administration. The DU has four phases. The objective of Phase 1 was to identify the problem and create a road map. The second phase involved looking into what was required to create a utility mapping ecosystem. The current phase involves looking at the underground utility workflow which has many components that will contribute towards reliable data.  The final phase is the operational phase when we implement a new utility mapping ecosystem.

In Phase 1 an assessment was made of the reliability (locational accuracy, completeness, and currency) of the existing data. It was concluded that the data quality of the data is seriously deficient. In terms of location, it is  inaccurate, much of it is out of date, and it is also incomplete. It was also found that the quality level of the data is undefined, in other words, no quality level has been assigned to each facility for example based on a quality standard like ASCE 38 or PAS 128. We do not know which piece of data is of higher quality or which piece of data is sufficiently reliable to be relied on for planning and land administration.

Road map for improving data quality

Addressing data quality involves fundamental survey, locating and mapping issues. In addition to assessing data quality an objective of Phase 1 was to develop a road map for addressing the data quality issue. First we wanted to ensure that going forward data for all newly installed utilities would be reliable. In 2017 we implemented a strategy requiring certified survey quality as-builts. Secondly, we started to look for opportunities to improve the data quality of existing below ground infrastructure. We are looking at several new technologies, such as ground penetrating radar and gyro mapping for detecting underground utilities and LiDAR and photogrammetric capture with a smart phone of trial trenches. We are also exploring ways of capturing not just vector data, but integrating 3D point cloud data of an open trial trench in our GIS so the next person interested in this section of road doesn't have to open up the trench to see what's there.

A key part of the road map is governance, especially accountability and transparency; assigning responsibilities for data capture, data quality improvement, and data quality management. We want to introduce a new framework so that we can ensure high quality utility data ongoing in the future. We are suggesting a process that would not interrupt or change the current utility workflow, but add a new data quality workflow on top of the current workflow. Asset owners will be able to continue to do their work the way they have in the past, but will be required to submit their data to a Data Quality Hub for quality control to ensure that data quality standards are complied with. We intend to implement quality control on the front end when data is submitted to the database, not at the tail end of the information supply chain. Eventually this process is intended to ensure that we are getting reliable and high quality data that can be shared back again to the end user, the planners and land administrators.

Community of practice

Creating a utility mapping ecosystem requires buy in from network owners, transportation agencies, excavators, and others. The Digital Underground Connect is a platform where we provide people to meet, to learn and to improve.

 

This post is based on Victor Khoo's talk on the Singapore Digital Underground Project at the Subsurface Utility Mapping Strategy Forum (SUMSF).

Grid resilience demands we understand our infrastructure above and below ground

Jay Cadman, SVP Enterprise, IQGeo

As the glue interlinking everything from the industrial ‘Internet of Things’ to smart grids and underpinning the real-time social and economic services of the future, full fiber and 5G is increasingly recognized as an essential national utility. With superfast broadband forming the enabling technology for social and economic progress, any outages could have an equally devastating effect to power or water shortages. Europe is already pioneering ways of improving infrastructure’s resilience to climate change. This is becoming increasingly critical as superfast broadband faces a more distributed, fluctuating and unpredictable threat landscape than ever before.

Full-fiber cables are vulnerable to underground water while 5G will move radio signals to even higher frequencies where they are more susceptible to weather interference. For example, Hurricane Sandy damaged Verizon’s Northeast network and some basement-level communications hubs, while in 2018 Hurricane Michael caused major flood damage to underground fiber-optic cables in Florida. Achieving resilience across the telecoms sector will mean understanding the complex intersection of infrastructure above and below ground. Future fixed and mobile connectivity networks will all be 5G so that everything from underground fiber cables to radio waves will need to be managed as a single interconnected ecosystem above and below ground. Knowing the location of all infrastructure will be critical to understanding where all our fiber optic cables and 5G antennae intersect with the people and places that will need them. It is also vital to understand the common vulnerabilities that could produce a single point of failure affecting multiple overground and underground networks. Infrastructure planners will need to know the location of 5G networks in relation to nearby threats and hazards. Hazard data may even need to be shared with rival telecoms operators and authorities to ensure common resilience across the sector.

The Data Gap

This presents a major challenge because many telcos do not have current, comprehensive data on overground and underground assets in an integrated, easily accessible and shareable format. Many current systems fail to fully capture live insights from both workforce and network assets. Network data is rarely held in a modern, mobile-friendly format which is accessible to field workers or contractors. Many networks do not link all network data with location, which is critical to understanding risks in all regions of their network. Smaller operators are frequently not documenting their network in a digital SoR (System of Record). All too often, network data is not only siloed within an organization, but also incompatible with external datasets such as meteorological or ecological satellite data. This also means it cannot easily be shared with other organizations or authorities to help combat common vulnerabilities and ensure sector-wide resilience.

For example, there are 3.4 million miles of underground infrastructure including data lines and fiber-optic cables in the UK alone, yet there is no up-to-date or integrated map of this subterranean labyrinth. This makes it impossible to achieve common resilience against underground threats such as flooding or to see how other present or planned underground utility infrastructure might pose hazards to telecoms networks.

To help prioritize critical services and customers for maintenance or upgrades, operators need comprehensive and current location-based information on underground fiber-optic networks in relation to all the critical settlements and services that depend on them. Similarly, without a single map of infrastructure above ground, operators cannot predict how local weather might affect antennae.

In a pioneering example of what could be achieved, London is working with companies to create a combined mobile-friendly map of its subterranean infrastructure where the site and source of hazards in relation to overground services can be swiftly identified.

Achieving resilience

Telecoms’ unpredictable, varied, and fluctuating threat landscape means operators must now go beyond reactive risk management and recovery and adopt forward thinking and predictive network resilience. Creating resilient 5G networks will require a holistic overview of the site and the source of potential threats across overground and underground infrastructures. Crucially, all fixed and mobile networks will need to be managed as an interconnected ecosystem regardless of the location of physical infrastructure. Key to this challenge is the ability to combine data from multiple sources and harness all of a network’s assets as a source of real-time threat intelligence. This means adopting geospatial information systems capable of capturing a wide array of network data from employee smartphones to IoT sensors and matching it with precise and accurate location data to reveal the locus and the solution for every problem anywhere in the network. Accurate SoRs and ‘as-builts’ are critical to ensuring a comprehensive and current risk overview across all infrastructure and effectively targeting mitigation strategies, from repositioning antennae away from threats to replacing copper wire with fiber-optic cable. Matching all telecoms data with location data is essential to contextualizing threats, revealing interdependencies with neighboring infrastructure that could create shared vulnerabilities, and identifying priority customers or communities to protect. Using open platforms capable of integrating network information with external sources is also vital to allowing important information to be shared with authorities or other operators. This also allows network data to be merged with relevant external sources of risk intelligence such as weather or vegetation data.

Below I have outlined some steps companies can take to create data-driven resilient grids.

Step 1: Democratize network data

Operators must devolve responsibility for updating network information across the workforce, from field technicians to office managers. This involves harnessing open, mobile-friendly geospatial information platforms that can capture information from a decentralized array of sources, from IoT sensors to field worker smartphones. As-builts and systems of record should be digitized and easily accessible to workers on the ground who can ensure they stay accurate and up to date. This empowers workers, creating a sense of collective responsibility for network intelligence and resilience. Opening up network data should also extend to the use of open APIs to integrate location-based network data with important information from external sources such as weather hazard data.

Step 2: Risk assessment and resilience

Assess the network to identify and remove systemic vulnerabilities and single points of failure. Since all fixed and mobile networks will ultimately be 5G, organizations must ensure they have integrated, comprehensive and current geospatial information on all infrastructure above and below ground so they can easily identify threats. Companies should be creating network-wide digital ‘dashboards’ tracking live, location-based intelligence revealing the site and source of hazards such as storms or cyber-attacks. Operators must ensure they can capture live information from any device in the field, and that their network location data is accurate and up-to-date, so they can take rapid remedial action or mitigate risks specific to each region. Virtualization of networks also means the equipment itself can indicate risk or damage and this can be matched with location data to create a digital twin of networks that encourages more agile, adaptable risk management.

Step 3: System resilience & security

Whether organizations adopt third-party cloud environments or bring this in-house, they must support geographic resilience, system redundancy, and the latest advances in cyber security. Critical network software must ensure data is duplicated and encrypted to drastically lower the likelihood of singular points of failure.

Step 4: Incident response

Have a company-wide damage assessment and incident response strategy, both to preempt current threats and to provide insights which can be used to predict and prevent future risks. Organizations should start by creating a live, location-based overview of damage, degradation, or hazards to the network across both overground to underground infrastructure. Incorporating this data into incident reports not only helps create more rapid and even predictive maintenance of networks, but also encourages a proactive and predictive risk management model that can draw on past incidents to inform future solutions. For example, data on regions at risk of flooding can be used to protect nearby fiber-optic cables but also to inform planning of future networks that mitigates identified risks. In this way, networks grow collectively stronger and smarter from every incident.

Step 5: Practice

Stress-test systems, people, and processes with regular rehearsals to ensure resilience is drilled into all company procedures, workers, and systems. Just as companies perform health and safety training, they should test and train all assets for network resilience. This will ensure that best practice is baked into the organization.

The threats facing the telecoms industry today are constantly changing, extreme weather and other recent trends pose the threat of a ‘black swan event’ that affects entire systems of networks. However, by digitizing and decentralizing network data and creating proactive resilience strategies, telecoms organizations can take control. As 5G networks increasingly comprise a mix of networks and infrastructures above and below ground, the key is to integrate live data from all assets and manage telecoms grids holistically as a single living ecosystem. It is vital that network geospatial systems are a ‘living document’ constantly drawing on live intelligence from the field.

Contributed article by Jay Cadman, SVP Enterprise, IQGeo

 

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.

AR enables better grid damage assessments and improves quality of utility GIS

Maintaining accurate, up-to-date GIS data has been a challenge for utility and communications firms for decades.  Inefficient CAD/GIS workflows result in utility GIS quality degrading with time.  Now with business drivers such as implementing a smart grid, determining service availability and other applications making GIS quality a top priority at an increasing number of utilities and communications firms, new technical solutions are being applied to implement new business processes that raise the quality of utility GIS data over time.  These include CAD/GIS integration; integrated engineering design, GIS and enterprise services; extensive geospatial open source libraries  for viewing, editing and analyzing geospatial and other data; and reality capture often together with AI for inspections, distribution and transmission vegetation management, asset inventories and creating network data models. Another example of a technical advance that can contribute to improving GIS quality over time is a recent proof of concept by Duke Energy, Verizon and EPRI in which augmented reality (AR) was applied to improve the reliability of damage assessments after major events.  While successful in making damage assessments more reliable, Duke found an unexpected result that AR also improved the locational accuracy and description of assets in the GIS.

Broken business processes degrades GIS data quality

 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.  For many utilities and communications firms traditional GIS/CAD business processes, which have been the standard approach for maintaining utility GIS for the past few decades, has simply not been able to maintain cost-effective, real-time, high quality asset location and associated data.  Instead GIS data quality tends to degrade with time.

Challenge: improving the reliability of damage assessments

At Distributech 2019 Aleksandar Vukojevic of Duke Energy together with Paul Giers Duke Energy, Micah Tinklepaugh EPRI, Norm McCollough EPRI, and John Simmins (now Associate Provost for Research and Economic Development at Alfred University) reported on a proof of concept at Duke Energy the primary objective of which was to apply AR to improving the reliability and trust-worthiness of damage assessments after major disasters, but found an unexpected benefit in contributing to improving GIS data quality.

The objectives of the trial were to investigate the application of AR to reduce errors in identifying and characterizing missing and damaged equipment and as a result improve trust in the assessments by the work crews assigned to carry out the repairs required to restore power. It was envisaged that AR could improve damage assessments by visualizing before-storm images over post-storm damage thereby simplifying identifying missing or damaged assets. Currently field technicians visit the area of the outage and use paper and pencil to assess and record damage. Some of the challenges associated with this process is that field technicians, especially less younger, less experienced ones or office staff seconded to the field, may not be knowledgeable about the secondary power grid and in assessing damage to it. The result is missed and incorrect identification of missing or damages equipment. In addition paper processes are slow and error prone making ordering the required replacement equipment a major source of delay in restorating power.  The result is a lack of trust in damage assessments by field crews.

Proof of concept: Applying AR to improve reliability of damage assessments

The trial involved a safety helmet mounted RealWear HMT-1 Android computer with an eye-level display and microphone. It incorporated a GPS so that location was recorded automatically. The HMT-1 was connected via WiFi to router in a truck that connected via a Verizon wide area network to a cloud server.  The field engineer views the "before picture" based on the location data and is guided to align the high resolution, stabilized HMT-1 camera to match the same view to capture a corresponding "after picture". Voice commands and voice responses to damage assessment questions presented in the application are utilized for a fully hands-free user interface. As the engineer performs the work, data is immediately sent to the back office for evaluation and action. The images and data are used to create a list of equipment and inventory required to restore missing and damaged equipment.  The trial did not involve an actual outage but simulated a major outage.  17 different sites were involved in the exercise. 

Results of the proof of concept

Early results indicated that nearly 100% accuracy rate was achieved in damage assessments using AR.  This represents a 50 % improvement over the existing, paper-based process. This resulted in much greater trust by work crews in the damage assessments.  In addition financial benefits were estimated to be significant. The first 12 hours response spent manually recording and transferring assessment reports was sped up dramatically. It was estimated that for an outage affecting 250,000 customers over a four day period, the time to assess and restore power could be reduced by 12 hours with a cost savings of over $ 8 million. One of the big advantages is that training only took 10 minutes even for a worker with no damage assessment experience.  Assessments were delivered to the back office in near real-time, much faster than for paper reports and eliminating the "middle man" who transcribed paper reports into a computer based system reduced the number of errors.

Side benefit of using AR: Improved GIS data quality

While Duke assessed the proof-of-concept to be successful for damage assessment, they also reported an unexpected but important result of the proof of concept.  The process using AR for identifying assets helped improve the quality of utility GIS data compared to the existing paper-based process that could actually result in degrading the quality of the GIS.

In conclusion Duke was extremely happy with the proof of concept. Achieving 100% accuracy even for inexperienced assessors impressed the Duke Energy team and created much greater trust by the work crews in the assessment reports. But AR had an important side benefit - Duke found that using AR to accurately locate and identify assets had the potential to contribute to improving the reliability of asset data stored in the GIS.  This is another example of the application of technology which change business processes and result in improving the quality of GIS data over time.

Sharing real-time utility outage information

During natural and man-made emergencies, a major problem that emergency managers have to face is that, as Scott Sternfeld emphasized at the December Open Geospatial Consortium (OGC) Energy Summit at EPRI in Charlotte, there is no shared public regional, state or national outage map in the U.S.  Emergency management personnel have to go to each utility one by one. Utilities may not have an online outage map, which means calling them.  The Outage Data Initiative is designed to change that by enabling utilities to share outage information in real time.  At Distributech 2019 Zac Canders of DataCapable and Mike Webber of PSEG, the largest power utility in New Jersey announced that PSEG would be using this approach to share outage information gleaned from social media with Comcast, a large communications company.

DataCapable has been mining social media and generating map visualizations using a GIS for some time.  By combing social media channels for specific terms that would signal an outage, DataCapable can notify utility staff including the location of the tweets.  The data can be immediately forwarded to a utility and presented on a mapping dashboard, showing the time and location of the each tweet found.  Experience has shown that with this method utilities can detect outages faster that by relying on traditional methods.  In 2018 DataCapable detected over 181,000 conversations relating to outages on Twitter alone.  Data Capable has provided this service to utility customers such as Seattle City Light and also offers a service that shows outages worldwide. 

Now there is an initiative underway to make it possible to share outage information.  Called the Outage Data Initiative and initiated by the White House several years ago, it is designed to use an XML-based exchange standards to enable outage information gleaned from various sources including social media to be shared.  It is a voluntary open standard for sharing power outage and restoration information. I puts public data, such as that gleaned from social media, in structured easy-to-use and machine readable format.

it is being used by Seattle City Light and four other utilities in the Puget Sound area.  At Distributech 2019 Zac Canders of DataCapable and Mike Webber of PSEG, the largest power utility in New Jersey announced that PSEG would be using this approach to share outage information with Comcast, a large communications company.

The big benefit is that is provides a cost-efficient foundation for utilities, emergency responders, and other first responders to maintain a real-time common operating picture of utility outages and restoration during a disaster.

DataCapable has been mining social media and generating map visualizations using a GIS for some time.  By combing social media channels for specific terms that would signal an outage, DataCapable can notify utility staff including the location of the tweets.  The data can be immediately forwarded to a utility and presented on a mapping dashboard, showing the time and location of the each tweet found.  Experience has shown that with this method utilities can detect outages faster that by relying on traditional methods.  In 2018 DataCapable detected over 181,000 conversations relating to outages on Twitter alone.  Data Capable has provided this service to utility customers such as Seattle City Light and also offers a service that shows outages worldwide. 

Now there is an initiative underway to make it possible to share outage information.  Called the Outage Data Initiative and initiated by the White House several years ago, it is designed to use an XML-based exchange standards to enable outage information gleaned from various sources including social media to be shared.  It is a voluntary open standard for sharing power outage and restoration information. I puts public data, such as that gleaned from social media, in structured easy-to-use and machine readable format.

it is being used by Seattle City Light and four other utilities in the Puget Sound area.  At Distributech 2019 Zac Canders of DataCapable and Mike Webber of PSEG, the largest power utility in New Jersey announced that PSEG would be using this approach to share outage information with Comcast, a large communications company.

The big benefit is that is provides a cost-efficient foundation for utilities, emergency responders, and other first responders to maintain a real-time common operating picture of utility outages and restoration during a disaster.

Augmented reality aids disaster damage assessment by inexperienced utility workers

One of the challenges of disaster response for utilities is situation assessment which involves sending utility personnel to the areas affected by a storm to assess the state of utility infrastructure. Skilled staff are often in short supply at such times and office and other staff without field experience are often assigned to perform damage assessment. These staff find it difficult to perform a reliable situation assessment because of unfamiliarity with the equipment they are looking for. At Distributech 2019 in New Orleans Rodney James of Duke Energy and John Simmins of EPRI described research they have been doing to use augmented reality (AR) to help with damage assessment by using specially equipped glasses to superimpose a map of the utility's infrastructure on the real world making it easy for an inexperienced staff member to see where equipment has been destroyed or otherwise affected by a storm.

Augmented reality used to require large heavy headsets or helmets but now there are a number of manufacturers of specially equipped light-weight glasses that can be used for AR. Duke Energy uses Realwear HMT-1 glasses that can be attached to the helmet that utility field workers are required to wear and that are safety rated. The glasses are smart running the Android operating system and are able to connect via a wide area network for real-time video and audio making it possible for someone back in the office to view what the staff member in the field is seeing. However, this can be a drain on the battery, so the setup can work with just audio communications as well.

I have blogged previously about Duke Energy's MapView mobile GIS application which enables anyone with a web browser to see a queryable map of all of the utility's infrastructure. A worker equipped with glasses sees MapView superimposed on the real world showing the location of all utility infrastructure with appropriate labelling. This enables an untrained staff member to determine very easily, quickly and reliably which equipment has been carried away by a flood, for example.  Of course this assumes that the utility's GIS data is accurate and uptodate.  I have blogged about this problem many times and about the recent research at EPRI to apply deep learning to improve the quality of utility GIS data.

Rodney James described other AR applications of the technology as well such as supervised routine field maintenance enabling new field workers to be mentored from the office by an experienced engineer.  It appears that we may soon see some practical applications of AR in the utility space deployed in the field.  A question then will be will all field staff including linesmen be equipped with glasses or just some.  In Duke's experience field staff have been enthusiastic about the glasses.

Modeling multi-utility interdependent underground networks for disaster management in cities

On this blog most of the discussion relating to underground infrastructure has been focused on construction focussing on the risks to workers and the public and the drag on the economics of construction.  There are other important impacts to not knowing where underground utilities and telecommunications infrastructure are.  During natural and man-made emergencies, there are two problems relating to underground infrastructure that emergency managers have to face.  The first is that, as Scott Sternfeld emphasized at the December Open Geospatial Consortium (OGC) Energy Summit at EPRI in Charlotte, there is no public regional, state or national outage map in the U.S.  Emergency management personnel have to go to each utility one by one. Utilities may not have an online outage map, which means calling them.  This problem is exacerbated by a lack of shared, reliable information about the location of infrastructure.  Together these problems severely hamper first responders.  At the Energy Summit Tatjana Kutzner, working with Thomas Kolbe, presented on a utility extension to the OGC standard for city modeling, CityGML, that allows modeling of multi-utility networks in an urban environment including interdependencies between them.

Disaster management use case

Thomas Becker; Claus Nagel and Thomas H. Kolbe

I remember being impressed by the UK Environment Agency's flood modeling simulations after the 2007 floods in the UK.  And also by Ergon Energy's flood assessment during the Queensland floods in 2011.  In both these examples a digital terrain model and information about building footprints and elevations were used to determine if a substation or a pumping station were likely affected.  It seemed to me at the time that using that information plus network connectivity from utilities would make it possible to determine customers who likely were without power or water.  From a utility GIS perspective this is not a difficult calculation.  Many utilities know for about 85% of their customers which feeder they are attached to and a simple network trace would enable them to determine who will likely be affected by a transformer or substation outage.  Thomas Kolbe and co-workers having been working for some time on a standards-based model for interdependent utility networks to provide a foundation for this type of modeling.

Thomas Becker; Claus Nagel and Thomas H. Kolbe

The next step is determining interdependencies.  If a feeder providing power to a pumping station has lost power, then using the water utility's network connectivity it is possible to determine which customers are likely without water.  If all interdependencies are considered including electric power, communications, water, district heating, and others it is possible to determine all the customers who are affected by a storm or other disaster, how they are affected and to prioritize restoration efforts.

Integrated modeling of multi-utility networks

Standards exist for modeling specific types of utility networks, for example, for electric power the CIM and Multispeak standards are widely used.  However, there is currently no standard for representing all utilities in an urban environment including interdependencies. At the Energy Summit Tatjana Kutzner presented on the work that she and others are doing to address this serious lack of sharable information for emergency managers.

To provide emergency managers access to the utility information they need to put together a composite assessment of the impact of a storm, flood or other disaster requires a model that can model network 3D geometry (location), topology and function, can represent all utility networks simultaneously, can represent the interdependencies between them, is hierachical - able to represent high, medium and low voltage electric or transmission and distribution water networks, and is able to interact with a city model to ultimately determine who is affected by a disaster and how.  Such a model makes enables analysis and visualization during a disaster and to simulate different different disaster scenarios.

Utility application domain extension (ADE)

Thomas Kolbe and co-workers are the developers of the CityGML standard that has been adopted by the Open Geospatial Consortium.  There are several Application Domain Extensions (ADEs) that have been developed to extend CityGML to other domains.  In 2010 a basic extension Utility Networks ADE was proposed for city utility networks.  The intention is to model infrastructure networks both as a 3D topographic, topological and and functional network. In other words, this is not simply a compilation of network as-builts, but includes the function of each component and its relationships to other components.  It knows the difference between different network topologies; water, electric power, steam, wastewater, and communications.  It also knows the interdependencies between different networks.

Tatjana explained how the Utility Network ADE extends CityGML to utilities with a common network core, different network components including functional components and materials classes and packages for specific utilities: electricity, district heating, water and so on.  She also discussed how the Utility ADE relates to existing network  standards.  For example, the electric network package is based on CIM and allows interoperability with CIM.  It doesn't include all of CIM, but only those elements that are important for the use cases that the Utility ADE is intended to address.

Underground utilities in Berlin SIMKAS 3D

Applications

She described a several projects that have used the utility ADE to model different disaster scenarios.

• Simulating cascading failures in Berlin (SIMCAS 3D)
• Risk analysis of supply infrastructure for the German Armed Forces.  Simulation of the propagation of an explosion at a substation to determine how many people would be affected in order to estimate the number of water trucks that would be required to provide water.
• Linking below ground and above ground infrastructure (Xander den Dujin Masters Thesis TU Delft).  Simulation of damage to the below ground electric power network and using pgRoute to determine which street lights would be out.
• Modelling, simulation and visualization of dependencies between drinking water and electrical networks at a combined drinking water facility hydroelectric power station in Nanaimo, British Columbia (Isaac Boates Masters Thesis University of Applied Sciences Karlsruhe).

I should add parenthetically that although there is no public regional, state or national outage map in the U.S.  there are ways of mapping outages using social networks.  DataCapable's Global Power Outage Tracker mines social media and then generates map visualizations using a GIS.  The data is presented on a mapping dashboard, showing the time and location of each tweet found.

Conclusion

The Utility Network ADE Core extension supports geospatial, topographic and functional modeling of multi-utility networks.  It supports modeling of different types of networks including electric power, water, and gas networks.  Because it is an extension to the CityGML urban model the ADE supports linking utility networks with city structures including residential, commercial and industrial.  It is designed to build on existing utility network models such as CIM for electric power networks. It provides a data model for modeling multi-utility scenarios including interdependencies and can be applied for analyzing, visualizing and simulating the disaster scenarios mentioned at the beginning of this blog which involve cascading network failures.  In addition it probably contains all of the data elements required for including distribution analytics for electric power and water networks which would enable this to provide the basis for dynamic modeling of multi-utility networks.

Avoiding serial road excavation work with Waze

Waze, now part of Google, is a crowd sourced handheld app used by 100 million drivers worldwide. It is supported by 500,000 volunteer map editors and 600 partners. Its connected partners program includes 40% of top cities and 60 % of state departments of transportation (DoTs). It is very interesting that Waze has developed a way for governments to report planned and actual road construction which can inform drivers in planning routes ahead of time. This offers a way to provide a single database that could be used to avoid the problem of the same stretch of road being dug up multiple times by different utilities sometimes with a few weeks of each other.

Several years ago I blogged about the online web-based system Koordination im öffentlichen Raum (Spatial, temporal and financial co-ordination of city planning, traffic change, and construction projects on public land) of the City of Bern, Switzerland.  This is a system for coordinating street works that achieves some of the same goals as the 2004 Traffic Management Act in the U.K. It is location aware and enables planners to avoid serial excavations of the same stretch of street or road by coordinating all construction from multiple agencies including Federal, Kantonal and city street and highway agencies, water/wastewater, gas, and electricity utilities, and telecommunications companies so that a section of street or road is not dug up more than once every five years.  In its first year of operation it was estimated that the coordination system saved SFR 7 million.

At GIS in the Rockies Saila Hanninen of Waze described some of the remarkable ways that Waze data and network are being used for purposes beyond what it was initially intended for.

• During and after Hurricane Sandy in Oct 2012 the White house called Waze for help to determine which gas stations were open in the areas hit by the strom.
• For the Rio de Janeiro Olympics, Waze helped to determine where to place three rapid transit lanes that resulted in a 27 % reduction in congestion.
• Waze helped Ghent redesign its city centre to reduce traffic by 40 % which also resulted in fewer accidents and increased bicycle and transit usage.
• Boston asked Waze to help with signal timing that resulted in 18% reduction in congestion just by changing timing.
• During the Pope's visit to Philadelphia, Waze was responsible for a 20% reduction in congestion.
• 63% of callers to 911 don't know their location - Waze can provide accurate locaction information.
• 40% of accidents are reported faster on waze which results in an average of 5 minutes faster response time.

Waze intends to get more proactive.  It now has a crisis response team, that can push messages to Waze users in areas affected by a disaster to collect information about road closures, the state of the roads, which gas stations are open, shelter availability, and safe routes to shelter.

Waze has a vision to eliminate traffic.  Altogether.   To do that requires not only information about the current state of congestion on roads, but also anything that could potentially affect traffic on roads in the future.  Knowing when road and major excavations near roads are planned is essential.  If the Waze partner program included everyone planning excavations on or near roads, it would have developed a database that would provide all the information required to coordinate excavations by utilities, telecoms, and governments.  Similarly to what happened in Bern, this could mean that roads would not be dug up more often than once in five years which would reduce traffic congestion and save money.

Importance of implementing cybersecurity for engineering projects using BIM

At GeoBusiness 2017 in London, Hugh Boyes, a Cyber Security specialist outlined some of the security risks of digital engineering and the importance of cybersecurity for engineering projects.  BIM models, floorplans and 3D LiDAR scans of sensitive buildings and infrastructure can often be found on the web.  He mentioned the floorplan of a major police station, a BIM model of a young offenders facility, and a BIM model of the Victoria Underground station.  All of these could potentially be very useful to anyone interested in disrupting infrastructure.  It is well-known that mapping underground infrastructure reduces risk during construction and also during disasters, natural and man-made.  However, it can also provide information about sensitive infrastructure.  Hugh mentioned substations as particularly sensitive elements of the energy grid.  With traditional centralized generation, substations are critical elements of the grid and are particularly vulnerable.  In many countries disrupting a small number of large substations can leave significant parts of the country without power.   (An advantage of a decentralized grid comprised of many microgrids with their own generating and storage facilities is that it is much less vulnerable.)

For people who are designing and building sensitive infrastructure using BIM, he recommended following the PAS1192-5 guidelines and incorporating security into the design from the start.  PAS 1192-5 specifies processes which will assist organizations in identifying and implementing measures to reduce the risk of loss or disclosure of information which could impact the safety and security of personnel and users of infrastructure or the built infrastructure itself.  PAS 1192-5 is applicable to any built asset or portfolio of assets which is deemed sensitive. It is for use by asset owners and organizations involved in the design, construction, maintenance and management of built assets, especially those who wish to protect their commercial information and/or intellectual property.  Hugh is the joint technical author of BS PAS1192-5 - Specification for security-minded building information modelling, digital built environments and smart asset management.

Distributech 2014: Combining utility GIS and weather data to manage extreme weather events

Utilities have been using geospatial data and technology for many years for mapping and asset management.  But GIS is now being used in many other areas from network design to marketing to outage management to energy conservation.  With the rise of the smart grid utilities are combining GIS and AMI to monitor transformer loading, identify and reduce theft and for disaster management.  Many people in the industry expect that under the impetus of the smart grid the expanding role of geospatial technology will accelerate and that geospatial will become a foundational technology for the electric power industry.  At Distributech, Danny Petrecca, Director of Geospatial Product Management at Schneider Electric made the case that the role of utility GIS is touching every aspect of a utilties business, affecting customers, operations and management.

Disaster management

As an example Danny gave an overview of how GIS, weather data, and the integration of weather data and GIS are helping utilities prepare for and deal with extreme weather events.  The frequency and severity of extreme weather events is increasing so disaster management has become a priority with most utilities. With GIS and weather services utilities are able to plan crew resources and network assets, reduce restoration time and costs, ensure crew and public safety, optimize damage assessment, and keep the public informed during storms.

Hurricane Sandy severely impacted New Jersey Natural Gas (NJNG) infrastructure, 30,000 homes and over 275 miles of main were damaged.  NJNG found that the biggest reason that they were able to restore service so quickly was their ability to analyze and manage the restoration process using their utility GIS system.  That they had been using GIS for a decade prior to Sandy meant that they were better prepared for such an extreme weather event than they had expected. The GIS enabled engineers to view the network in the context of the damage caused by the storm and it enabled them to identify critical valves and shut off gas service in a matter of hours.  It helped them restore over 255 miles of pipeline in under two months.  It helped them resectionalize their network into smaller sections which they were able to repressurize in one day.  A very important benefit of the GIS was that NJNG were able to provide timely and accurate information to the public on the status of the network including estimated time of service restoration.

Weather services

Weather services can provide information, (historical, current and forecasts), about lightning strikes, wind, temperature and humidity, ice and snow, and storms.  They can predict precisely when and where a storm will hit in a utility's service territory.  This enables a utility to schedule crews on-call, holdover, and dispatching and the type of equipment that will be required.

Before a storm weather services can provide Before:high quality forecasts, expert meteorological consultation, and real time alerting. When a storm hits, weather services provide real-time lightning strike information (where and when), nowcasting tools, and current situational awareness.  And after the storm weather services can help with post-storm inspection and assessment.  Weather data is available in digital form and some provide it as a web service compliant with the Open Geospatial Consortium's (OGC) web services standards such as WMS.

Integrated utility GIS and weather services

By integrating weather services and utility GIS allows you to do even more interesting things, like quantitatively monitoring storm impact on  infrastructure like transformers in real-time, using geofences to setup alerts for lightning strikes, and correlating storm and outage events to be able to predict where issues can be expected as a storm moves across the utility' service territory.