Augmented Reality for Water Utilities: La Forge into the Future!

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Let’s imagine a world where people use Augmented Reality for a moment. Pull up a bean bag chair and we will pretend we’re at PARC. First, we need a story. How about an earthquake in a big city? Hundreds of water pipes can break in a quake. Oakland, CA is a good example. Their average water pipe is 80 years old, with some pipes dating back to the 1880’s .

Enter John, a water utility superintendent in Oakland and ardent “Star Trek” fan, who is in the middle of a busy day in the field when the quake hits. The ground shakes, roads crack, bridges sway, and hundreds of John’s water pipes burst.

He drives a truck, so he can get creative in accessing the sites despite traffic congestion. Besides, he likes off-roading and this is a great excuse to use government property to do such.  He needs to decide quickly which pipes to repair first, but headquarters is without power and thus no help. Where should he direct his crews?

John pulls up his augmented reality app and accesses an interactive tree map to help solve his dispatching problem. Here is a mock-up of John’s view:

Water AR

“Wait,” you say, “treemaps in an earthquake?”

Yes! Treemaps are for real. They provide a fast, visual way to sort information into an easily scanned hierarchy. Scanning spreadsheets or tabular data is difficult and time consuming.

But will people use treemaps?

Ben Schneiderman of Perceptual Edge explores sales, product and even coffee flavor tree maps in a brief paper outlining the effectiveness of this visualization. So we know they are useful in a range of scenarios.

Back in 2010, Marcos Weskamp made a news tree map that demonstrated the ease of scanning and filtering content. He is now Head of Design at Flipboard, the successful web site and app that uses related information architecture to build treemaps for content curation.

Still not sold? Even the big guys are loving treemaps.

Microsoft is adding treemaps to Excel 2016.

At Oracle, the advanced user interfaces division recently published a paper entitled “Enterprise Network Monitoring Using Treemaps.” Study participants using treemaps performed better and were faster than those using tables when:

  • Identifying or counting items
  • Comparing using one or more criteria
  • Doing advanced comparison
  • Performing open-ended analysis

Okay, now back to the story.

John is in his truck in the middle of an earthquake and doesn’t have time to crawl through pages of tabular data when there is so much commotion around him. He needs better, more intuitive tools to help him make fast, accurate decisions. Hence, interactive tables in augmented reality.

Augmented Reality is a great way to represent non visible aspects of reality to support cognition during critical thinking. John can visually filter through the most significant water breakages to minimize the impact of the earthquake on his community.

John can quickly navigate the breakage alerts by population density, risk, electrical asset proximity and more. He filters his list by predicted water loss–Oakland’s in a drought and can’t afford to lose large amounts of water–and immediately dispatches crews to circumvent any further water loss.

But more importantly, John gets to live his “Star Trek” dream of working like Lieutenant Commander Geordi La Forge.

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Utility 3.0? We’re not at 2.0 yet!

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If you think that the grid is getting more dynamic as we move towards Utility 2.0 (as I wrote about in a previous post), just what till you see Utility 3.0.

“Wait!” you say. “We’re not even at 2.0!”

And you’re right. In the United States, a recent report by the Federal Energy Regulatory Commission (FERC) estimates that less than one-third of energy consumers have smart meters. Other places, such as Italy, have a much higher penetration rate of smart meters, but overall we are still just at the start of a ubiquitous smart grid.

Still, Utility 2.0 looks to be a transitional state that prepares the way for an even more dynamic energy system which is expected to evolve into what many now call  the “Transactive Energy Market.”

With Utility 3.0, the energy distribution system will consist of numerous microgrids, and an even larger network of nano grids at the consumer level, that encompass centralized and decentralized energy sources. Our current utility-scale power plants run on nuclear, hydro and fossil fuel won’t go away overnight. The current generation of wind farms and utility solar will be functional for a long time. But added to their ranks will be numerous distributed energy resources such as residential solar, community solar and batteries of many different capacities, functions and locations.

Here’s what it will look like, according to a Gridwise infographic:

Gridwise diagram

At the heart of all of this will be energy transactions between consumers, suppliers of all sizes, and energy markets from single people living in apartments to power plants and industrial sites.

What you know today as your local electric utility will likely morph into a distribution system operator, or DSO since we love industry abbreviations. In the infographic, the DSO sits squarely in the center. DSOs will operate and maintain the network (wires that move energy between buyers and sellers), and also the mechanism for reconciling all those energy transactions.

Think of this utility evolution as the difference between telecommunications companies (telcos) before Internet Protocol (IP) became widespread, and telcos today. Before the Internet, telcos were network operators (wires and airwaves) and the services provided on those networks were limited to what telcos offered (local calling, long-distance, three-way calling, call waiting, etc). Consumers were captive to those services and providers.  With the emergence of IP, telcos faced a critical decision: do they continue to operate the wires, or do they create a platform on top of the wires with the ability to create and extract new value that might even combine third-party services with theirs? Or, do they turn their core services into commodities and let third party service providers extract the value from new, niche products?

Just like the telcos, utilities in the era of Utility 3.0 need to new ways to create value, including extracting value from enabling the transactive energy market.  Keeping supply and demand balanced on a grid will be more complicated than moving bits across the Internet, for several reasons:

  • One, reliability and safety are at the core of energy distribution network value.  The health and reliability of the grid depends on the balance of supply and demand, especially given the fact that many more suppliers are selling into the energy market using the distribution network.
  • Two, every buy order must be filled, or else people will go without power.
  • Three, it will matter where a transaction takes place, since it involves physically moving a commodity (electricity) at a specific place and time.  In the internet transaction, it doesn’t much matter where the parties are located, other than for legal and tax reasons.

The complex web of new services, service providers, and transactions will spawn new capabilities layered above the existing network, in what is called the Transactive Energy Platform.  At the core of this new platform resides real-time and even predictive analytics that account for the time, place and network location of production, consumption and transaction. This new platform must  dynamically optimize the network services and energy production and distribution assets based on reliability, cost, and market pricing at all levels of the distribution network. That will be the role of situational intelligence in Utility 2.0 enabling a successful transformation to Utility 3.0 and the transactive energy market.  That’s what I’ll talk about in my next post.

 

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A Nobel Prize in Economics for Analytics

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Nobel Prize

This week, Professor Angus Deaton of Princeton University was awarded the Nobel Prize in Economics for his work in improving economic policy making through bottom-up analysis of individual consumption.

As the Swedish academy stated, Deaton developed a system for estimating how demand for each good depends on the prices for all goods and on individual incomes. Deaton’s system is now a standard tool for research and in practical policy evaluation.

In a way, Deaton’s prize is a victory of analytics.

According to a Reuters article, he has pioneered the use of household survey data, especially data on consumption, to measure living standards and poverty.

Deaton’s breakthrough comes from analyzing individual consumption patterns, rather than strata of earned income, to better understand households living in poverty. This approach relies on a bottom-up analysis of individual data, rather than a top-down theoretical model of how households in poverty behave.

A better understanding of poverty, in turn, leads to new and improve methods for economic development to alleviate poverty.

(Image courtesy of Flikr)

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SI World 2015: Learn about Intelligent Energy Storage

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Utility-scale energy storage is disrupting the electricity industry, which means it’s disrupting just about everything.

Storage on this scale means that energy no longer needs to be consumed the moment it’s produced. That balancing act places huge stress on the technology, markets and policies that drive the industry. Now, excess energy—such as roof-top solar on a sunny day, wind power during blustery weather, or base-load generation at night—can be absorbed into giant batteries and used during times of peak demand.

Energy storage has its own challenges, though, that turn out to be situational intelligence applications. Where should you locate your batteries for maximum grid reliability? When should you charge or discharge batteries? If you know the solar or wind forecast and your fossil-fuel generation capabilities, how do you optimize your fuel mix for low carbon, low prices and high reliability?

Dr. Hiroshi Hanafusa of NEC will discuss the issues of batteries, cloud networks, services and big data analytics that drive the economic value of energy storage. If you’re curious about how storage will transform the powered world as we know it, don’t miss this session.

This year, SI World takes place Wednesday, October 28, in New Orleans. Registration is still open.

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Situational Intelligence for Cyber Security

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Network security

Cyber attacks aimed at U.S. businesses and government entities are being launched from various sources, including sophisticated hackers, organized crime, and state-sponsored groups. These attacks are advancing in scope and complexity.

The electrical industry is uniquely singled out as a target for cyber attacks.   The Department of Homeland Security Industrial Control Systems Cyber Emergency Response Team (ICS-CERT) reports that in the first half of 2013 some 53% of all reported cyber attacks were on the energy sector, followed in prevalence by 32% on Critical Manufacturing, and 5% each for the next most targeted sectors (communications and transportation).

The electric utility industry is also unique among critical infrastructure sectors in having a mandatory and enforceable reliability and cyber security standards regime. Under the existing regime, the electric power industry works closely with various government agencies on securing the power system. Additionally, utilities actively implement cyber security measures on their own, and help develop reliability standards with the North American Electric Reliability Corporation (NERC).

Imminent cyber threats require quick action and flexibility that can come only from close collaboration with the government and emergency response protocols that are planned and practiced before a disaster strikes. It also takes situational awareness of a variety of data to isolate and prevent or recover from an event. Increasingly the focus is on defense in depth coupled with resiliency when a vulnerability is exploited.

Getting all the stakeholders that are responding to a cyber event on the same page requires access to intuitive and comprehensive visualization of the problem, drawn from analytics that span all relevant data sources. Also helpful is quick access to various response mechanisms–operational controls, social media, first responder communications—integrated with the analytics and visualization:

Situational intelligence applications show promise as an approach to gather all data sources and stakeholders together into a coherent approach to cyber event preparation, prevention, assessment, recovery and documentation.

John Di Stasio is President of the Large Public Power Council.

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SI World 2105: Experience the Diversity of Situational Intelligence

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Situational Intelligence is rapidly spreading to new sectors and markets.

At the upcoming SI World conference, representatives from nine different companies and organizations will present situational intelligence use cases covering railway operations, storm damage assessment, heavy equipment tracking, skilled workforce management, utility planning and operations, and military logistics.

This diversity of applications shows the applicability and value of performing analyses across multiple data silos and presenting the results in intuitive visualizations for immediate action. As data continues to multiply, especially because of the proliferation of IoT devices, such analysis will become even more common and more valuable.

This year, SI World takes place Wednesday, October 28, in New Orleans. Registration is still open.

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Water, Energy and Situational Intelligence

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water_tower

Although rain falls freely from the sky (except in California, but that is a subject for another post), water utilities consume a lot of energy doing things like pumping water into water towers.

According to the Alliance to Save Energy, energy is among the top three costs borne by water utilities, often coming second to labor. In developing countries where labor costs are low, energy is usually the highest utility cost.

Energy consumption related to water production, distribution and consumption include

  • Pumping from wells, streams, lakes and oceans
  • Desalinating salt water
  • Operating treatment plants
  • Pumping to and from water towers and across elevation zones
  • Maintaining proper pressure in pipes
  • Heating and chilling water for end use

Driving down energy consumption lowers costs for water utilities and their customers, plus provides the related energy utilities with additional kilowatt hours to meet other growing demands.

You can reduce costs by optimizing production and distribution according to the forecasted supplies of water and energy. Because energy prices are dynamic, varying the time that you treat and pump water makes a difference. The fact that water is much easier to store than energy also creates opportunity. You can produce, pump and store water while rates are low, and then distribute it later.

This sort of optimizing requires analysis of current and forecasted supply, demand and cost of both water and energy. Other relevant factors include the weather and the relative elevation of water production, storage and consumption sites. Pulling all these data sources together into a predictive solution that provides actionable insight requires analysis across time, territory and network, a substantial analytical task at which situational intelligence excels.

The Alliance to Save Energy presents several case studies of energy efficiency for water. One example comes from Pune, a city of more than 3.5 million people in India. By focusing on energy efficiency, the Pune Municipal Corporation reduced their energy consumption by 3.8 million kWh per year. That produced annual savings of $336,000.

Capital is often in short supply for water utilities, especially in the US, so the annual savings are certainly welcome. As a bonus, energy efficiency measures also allowed Pune to deliver 10 percent more water without adding any new water production capacity, saving further capital. For a utility, that’s almost like cash falling from the sky.

 

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