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A startup emerges to use wireless mesh and the cloud to fight energy theft

Katie Fehrenbacher — Tue, 22 Jan 2013 05:00:34 +0000

Utilities call energy theft — like when an indoor marijuana farm taps directly into a high voltage line for its super bright lights — a “non-technical loss” or a “commercial loss.” It’s a bizarrely mundane term to describe thefts which cost utilities billions of dollars in losses a year around the world. For example, Canadian utility BC Hydro has estimated that it’s losing a shocking $100 million each year from power theft.

That security problem is what a young Canadian startup called Awesense has emerged to tackle. The company, founded back in late 2009, has developed a product that uses power line sensors connected through a wireless mesh network combined with a cloud-based application. Utility workers can use the combo to remotely monitor and learn details about how much power their companies are actually distributing, versus how much power is being measured by their billing systems. In other words, “how much revenue they’re losing,” as Awesense founder and CEO Mischa Steiner-Jovic explains it.

Awesense’s technology is a mobile solution — utility workers clamp on the power line sensors wherever they suspect theft is happening, and if no theft is being detected they can simply move the network to another part of the grid. The sensor nodes create the ad-hoc mesh network amongst themselves (via the 915 band in North America, for all you wireless spectrum geeks out there).

The capital expense of the networks are low enough that Awesense has now decided to start selling theft detection as a service. Awesense will install the technology for utilities for no upfront cost, and then take a cut of the revenue saved. Steiner-Jovic says over the past few years they’ve realized that there’s been a lot of interest from utilities for the theft-detection product, but that utility budgets are often times small and rigid.

In addition to growing its theft detection-as-a-service this year, Awesense is hoping to grow its list of international customers, where energy theft is a massive issue. Currently it has customers (it’s not disclosing the names other than Fortis BC) in Canada, the U.S., and Latin America, and it’s looking to expand more into Latin America as well as Asia Pacific and Europe. India has some of the highest theft losses in the world, with close to 30 percent of the power in the country lost to theft (check out some photos of the crazy jerry-rigged power grids of Old Delhi). The former Soviet Union has almost 50 percent. Brazil is at 15 percent.

To date, Awesense has been mostly bootstrapped, and just raised a “seven figure” round from angels last Summer. Steiner-Jovic says the company could be interested in raising a venture round in the future to grow its business. Applying IT tech to the power grid and clean energy is still an area where startups have been able to get funding from some venture capitalists, despite the difficult funding environment for most cleantech.

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When big IT goes after big data on the smart grid

Adam Lesser — Tue, 20 Mar 2012 17:49:42 +0000

This article originally appeared on GigaOM Pro, our premium research service (subscription required).

With many utilities facing the task of storing petabytes of smart meter data for as long as seven years in order to satisfy regulatory requirements, the ability to house and leverage the massive load of data accumulating from the smart grid is a significant IT challenge. And it isn’t a competency that many utilities have had historically.

I’ve written before about how utilities are transforming into IT companies, as they must learn to manage and mine increasing amounts of data. The first task for all utilities engaged in smart meter deployments has been to process smart meter readings to ensure integrity of billing, a market known as meter data management systems (MDMS). Two of the key players in that market, Ecologic Analytics and eMeter, were snapped up by Landis+Gyr and Siemens respectively over the past four months.

That market has been fairly staked out at this point, and has relatively finite growth potential because there are only so many utilities who will need a MDMS. But the opportunity to do something with that data is a crucial big data challenge and potentially a much bigger market because tools to mine data can continue to evolve to solve problems for utilities and save them money.

Stepping into the fray have been established IT companies. EMC made a strategic investment in smart grid networking company Silver Spring Networks in December and data warehousing and analytics firm Teradata has partnered with global meter maker Itron. Companies like EMC and Teradata are quick to point out that existing MDMS software platforms for processing meter data have none of the high performance data processing engines needed to effectively manage and mine data.

EMC, for example, is relying on its Greenplum analytics platform to make an impact on utilities’s bottom line. The company has been using its reputation as a leader in storage warehousing to make the case to utilities that its hardware and software integration is best suited to help utilities manage its big data problem. And the core of that message has been that utilities need to evolve beyond MDMS.

“Once the data is collected by an MDMS, the fundamental problem with utilities is they’re trying to apply analytics to the MDMS on an application that is already performance bound,” said Thomas Price, the Global Sales Director for the Utility Industry at EMC.

The fact that Silver Spring Networks was already deploying Greenplum internally for its utility clients was one of the reasons that drove EMC’s investment. Price added that Silver Spring was one of the only smart grid providers he’s dealt with that is using Hadoop to develop approaches to unstructured data on the grid, thinking in terms of what IT analytics tools can be brought to bear on the petabytes of data accumulating.

And what could an analytics engine specifically built to aggregate, correlate and mine disparate data, ranging from meter readings to weather data, actually do for a utility? For starters, a high performance data engine should increase the speed with which meter readings are batched, a step toward providing real time data. Reports are that data warehousing software not optimized for the smartgrid can take as long as 12 hours to turn over a four hour block of smart meter readings whereas Price says Greenplum will do it in 15 minutes.

But much more interesting is the possibility that analytics can save utilities money by solving problems like “non technical loss,” or people stealing power. We don’t usually think about the possibility that a pot farm is stealing power but power theft is an actual problem for utilities. A couple percent in places like the U.S., but almost 20 percent of power is stolen in countries like Brazil. Analytics engines pick up unusual patterns like correlating the amount of power going out the door versus what’s getting billed in order to see where anomalies exist. Major Canadian utility, BC Hydro, has issued a request for proposals solely focused on theft prevention.

Other applications include using analytics to figure out the source of an outage on the grid, rather than rolling a truck to the end user reporting the outage, which is costly and inefficient. Additional applications revolve around addressing power quality issues like low voltage spots on the grid.

In our conversation, Price noted that EMC is employing 25 data scientists with PhDs in math and statistics, to correlate data and write algorithms specific to industries like the energy sector. The fact that a $60 billion data storage and IT company is employing its software know how to the smart grid tells us that just ingesting and warehousing that data will not be enough going forward. Rather, the real opportunity isn’t installing the meter or verifying the meter read, but helping utilities use that data to build better businesses.

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When big IT goes after big data on the smart grid

Adam Lesser — Tue, 20 Mar 2012 13:00:14 +0000

The ability to house and leverage the massive load of data accumulating from the smart grid is a significant IT challenge. And it isn’t a competency that many utilities have had historically. That market has been fairly staked out at this point, and has relatively finite growth potential because there are only so many utilities who will need a MDMS. But the opportunity to do something with that data is a crucial big data challenge and potentially a much bigger market because tools to mine data can continue to evolve to solve problems for utilities and save them money.

Related research and analysis from GigaOM Pro:
Subscriber content. Sign up for a free trial.