A power cut in most places will bring down the streetlights for a while. But in India last July blackouts nearly brought down the country. Around 700 million people were without power because of a grid collapse dubbed ‘Blackout Tuesday.'
The power outage stretched around 2000 miles (3200 kilometers) across the north of the country, from Arunachal Pradesh in the east to Rajasthan in the west. The disaster, like major outages previously in Paraguay, Java, and America, highlighted the frailty of power grids and put the spotlight on how utilities could avoid such events in future.
The answer, many believe, is smart grids: power networks with embedded intelligence and a bigger capacity to deal with highs and lows in energy demand and supply. Smart grids are deemed to be so critical to our energy future that in many countries there is a legal requirement for them to be introduced within a given timeframe.
But this data poses a challenge for utilities, because there is so much of it. Traditionally, a power company might take a meter reading from a customer once a month to collect data. With smart grids, the amount of data has skyrocketed. Some utilities admit they have not yet really worked out what to do with all this information.
"It is not unusual for power companies to still be managing data at a level of granularity comparable to that of pre-smart grid days, despite now having technology that can deliver much more detailed information," says Smart Grid Update in its Data Management for Utilities briefing.
However, it adds: "While the challenges associated with managing the masses of data associated with smart grids are certainly significant, they are not overwhelming.
"Indeed, utility information management is simply one of several ‘big data' areas which a growing number of IT vendors are rushing to solve. The tools to deal with AMI data may yet need some refining, but they certainly exist."
So how can data analytics help power companies? They can help cut blackouts in two ways. First, having intelligence on the grid can help utilities catch failures as they are beginning to happen, and come up with workarounds that stop them from spreading. Second, a better understanding of grid behavior can help a utility balance supply and demand so the conditions for a blackout are less likely to happen in the first place.
There are several technology companies that have developed advanced analytics systems for utilities, but for some utilities the problem is not what systems they need to buy to deal with smart grid data, but what changes they need to make to their own businesses.
"The utility is being inundated with phenomenal amounts of data," says Brian Rich, Vice President of Business Technology at Pacific Gas and Electric Company (PG&E), one of the largest combination natural gas and electric utilities in the United States.
"Process analytics means that for the first time the company is breaking down traditional silos that haven't had the information required to integrate their processes."
PG&E has so much smart grid information (70 terabytes of AMI interval data alone, increasing by 3 terabytes a month) that it has decided to replicate its data sets so it can perform deep analytics on the replicated set without interrupting the operational criticality of the data.
This may sound like a lot of effort, but Rich says it is paying off for the utility. "Before we were flying blind," he states. "Now we can have much more meaningful conversations with our customers about demand-side management programs."
Plus the technology is helping PG&E to reduce grid failures. "We do a lot of over-the-air remediation," Rich explains. "If we have a meter not giving us readings we would previously have had to roll a truck. Now we can fix it by pushing a firmware upgrade over the network.
"This, coupled with our significant investment in fault location, isolation, and service restoration, has enabled us to be more proactive about asset failures."
Ultimately, such measures may help make blackouts much more a thing of the past.
Ben Kellison, a smart grid analyst at GTM Research, says: "Analytics and processing power on the grid is beginning to allow utilities to identify and isolate the causes of major blackouts before they cascade across the transmission grid. Meanwhile last-mile grid devices are providing the insight to reduce local outage duration, improve customer service, and increase a utility's operational efficiency."
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