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  • admin 9:51 am on November 21, 2015 Permalink
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    Will IoT & Analytics Really Make Full Automation Possible for Utility Power Networks? 

    There are now machines that have conquered the game of chess and starred on TV game shows. Soon we may even be able to chat and befriend them, a reality that perhaps isn’t too far off, when companies like Facebook are investing heavily in it to ensure secretive development on how its apps might be able to better help you find and communicate with your friends – automatically.

    What about in our Utility firms? Will we see machines roam more freely in the area of power network control? There is much debate around the level of automation that Internet of Things (IoT) based technologies, driven by analytics, will enable in network control, and over what timescales.

    But in reality, is full automation actually even possible?

    I’ve written in a previous blog post that today, analytics within the Utility networks business falls into three categories:

    • Distributed network solutions implemented on the network itself which have “productised” analytics at the heart of what they do;
    • Virtual control and monitoring solutions that continually run and assess the state of assets based on configurable analytics algorithms; and
    • Advanced analytics, and companies with “utilities big data” offers that integrate all data from across the Utility for analysis in conjunction with other relevant external data.

    Distributed network solutions” by their nature are automated, needing little human interaction. So this area is not contentious. But in “control and monitoring”, the idea of automation certainly is more contentious.

    So is full automation possible? In my opinion, “yes”, in theory at least. Although it may well be that automation is implemented very slowly given that installed physical infrastructure is a long way off managing and responding to the sophisticated control signals required, especially on low voltage networks.

    But we have to remember that culturally, this is a big deal. Network control is safety critical, and there will always be much that is unknown about how a power system might operate. full automation is never trusted enough to be implemented.

    Today virtual control and monitoring as described above is gaining traction, and helps engineers operate networks better. But this alone will not enable full automation. However, there is a trend emerging that challenges my own categorization of the use of analytics within the Utility networks business, which could lead us towards full automation. The three categories as I outline them above are merging.

    We are already seeing control and monitoring solutions emerging that can push analytics packets onto distributed assets real time, based on internal and external analytics triggers. Advanced analytics, and big data platforms are moving ever closer to real time, allowing more and more network data to be analysed in near real time to improve network operation, in combination with more parameters that a human could nominally apply manually.

    I believe that what we’re seeing is just the start. As the industry matures in its use of IoT, and analytics on the data from IoT, network analytics will only accelerate and become ever more intertwined. The way that analytics is performed today – separately – will become a thing of the past.

    Many in data and analytics talk about merging data from IT and OT systems for analytics purposes. Longer term, I see a single environment not only “doing analytics”, but gradually automating network operation, as well as the execution of many other businesses processes in the digital network business of the future. This is the latest potential of IoT for Utility power networks.

    Interested in discovering how IoT data can generate more value for your company when combined with business operations and human behavioural data? Read on.

    Iain Stewart is the principal utilities expert for Teradata in the EMEA region, with over 13 years of experience in utilities sector. Iain also has in depth experience of both smart metering and smart grids, including how these link to and support the wider sustainability agenda. Other areas of experience include renewable energy, and smarter cities. Connect with Iain Stewart on Linkedin.

    The post Will IoT & Analytics Really Make Full Automation Possible for Utility Power Networks? appeared first on International Blog.

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  • admin 9:52 am on December 14, 2014 Permalink
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    My Take: Data Is Full Speed Ahead: Are you Ready? 


    From Macy’s photo gallery.

    While I’m prepping for the holidays, like most people, shopping is on my mind. Scanning the news, I noticed an article discussing the link between dropping fuel prices and Macy’s expectation of increased profits. With lower gas prices, consumers will theoretically have more money to spend in the stores, and with holiday shopping in full swing, that’s a good thing for the retailer.

    But this got me thinking about another connection that maybe isn’t so obvious. What does this influx in consumer spending mean for marketers? After all, more consumer spending means more data coming into the organization and greater opportunities to build relationships with customers based on individualized insights. Businesses need to ask themselves: What can we do with this influx of data and are we ready for it? Do we have the systems and solutions in place to fully capitalize on the possibilities increasingly more customer data presents?

    Many retailers prepare for this sort of spike in activity around the holidays or other buying cycles relevant to specific industries, but I’m not convinced businesses are doing enough to prepare for spikes that result from imminent macro-economic, social and political changes (see G-20 commitment to up the global economy by $ 2 trillion over the next five years. This too means … more data). Retailers, indeed all businesses, who aim to capitalize on these future happenings need to establish best practices now, and invest in the tools and protocols needed to make the most of data influxes no matter how and when they crop up.

    That’s my take. Please share your views or best practices about how you’re getting the most value from your data.

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