Hydropower and the Internet-of-Things: new horizons


Posted on: January 10, 2018 by Jean-Marc Lestic

Across the utilities sector, until very recently, operational and information technologies existed in different and distinct domains.  The tools and technologies used to measure and control generation, for example, never came close to sharing data or functions with the tools used to service customer accounts or for trading.

It wasn’t just the technologies that were separate.  The professional profiles of those who used the tools were equally distinct:  power engineers used the former, while administration, financial control and marketing used the latter. The arrival of the Internet-of-Things, coupled with the democratization of data-analytics, is set to bridge this split.

Recently I’ve been focused on the ways in which data analytics can change opportunities and behaviors in the hydropower sector, and it’s worth taking a moment to think about this in terms of the IoT and the way it changes the divide between operational and information technologies.

Hydropower and the IoT

Let’s start by considering where and how the IoT is becoming enmeshed across the hydropower industry. Cheap sensors with more or less zero maintenance overheads are appearing right across the hydropower operational landscape as components of the industrial IoT.  Location isn’t strictly limited to the dam itself:  upstream and downstream, sensors can now transmit continually, for example, to provide comprehensive flow of data.

With open data becoming increasingly important, the actual ownership of the means to generate data becomes less significant that the willingness to share and contribute.  Extended networks of monitoring devices owned by power companies and river authorities, for example, can work together to build up ever-richer pictures of the changing state and impact of water resources.

Sensor use increases correspondingly inside the actual hydropower facility too as the industrial IoT begins to take shape.  Here again, sensors can provide a continuous, high-rate stream of data to keep operational staff informed on everything from the stability to the heat-generation in turbine bearings.

When we look downstream, to the point at which power is consumed, we are beginning to see a corresponding growth in IoT data-generation.  We can see, for example, near-real-time visualizations of the mix of generation sources – helping us understand the ratios between solar, wind, hydro and traditional non-renewable sources.

Further down the line, in civic, industrial, commercial and domestic environments, smart sensors provide an increasingly articulated and detailed view of usage.  My new IoT-enabled fridge, for example, knows when I am going on holiday, so it can moderate cooling patterns for the duration of our vacation.

Sensors are easy: skills less so

The sensors that are the foundation of the industrial IoT are relatively simple to source and install.  The challenge today, lies in finding the skills needed to make them deliver value – the skills capable of envisaging and implementing data-driven operations. Some of these are highly-specialized.  The ability to establish and manage an operating environment made up of thousands of sensors, remains a relatively rare skill.

Equally rare are the skills needed to ask how theoretical connections between diverse sensor groups can be turned to direct operational advantage.  The range of industry-specific and IT skills needed here is wide and getting wider.

These span diverse activities.  You need expertise in developing the cognitive machine-to-machine communications needed to tune hydropower performance according to demand and environmental conditions. At the same time, you need the skills to integrate operational and information technologies.  Preparing accurate forecasts and linking these to trading systems, for example, combines expertise which has traditionally been separated according to professional focus.

And it’s not just new skills that are needed.  To maximize benefit from the industrial IoT demands levels of computing and storage capacity that few utility companies have available.

New landscapes – new partnerships

A few years ago, I met a really successful sales guy.  He sold network capacity to enterprise clients.  He always used to start discussion with a simple question.  He’d ask, “Are you satisfied with your networks?” – and nobody ever said yes. Sales often followed.

In some ways, the IoT and data analytics revolution invites a similar sales approach.  Paint a picture of a world transformed by data-driven insight and then sell the technologies and services on which the transformation depends. But that is an old-school sales approach – and not one, I believe, that is any longer effective or sustainable.

The reality here, is that neither the giant or the smaller regional utility players have the will or the depth of resources needed to invest in the expertise or computing resources required by this digital transformation. The potential is there – but only through partnership.

There is no reason why every hydropower company cannot:

  • Make this transition to data-driven operations.
  • Benefit from the intelligence gathered from a massively extended IoT network of owned and shared sensors.
  • Integrate and combine these new data resources for business advantage across both operational and commercial systems.

But it will only happen if the hydropower company has access to partners with both these specialist skills and resources, and with a deep understanding of how hydro works. Over the next five years or so, I believe that the traditional divide between operational and information technology will have all but disappeared in the utility sector.

The question for any forward-thinking hydropower player today, perhaps, is: are you going to watch it happen – or are you going to make it happen?

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About Jean-Marc Lestic

Operations Manager, Atos Worldgrid
As an operations manager for Atos Worldgrid, Jean-Marc has extensive experience in data analytics and machine learning in the utilities sector.  He has worked on major projects from Cupertino to Bangkok, often with a special focus on SCADA.  He holds an Engineering Master’s Degree from ISEP (Paris), and subsequently specialized in big data at ENSIMAG (Grenoble).  Jean-Marc joined Atos in 2005 from transport software experts Amadeus.

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