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Government Statistical Service (GSS) Conference 2019

The conference is titled “GSS Conference 2019: Our Statistics, Today’s Issues” with a theme of government data informing public debate and shaping policy through evidence-based decision making.

The conference will be an exciting opportunity to meet other statisticians and data scientists working across a variety of organisations and will allow you to share ideas and examples of excellence in the field of evidence-based decision making.  The first GSS Awards will also be held at this year’s conference.

If your poster has been chosen for display, please remember to print it in A2, and if you are not attending the conference, make sure you arrange for it to be brought to the venue on the 1st October 2019.

It’s easy to join – simply create a Slack account, add yourself to the GSS workspace ( with your government email address and then click ‘add a channel’.

Bringing Utility Analytics into the Future with Artificial Intelligence: Exclusive Interview with Robin Hagemans of Infiniot

As smart meters and data analytics become more of a standard cornerstone of utility operations, no longer a niche tool, leaders at these energy providers must become comfortable quickly adapting to new ways of doing business.

The use of artificial intelligence, or AI, is key to processing and taking full advantage of the new and growing sets of data that are already one of the utility industry’s most important assets.

I had the opportunity, based on my education in chemical engineering and the strong belief in data within my company, to build a strong team to develop thought leadership on how data science modelling and simulation could add value to complex energy transition utility challenges.

These algorithms are input for AI systems that can control parts of these challenges for example in how to charge electrical vehicles in the smartest way or how to maintain the grid stability in areas with many PV panels and heat pumps.

Software engineering habits with good development practice, test scripts and continuous integration and continuous delivery processes are mandatory, especially for the mission-critical utility systems.

AI has to prove its value the following years where the volatile effects of the energy transition for example could be better understand and controlled with a data driven toolset like AI.

MC: As you look at the coming years in the energy space where the topics most often discussed include renewable energy, cybersecurity of the grid, and grid modernization, how do you see artificial intelligence fitting in?

This first step approach would become too expensive for a positive business case on a certain moment.    It will probably be smarter to change direction and move the AI to the data and to develop a more decentralized AI system.

AI can also handle capacity problems based on volatility of renewable energy and both recognize cybersecurity anomalies, probably both decentral and maybe on the same chip in a future energy device.

While local real-time problems better should be handled locally with embedded AI on these energy devices, a smart combination of data science and software engineering.

More positively, most of the new data that will be generated form future utility systems still needs to be designed and placed, so today is the opportunity to prepare for valuable AI systems in the future.

RH: I see that many of the speakers on this conference are really innovation-minded people who all have a very strong belief in the power of data, and a strong idea and knowledge in how AI is the tool to make a next step in decision systems for complex questions in utility firms.

More and more they are able to enter the boardroom and not only show value with their AI solutions, but also to influence the company roadmaps to create better conditional aspects for the data functions in their organizations, as I mentioned earlier in this interview.

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