| | JULY 201919CIOReviewCX INSIGHTSArtificial Intelligence Business SolutionsA Unique Approach to AI DevelopmentHOW AI CAN IMPACT ENERGY SECTORBy NAZIM OSMANCIK, Group Head of Economics & Fundamentals, Centrica Plc.AI and ML are changing the world around us and the energy sector is no exception. Organizations that can harness their power in the right way and early on will benefit the most. Technology always played a crucial role in the energy sector, especially in engineering applications. However, the recent revolution has been in the digitalisation of data and utilisation of algorithms that can `learn'. This opened the door to advanced automation and AI applications that cut across sectors.Looking back, the journey to this point was not smooth as far as I witnessed. When I picked up coding during my days at Macalester College two decades ago, I became fascinated by what computer science could achieve. I remember dreaming of building a massive neural network that would fully automate the operations of a large organisation one day. While I knew such ideas were aspirational at the time, I was struck by how little enthusiasm there was for this technology outside academic research. This was the case even in organisations that took pride in using modelling and analytics to increase value or manage risk. Methods like neural networks were too cumbersome and required too much effort to be practically useful.Who knew that akin to humans, AI simply needed lots of information and time to learn and master something. As computational capability advanced and the amount of digital data increased, AI started to work, unlocking possibilities that were in the realm of science fiction a decade earlier. AI systems are now routinely deciding on the ads you see on a website and recognising your face to log into phone apps. They can help diagnose medical conditions, increase the output of a dairy farm by identifying what makes animals "happier", and park your car. In the energy sector, and electricity in particular, there were several trends that paved the way for AI to be uniquely valuable. Falling costs of renewable energy, ascent of on-site distributed energy, emergence of IoT, and digitalisation of data disrupted the business models built around large centralised supply. The intermittent nature of renewable generation increased price volatility and created challenges in system operations. In this environment, predicting supply, recognising patterns and responding to them rapidly are key to maximising the value our flexible generation assets such as grid-scale batteries. Meanwhile, on the demand side, energy customers have been asking for more insight and control over their energy use. The information they need is available from smart meters and sensors, which are already in their billions and growing rapidly. Centrica alone has sold nearly 2.5 million smart thermostats and other types of sensors under its Hive brand. Harnessing the information from these devices with AI supports us in serving the changing needs of our customers. Our Hive thermostats give our residential energy customers complete control over their energy use. Our Hive Link service combines information from sensors and machine learning to understand the customers' routine over a two-week period and can alert the person caring for them if that routine is broken. Social care is one of the biggest challenges facing economies and we believe this is a good example of where technology has a significant role to play. Our BoilerIQ system predicts boiler failures before they happen and help schedule engineer visits to prevent them, so no one wakes up to a cold house. In the near future, as electric cars become more commonplace, scheduling charging and alternative uses of the car battery will be managed by AI, creating opportunities in Nazim Osmancik
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