Ever imagined using energy from your own rooftop solar panels to power all your air-conditioning units, heat up water and charge your smartphone? This can now be a reality. In Singapore, smart-enabled HDB flats to be completed in Punggol next year will allow homeowners to track energy consumption via a mobile app, and control just about any appliance that is connected to a power source. By 2040, one billion households and 11 billion smart appliances can actively participate in interconnected electricity systems, allowing these to alter when to draw electricity from the grid, according to the International Energy Agency (IEA). Other demand sectors, such as transport, buildings and industry, are also feeling the effects of a seismic shift in the energy sector.
Earlier this year, Bill Gates, founder of Microsoft and the richest man on Earth, wrote an essay online at "The blog of Bill Gates," to college students graduating worldwide in 2017. One is artificial intelligence (AI). We have only begun to tap into all the ways it will make people's lives more productive and creative. The second is energy, because making it clean, affordable, and reliable will be essential for fighting poverty and climate change." The third field he mentioned was biosciences.
At the beginning of 2016, the world's most sophisticated artificial intelligence (AI) beat World Champion Lee Sedol at a game called'Go' – a chess-like board game with more move combinations than there are atoms in the universe. Before this defeat, Go had been considered too complicated for even the most complex computers to beat the top humans. It was a landmark moment in the development of ever-more sophisticated AI technology. But the future of AI holds more than simply board game victories. It is rapidly finding its way into all aspects of modern life, prompting the promise of a'Fourth Industrial Revolution'.
Editor's Note: This is the first in a four-part series examining the growing role of machine learning and artificial intelligence in the power sector. Tomorrow, we look at how regional grid operators are using AI to optimize operations. The future of the electric grid is undoubtedly cleaner and more efficient and distributed, with hefty doses of technology and machine learning helping to operate it all. But if you're expecting a system dramatically transformed, experts say you'll be left waiting. Artificial intelligence and machine learning are already helping utilities run their networks more efficiently, extending the life of equipment and helping to dispatch energy into markets more efficiently.
Restructuring electricity grids to meet the increased demand caused by the electrification of transport and heating, while making greater use of intermittent renewable energy sources, represents one of the greatest engineering challenges of our day. This modern electricity grid, in which both electricity and information flow in two directions between large numbers of widely distributed suppliers and generators — commonly termed the ‘smart grid’ — represents a radical reengineering of infrastructure which has changed little over the last hundred years. However, the autonomous behaviour expected of the smart grid, its distributed nature, and the existence of multiple stakeholders each with their own incentives and interests, challenges existing engineering approaches. In this challenge paper, we describe why we believe that artificial intelligence, and particularly, the fields of autonomous agents and multi-agent systems are essential for delivering the smart grid as it is envisioned. We present some recent work in this area and describe many of the challenges that still remain.