Demand response and demand flexibility—shifting demand to intervals where electricity is abundant and cheap, and away from when the grid is constrained or power is expensive and dirty—can help keep prices down, optimize the grid overall, and help us integrate more renewable supply into grid power while displacing more fossil fuels. Until recently, this has mainly meant doing simple things like turning off loads during the on-peak intervals of time of use rates. But now new technologies are coming to the grid, including artificial intelligence, machine learning, and the so-called Internet of Things, which could let us moderate loads and operate grid assets in a much more intelligent, precise, and dynamic fashion, taking grid optimization to a new level and reducing the need for peaking resources.
But this is all quite new, and how we’re going to implement it, and what it may require, largely remains to be seen. In this episode we’ll talk with Sara Bell, founder of Tempus Energy, and get a little insight into how some early pilots of these technologies are working in the UK and South Australia. We’ll also get an inside view of her campaign to revise the design of the capacity market in the UK, so that it actually benefits consumers in accordance with the law, rather than distorting markets in favor of fossil fuel incumbents.
Geek rating: 8
Guest: Sara Bell is the founder and CEO of Tempus Energy, an AI-based platform for demand flexibility. Sara is a Director of the Association of Decentralised Energy, a member of the Scientific Advisory Council for Energy for the Engineering & Physical Sciences Research Council and a member of the High Level Group of i24c, the Industrial Innovation for Competitiveness initiative, a platform dedicated to developing and promoting an industrial strategy that secures European industry’s competitive advantage through innovation. Sara is also an Innovation Ambassador for Innovate UK.
On Twitter: @sarabelltempus
On the Web: https://www.tempusenergy.com/technology/
Recording date: December 16, 2017
Air date: January 10, 2018
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