Electric water heaters [chapter]

Geoffrey Burdett
1987 The Newnes Guide to Home Electrics  
The increased penetration of renewable energy sources poses new challenges for grid stability. The stochastic and uncontrollable generation of solar and wind power cannot be adjusted to match the load profile, and the transition away from traditional synchronous generators is reducing the grid capacity to arrest and recover from frequency disturbances. Additionally, the distributed nature of many renewable energy sources makes centralized control of generation more complicated. The traditional
more » ... d. The traditional power system paradigm balances the supply and demand of electricity on the grid by regulating generation. As this becomes more difficult, one alternative is to adjust the load instead. This is not entirely novel, and utilities have incentivized large industrial customers to reduce consumption during peak hours for years. However, the residential sector, which constitutes 37% of electricity consumption in the U.S., currently has very little capacity for load control. Smart electric water heaters provide utilities with an appliance that can be remotely controlled and serves as a form of energy storage. They have very fast response times and make up a large amount of residential energy consumption, making them useful for load peak shifting as well as other ancillary grid services. As smart appliances become increasingly widespread, more and more devices can be brought into the utility's control network and aggregated into a flexible resource on a megawatt scale. i This work demonstrates the usefulness of aggregated electric water heaters for peak shifting and frequency response. Because a large number of assets are required, emulators are developed based on observations of real devices. Emulated water heaters are then connected to an energy resource aggregator using an internet-of-things network. The aggregator successfully uses these assets to shift consumption away from peak hours. An algorithm was developed for detecting upward frequency disturbances in real-time. The aggregator uses this algorithm to show that an aggregation of water heaters is well-suited to respond to these frequency disturbances by quickly adding a large amount of load to the grid. ii Dedication To T.A.C. iii Acknowledgements Special thanks to Tylor Slay for being the MVP. You are a rare gem of a scientist and a person, and this work wouldn't have been possible without you. Thank you Bob Bass for being a great teacher, boss, and advisor, and for giving me the opportunity to be a part of this team. And, of course, thanks to Kevin and Yuki for putting up with me for the last two years. Thank you to Conrad Eustis, Kevin Whitener, and PGE for supporting this research and providing me access to the SSPC data. I'd also like to thank my mom for always being there for me, Jim Houck for giving me a place to live, and all of the friends near and far who didn't give up on me even when I disappeared from their lives for years at a time. Finally, thank you Hong Lei and Richard Campbell for joining my thesis committee. I respect and appreciate the time and effort you have committed to my studies. iv Contents Abstract i Dedication iii Acknowledgements iv
doi:10.1016/b978-0-434-90199-9.50012-0 fatcat:td736osgsrhlfbzfvavw5k2k2y