The electricity industry is now undergoing a dramatic transformation as computerization is being driven down to the home level through smart meters and smart home technologies. Smart meters enable consumers to more informatively control and manage their energy consumption, and they give retail energy providers the ability to do real-time pricing and interrupt consumers individually. Currently, retailers face electricity prices which change instantaneously with wholesale markets, but consumers see fixed rates that do not change over time in the short run. The main objective of this work is to investigate the conditions under which dynamic pricing to smart homes can improve social welfare, the magnitude of these improvements, and their sensitivity to home characteristics. / We develop a mathematical framework for a smart home's optimal dynamic response to dynamic price signals. We view the home as an energy system which we decompose by consumption category and appliance. We provide the first models for price-responsive, occupant-aware appliances. We propose approaches to estimate the utility function for thermal comfort. We also prove structural policy results. / We also provide a hierarchical pricing methodology for an electricity utility which sends price signals to homes, which in turn prices to appliances. Starting with first principles, we show that under certain conditions it is socially optimal for the electricity utility to pass through spot prices to the customers. We also provide a methodology to simulate a real-sized city. / Finally, we present extensive numerical results on ComEd's residential customers' responses to dynamic prices through air conditioners during a summer month. Our results suggest that dynamic prices reduce the power bills significantly and even more so with price-responsive appliances. On the other hand, it increases the power bills significantly on peak days while price-responsive air conditioners mitigate these bill increases. Overall, the social welfare may increase up to 2.6% for the month and up to 6.8% on a peak day. We discuss future directions for further exploring the benefits of smart homes and pricing.
| Identifer | oai:union.ndltd.org:CHENGCHI/U0003499776 |
| Creators | Uckun, Canan. |
| Publisher | The University of Chicago. |
| Source Sets | National Chengchi University Libraries |
| Detected Language | English |
| Type | text |
| Rights | Copyright © nccu library on behalf of the copyright holders |
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