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      Using temperature sensitivity to estimate shiftable electricity demand

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          Summary

          The growth of intermittent renewable energy and climate change makes it increasingly difficult to manage electricity demand variability. Centralized storage can help but is costly. An alternative is to shift demand. Cooling and heating demands are substantial and can be economically shifted using thermal storage. To estimate what thermal storage, employed at a scale, might due to reshape electricity loads, we pair fine-scale weather data with hourly electricity use to estimate the share of temperature-sensitive demand across 31 regions that span the continental United States. We then show how much variability can be reduced by shifting temperature-sensitive loads, with and without improved transmission between regions. We find that approximately three-quarters of within-day, within-region demand variability can be eliminated by shifting just half of temperature-sensitive demand. The variability-reducing benefits of shifting temperature-sensitive demand complement those gained from the improved interregional transmission, and greatly mitigate the challenge of serving higher peaks under climate change.

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          Highlights

          • Using thermal storage, HVAC-related energy demand can be shifted in time

          • We estimate the large-scale potential of such shifts on the U.S. electricity system

          • HVAC loads are identified by linking hourly electricity demand to fine-scale weather

          • Shifting half of estimated HVAC demand reduces daily variability by 75 percent

          Abstract

          Energy resources; Energy policy; Energy management; Energy Modeling.

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          Most cited references26

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          A summary of demand response in electricity markets

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            Climate change is projected to have severe impacts on the frequency and intensity of peak electricity demand across the United States

            The existing empirical literature on the impacts of climate change on the electricity sector has focused on changing electricity consumption patterns. In this paper, we show that incorporating impacts on the frequency and intensity of peak load consumption during hot days implies sizable required investments in peak generating capacity (or major advances in storage technology or the structure of electricity prices), which results in substantially larger impacts than those from just changes in overall consumption. It has been suggested that climate change impacts on the electric sector will account for the majority of global economic damages by the end of the current century and beyond [Rose S, et al. (2014) Understanding the Social Cost of Carbon: A Technical Assessment ]. The empirical literature has shown significant increases in climate-driven impacts on overall consumption, yet has not focused on the cost implications of the increased intensity and frequency of extreme events driving peak demand, which is the highest load observed in a period. We use comprehensive, high-frequency data at the level of load balancing authorities to parameterize the relationship between average or peak electricity demand and temperature for a major economy. Using statistical models, we analyze multiyear data from 166 load balancing authorities in the United States. We couple the estimated temperature response functions for total daily consumption and daily peak load with 18 downscaled global climate models (GCMs) to simulate climate change-driven impacts on both outcomes. We show moderate and heterogeneous changes in consumption, with an average increase of 2.8% by end of century. The results of our peak load simulations, however, suggest significant increases in the intensity and frequency of peak events throughout the United States, assuming today’s technology and electricity market fundamentals. As the electricity grid is built to endure maximum load, our findings have significant implications for the construction of costly peak generating capacity, suggesting additional peak capacity costs of up to 180 billion dollars by the end of the century under business-as-usual.
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              Knowledge is (Less) Power: Experimental Evidence from Residential Energy Use

                Author and article information

                Contributors
                Journal
                iScience
                iScience
                iScience
                Elsevier
                2589-0042
                17 August 2022
                16 September 2022
                17 August 2022
                : 25
                : 9
                : 104940
                Affiliations
                [1 ]Department of Economics, University of Hawai’i at Mānoa, 2424 Maile Way, Saunders 542, Honolulu, HI 96822, USA
                [2 ]University of Hawai’i Economic Research Organization (UHERO), Honolulu, HI 96822, USA
                [3 ]University of Hawai’i Sea Grant College Program, Honolulu, HI 96822, USA
                [4 ]Department of Electrical Engineering, University of Hawai’i at Mānoa, Honolulu, HI 96822, USA
                [5 ]Northern Virginia Electric Cooperative, Manassas, VA 20109, USA
                Author notes
                []Corresponding author mjrobert@ 123456hawaii.edu
                [6]

                Lead contact

                Article
                S2589-0042(22)01212-3 104940
                10.1016/j.isci.2022.104940
                9450160
                0a429545-cedc-43c9-96f9-f5b1b3e094aa
                © 2022 The Authors.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 22 December 2021
                : 13 June 2022
                : 11 August 2022
                Categories
                Article

                energy resources,energy policy,energy management,energy modeling

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