Title:   Using Temperature Sensitivity to Estimate Shiftable Electricity Demand

Speaker： Michael Roberts, University of Hawaii

Time：  9: 00 - 10:30, 8 June, 2021 (Beijing Time, GMT+8)

Mode：Online   

About the speaker:

Michael Roberts is a Professor in the Department of Economics, University of Hawaii Economic Research Organization (UHERO), and Sea Grant at the University of Hawaii at Mānoa. He has conducted research on effects of agricultural policies, impacts of climate change on agriculture, commodity pricing, energy efficiency standards, and renewable energy integration. He served on editorial boards for leading agricultural, environmental and resource economics journals, and is currently a Co-Editor at the Journal of Association of Environmental and Resource Economics. Before moving to Hawaii, he was an Assistant and then Associate Professor at North Carolina State University and worked for a number of years at USDA’s Economic Research Service. He has an undergraduate degree from UC San Diego, an MS from Montana State University, and MA and PhD degrees from UC Berkeley.

Abstract:

Growth of intermittent renewable energy and climate change make it increasingly difficult to manage electricity demand variability. On a levelized basis, wind and solar photovolatic (PV) are now the least costly sources of power, but have output that fluctuates with weather and sunlight. As a result, demand net of renewable supply is more variable than demand itself. At the same time, climate change is increasing peak demand for cooling on hot summer days. Transmission, batteries, pumped-water hydroelectric systems, hydrogen, and other storage methods can help to smooth net demand, but these are costly. An alternative to these balancing technologies is to make better use of shiftable demand, but it is unclear how much shiftable demand exists. A significant share of electricity demand is used for cooling and heating, and low-cost technologies exists to shift these loads. With sufficient insulation, energy used for air conditioning and space and water heating can be stored in ice or hot water from hours to days. In this study, we combine regional hourly demand with fine-grained weather data across the United States to estimate temperature-sensitive demand, and how much demand variability can be reduced by shifting temperature-sensitive loads. We find that approximately three quarters of within-day demand variability can be eliminated by shifting only half of temperature-sensitive demand. The variability-reducing benefits of employing available shiftable demand are much greater than those from improved interregional transmission and mitigate the challenge of serving higher peaks under climate change. We discuss likely implications for the cost of high-renewable power-systems and near-term investments.

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