Tao Sun

All Publications

• Unified 0.25-degree gridded infrastructure-critical extreme weather for the United States from 1979 to 2100. Scientific data Sun, T., Zanocco, C., Flora, J., Sheshadri, A., Rajagopal, R. 2025; 12 (1): 1544

  Abstract

  Extreme weather events can severely disrupt critical infrastructure, triggering cascading effects on power, transportation, and essential services. However, standard weather and climate datasets often lack specialized variables necessary for hazard assessments. We present a unified dataset of infrastructure-critical weather and climate variables across the United States at 0.25° resolution, covering daily or sub-daily intervals from 1979 to 2100. The dataset includes temperature, dew point, wind gusts, precipitation partitioned by rain, snow, and freezing rain or ice pellets, lightning, and wildfire metrics. Historical conditions (1979-2023) are synthesized from observations and reanalysis products, while future projections are derived from 14 CMIP6 global climate models (historical, SSP245, and SSP585 experiments). Physically based and data-driven methods are used to estimate variables not directly provided by existing models. By integrating these variables into a single unified dataset, we enable consistent, high-resolution assessments of weather-related infrastructure risks across past and future periods, supporting wide-ranging applications in energy, transportation, water resources, emergency management, and beyond.

  View details for DOI 10.1038/s41597-025-05918-5

  View details for PubMedID 40940354

  View details for PubMedCentralID 5773887

• Solar and batteries are affordable options for US households NATURE ENERGY Sun, T., Feng, Y., Zanocco, C., Flora, J., Majumdar, A., Rajagopal, R. 2025

  View details for DOI 10.1038/s41560-025-01822-9

  View details for Web of Science ID 001542546800001

• Solar and battery can reduce energy costs and provide affordable outage backup for US households NATURE ENERGY Sun, T., Feng, Y., Zanocco, C., Flora, J., Majumdar, A., Rajagopal, R. 2025

  View details for DOI 10.1038/s41560-025-01821-w

  View details for Web of Science ID 001541701500001

• Mapping the Depths: A Stocktake of Underground Power Distribution in United States Sun, T., Zanocco, C., Floras, J., Rajagopal, R., IEEE IEEE. 2024

  View details for DOI 10.1109/PESGM51994.2024.10688935

  View details for Web of Science ID 001345803901225

• Extreme event counterfactual analysis of electricity consumption in Brazil: Historical impacts and future outlook under climate change ENERGY Zuin, G., Buechler, R., Sun, T., Zanocco, C., Galuppo, F., Veloso, A., Rajagopal, R. 2023; 281

  View details for DOI 10.1016/j.energy.2023.128101

  View details for Web of Science ID 001043761700001

• Cooling-related electricity consumption patterns for small and medium businesses in California: Current impacts and future projections under climate change ENERGY AND BUILDINGS Sun, T., Zanocco, C., Flora, J., Johnson, S., Soto, H. J., Rajagopal, R. 2023; 295

  View details for DOI 10.1016/j.enbuild.2023.113301

  View details for Web of Science ID 001039395600001

• Assessing Californians' awareness of their daily electricity use patterns NATURE ENERGY Zanocco, C., Sun, T., Stelmach, G., Flora, J., Rajagopal, R., Boudet, H. 2022

  View details for DOI 10.1038/s41560-022-01156-w

  View details for Web of Science ID 000898288500001

• The Grid Under Extremes: Pandemic Impacts on California Electricity Consumption IEEE Power and Energy Magazine Bergman, D., Sun, T., Buechler, E., Zanocco, C., Rajagopal, R. 2022; 20 (6): 38-46

  View details for DOI 10.1109/MPE.2022.3199846

• Global Changes in Electricity Consumption During COVID-19. iScience Buechler, E., Powell, S., Sun, T., Astier, N., Zanocco, C., Bolorinos, J., Flora, J., Boudet, H., Rajagopal, R. 2021: 103568

  Abstract

  Understanding how the COVID-19 pandemic has altered electricity consumption can provide insights into society's responses to future shocks and other extreme events. We quantify changes in electricity consumption in 58 different countries/regions around the world from January-October 2020, and examine how those changes relate to government restrictions, health outcomes, GDP, mobility metrics, and electricity sector characteristics in different countries. We cluster the timeseries of electricity consumption changes to identify impact groupings that capture systematic differences in timing, depth of initial changes and recovery rate, revealing substantial heterogeneity. Results show that stricter government restrictions and larger decreases in mobility (particularly retail and recreation) are most tightly linked to decreases in electricity consumption, though these relationships are strongest during the initial phase of the pandemic. We find indications that decreases in electricity consumption relate to pre-pandemic sensitivity to holidays, suggesting a new direction for future research.

  View details for DOI 10.1016/j.isci.2021.103568

  View details for PubMedID 34877481

• On the Dynamics of Distributed Energy Adoption: Equilibrium, Stability, and Limiting Capacity IEEE TRANSACTIONS ON AUTOMATIC CONTROL Sun, T., Tong, L., Feng, D. 2020; 65 (1): 102–14

  View details for DOI 10.1109/TAC.2019.2906723

  View details for Web of Science ID 000506851100008

• Cooperative Game for Carbon Obligation Allocation Among Distribution System Operators to Incentivize the Proliferation of Renewable Energy IEEE TRANSACTIONS ON SMART GRID Zhou, Q., Shahidehpour, M., Sun, T., Feng, D., Yan, M. 2019; 10 (6): 6355–65

  View details for DOI 10.1109/TSG.2019.2903686

  View details for Web of Science ID 000507947800043

• Killing Death Spiral Softly with a Small Connection Charge Sun, T., Tong, L., IEEE IEEE. 2017: 173–79

  View details for Web of Science ID 000428047800024

• The Economic Impact of Electric Vehicle Routing and Charging Strategy on Traffic-Power Integrated Networks Shi, Y., Sun, T., Feng, D., IEEE IEEE. 2017: 453–58

  View details for Web of Science ID 000427164800073

• A Shapley Value Based Method for Allocating Carbon Obligation between Generation Side and Demand Side in Power System Chen, L., Sun, T., Zhou, Q., Feng, D., IEEE IEEE. 2017: 56–60

  View details for Web of Science ID 000427164800009

• Optimal Demand Contracting Strategy Under Uncertainty and Its Implication for Advanced Pricing IEEE TRANSACTIONS ON SMART GRID Feng, D., Sun, T., Fang, C., Shi, Y., Xu, S. 2016; 7 (4): 1876–85

  View details for DOI 10.1109/TSG.2015.2469736

  View details for Web of Science ID 000379696800011

• Directed Graph Based Carbon Flow Tracing for Demand Side Carbon Obligation Allocation Sun, T., Feng, D., Ding, T., Chen, L., You, S., IEEE IEEE. 2016

  View details for Web of Science ID 000399937901218

• Application of Carbon Intensity in Generation Expansion Planning: A Comparative Study Zhou, Q., Sun, T., Ding, T., Feng, D., IEEE IEEE. 2015

  View details for Web of Science ID 000371397503141