Qian Luo

Climate change is expected to increase the severity of hurricanes and tropical storms, posing significant risks to the electricity grid. These include downed power lines, damaged solar panels, and impaired wind turbines from high winds. New York (NY) and New Jersey (NJ) are not spared from these vulnerabilities and must strengthen their infrastructure and mitigate social and technical impacts. Clean energy mandates, such as NJ’s Executive Orders No. 315 and 307 (100% clean energy by 2035 and 11 GW of offshore wind by 2040), and NY’s Executive Order No. 166 (40% emissions reduction by 2030), add urgency to ensuring grid resilience under extreme weather. This study demonstrates the Power System Cyclone Impact Model (PCIM), used alongside the GenX electricity system planning tool, to assess grid resilience under hurricane-induced high wind speeds in the NY and NJ region. Results reveal that onshore and offshore wind could contribute additional power during storms, provided transmission and storage systems remain operational. This output helps offset outages elsewhere in the grid across all storm categories. In contrast, solar emerges as a vulnerability due to combined impacts from wind stress and cloud cover, significantly reducing generation during and after storms. Thermal generators show the lowest failure rates, though this may partly reflect current model limitations, as only wind stress and cloud cover are considered, excluding hazards like flooding. Non-served energy costs vary with electricity demand and fluctuations in wind and solar output. July stands out as the most vulnerable month, due to high demand and limited wind generation, leading to higher NSE. This research provides a first step toward understanding storm-related grid resilience in NJ and NY. The PCIM model is designed to be generalizable, with future work focused on expanding its scope to include additional hazards like storm surge and flooding, and more storm-prone regions.  

While electrifying transportation eliminates tailpipe greenhouse gas (GHG) emissions, electric vehicle (EV) adoption can create additional electricity sector emissions. To quantify this emissions impact, prior work typically employs short-run marginal emissions or average emissions rates calculated from historical data or power systems models that do not consider changes in installed capacity. In this work, we use an electricity system capacity expansion model to consider the full consequential GHG emissions impact from large-scale EV adoption in the western United States, accounting for induced changes in generation and storage capacity. We find that the metrics described above do not accurately reflect the true emissions impact of EV adoption–average emissions rates can either under- or over-estimate emission impacts, and short-run marginal emissions rates can significantly underestimate emission reductions, especially when charging timing is flexible. Our results also show that using short-run marginal emission rates as signals to coordinate EV charging could increase emissions relative to price-based charging signals, indicating the need for alternative control strategies to minimize consequential emissions.

Targeting one of the largest CO2-emitting sectors, the US Environmental Protection Agency (EPA) finalized new regulations on power plant emissions in 2024. However, the regulations are complex, with multiple mitigation options for compliance, making it difficult to understand their consequential effects on total CO2 emissions. We evaluate these effects by enhancing a capacity expansion model via incorporating new detailed operational constraints tailored to different technologies based on the EPA’s new rules. We show that the new rules could nearly double power sector CO2 emissions reductions through 2040, bringing emissions to about 51% below the 2022 level at low average cost per ton avoided, driven primarily by coal retirements. However, the rules omit regulations on existing natural gas generators, encouraging greater use of inefficient older gas plants. We find that emissions could be cost-effectively driven to 81%–88% below 2022 levels if the EPA’s rules were applied equally to all gas generators, regardless of vintage.

The US Inflation Reduction Act (IRA) subsidizes the deployment of clean electricity, hydrogen production, and carbon capture and storage (CCS), which could enable additional actions by other federal, state, and local policy-makers to reduce emissions. Power plant rules finalized by the Environmental Protection Agency (EPA) in 2024 are one such example of complementary policies. The rules establish emissions intensity standards, not technology mandates, meaning power plant owners can choose from a range of technologies and control options provided that emissions standards are met. This flexibility makes electricity systems modeling important to understand the potential effects of these regulations. We report below a multimodel analysis of the EPA power plant rules that can provide timely information, including for other countries and states, on emissions impacts, policy design for electricity decarbonization, power sector investments and retirements, cost impacts, and load growth. We also discuss related technical, political, and legal uncertainties.