Evaluating Grid Stress and Reliability under a Range of Future Climate, Emissions, and Socioeconomic Scenarios in the U.S. Western Interconnection
Electricity grids face adaptation challenges due to the interactions between the increasing frequency and severity of extreme events, energy system transitions, and shifts in underlying trends in climate and socioeconomics—all of which affect electricity demand as well as supply resources. Understanding the grid stress (e.g., risks of power outages and/or higher electricity prices) under different possible futures is crucial to inform energy sector decision makers evaluating investments in transmission, storage, generation, and conservation. In this study, we investigate the evolution of grid stress within the U.S. Western Interconnection during the 21st century under eight scenarios of energy system adaptation in response to a wide, yet plausible range of emission pathways (RCP4.5 and RCP8.5), socioeconomic changes (SSP3 and SSP5), and climate modeling uncertainties. We utilize an advanced, iterative, multiscale and multimodel framework to project a feasible set of future electricity demand, renewable energy generation, generator/transmission capacity expansion, and high-resolution generator siting in U.S. Western Interconnection. Hourly grid conditions under these eight scenarios are simulated with the Grid Operations (GO) model, an open-source framework to create customized production cost models that are balanced in computational speed and accuracy. Our results provide insights into how electricity infrastructure and amount of grid stress vary with respect to compounding impacts of climate change, socioeconomic conditions, and energy system pathways. In addition, these results unveil how system reliability and resiliency fluctuate during extreme weather events, especially future heat waves. Overall, this study can help energy system decision-makers and stakeholders in maintaining future grid reliability by detecting possible breaking points early and taking proactive measures.