Qingyu Xu

GenX is a highly-configurable, open source electricity resource capacity expansion model that incorporates several state-of-the-art practices in electricity system planning to offer improved decision support for a changing electricity landscape. GenX is a constrained linear or mixed integer linear optimization model that determines the portfolio of electricity generation, storage, transmission, and demand-side resource investments and operational decisions to meet electricity demand in one or more future planning years at lowest cost, while subject to a variety of power system operational constraints, resource availability limits, and other imposed environmental, market design, and policy constraints. GenX features a modular and transparent code structure developed in Julia + JuMP. The model is designed to be highly flexible and configurable for use in a variety of applications from academic research and technology evaluation to public policy and regulatory analysis and resource planning.

Corporations and other organizations procure large amounts of carbon-free electricity and often use these procurements to make claims regarding the carbon intensity of their electricity consumption. Although a claim of carbon-free electricity use implies to the public that an organization’s electricity consumption and procurement practices have a near-zero aggregate impact on climate change, this may not be the case. In fact, multiple proposed emission accounting systems offer different definitions of being “carbon-free.” Here, we explore how the carbon-free procurement strategies associated with several of these accounting systems affect emission outcomes at the entire electricity system level, accounting for changes in operations and installed capacity. We find that the actions incentivized by hourly accounting of carbon-free electricity consumption, including the uptake of advanced clean energy technologies, are most consistently associated with real system-level emission reductions. This study assesses the system-level impacts of carbon-free electricity procurements by voluntary actors in the western United States, accounting for induced changes in both system operations and installed capacities. We find that in the current US policy environment, procurement strategies that match participants’ demand with carbon-free generation on an annual basis have minimal impact on long-run system-level CO2 emissions. Similar outcomes occur when participants calculate their annual emission impacts using short-run marginal emission rates and attempt to offset these with their procurements. In contrast, we find that matching participants’ demand on an hourly basis with carbon-free generation can drive significant reductions in system-level CO2 emissions while incentivizing advanced clean firm generation and long-duration storage technologies that would not otherwise see market uptake. Greater emission impacts are correlated with increased participant costs. We further find that government-imposed clean electricity standards can increase the effectiveness of all forms of voluntary procurement.

The Inflation Reduction Act (IRA) significantly impacts the U.S. energy sector, particularly the PJM Interconnection. It’s projected to increase PJM’s clean electricity to 60% by 2030, up from 48% without the IRA, necessitating faster renewable energy and transmission growth. The IRA could reduce PJM’s CO2 emissions by 37% from 2019/2021 levels, but emissions may rise post-2032 without extended policy support. The Act also lowers electricity costs in PJM. Deeper decarbonization in PJM will require more rapid expansion of low-carbon resources, possibly including advanced technologies like carbon capture and storage (CCS) or long-duration storage by 2035. Implementing a clean electricity standard and CO2 emissions cap and trade could help achieve up to a 90% CO2 reduction by 2035, while maintaining or lowering electricity costs.

This study aims to assess the most cost-effective pathways for New Jersey to achieve 100% carbon-free electricity, in line with its current laws and policy objectives. It explores the potential roles of in-state solar PV, offshore wind, nuclear power, and imported electricity in meeting the state’s future electricity needs. The study provides an independent analysis of the costs and trade-offs associated with different strategies, offering insights for decision-makers. Using the advanced GenX electricity system optimization model, the study plans investment and operational decisions to meet future electricity demand within engineering, reliability, and policy constraints at minimal cost. It models the electricity system of New Jersey, the PJM Interconnection, and neighboring regions, covering 15 zones in total, to evaluate various policy, technology, and fuel price scenarios. The goal is to find feasible options for New Jersey to achieve a completely carbon-free electricity supply by 2050.