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New Jersey's Pathway to a 100% Carbon-Free Electricity Supply: Policy and Technology Choices Through 2050

Authors: Xu, QIngyu; Patankar, Neha; Zhang, Chuan; Jenkins, Jesse D.;

New Jersey's Pathway to a 100% Carbon-Free Electricity Supply: Policy and Technology Choices Through 2050

Abstract

New Jersey is among a vanguard of states pursuing a transition to a 100% carbon-free electricity system. The goal of this study is to provide a detailed assessment of key policy and technology options and choices and their implications for New Jersey���s pathway to 100% carbon-free electricity. In particular, this study examines least-cost pathways to reach New Jersey���s current laws and stated policy goals under a range of possible future conditions and explores the role of in-state solar PV, offshore wind, nuclear power, and imported electricity in the state���s electricity future. Our goal is to provide an independent assessment of costs and trade-offs associated with different choices facing New Jersey stakeholders provide actionable insights for decision-makers. For this study, we use a state-of-the-art open-source electricity system optimization model, GenX, which plans investment and operational decisions to meet projected future electricity demand while meeting all relevant engineering, reliability, and policy constraints at the lowest cost. We create a detailed model of the electricity system of New Jersey, the PJM Interconnection, and neighboring grid regions (15 total zones, two in NJ, nine in PJM) and explore a range of policy, technology, and fuel price scenarios to assess options for New Jersey to reach a 100% carbon-free electricity supply by 2050. Key Findings: 1. A transition to 100% carbon-free electricity is feasible while maintaining reliability and with reductions in bulk electricity supply costs (-29% to -10% vs. 2019 costs under a least-cost approach). 2. The lowest-cost strategy to reach 100% carbon-free electricity supply entails a significant increase in NJ���s dependence on imported electricity. Imports of wind, solar and other carbon-free resources from out of state are generally more affordable than available in-state resources. 3. Electricity demand could increase significantly (up to +70% total sales and +85% peak demand), and patterns of consumption shift dramatically (from summer afternoon to winter overnight peak demand) due to electrification of vehicles and buildings consistent with NJ economy-wide climate goals. 4. The lowest-cost pathway to 100% carbon-free electricity departs from NJ���s current policy approach, which prioritizes in-state and distributed generation (e.g., solar, offshore wind, nuclear). 5. Import dependence can be reduced by requiring in-state renewable resources and preserving the state���s existing nuclear reactors; the most affordable strategy to prioritize in-state resources increases bulk electricity supply costs by 7-10% relative to the least-cost 100% carbon-free pathway, but still results in costs comparable to or lower than today (-24% to -1% vs 2019). 6. If more states in the region pursue parallel deep decarbonization goals, the costs of reaching 100% carbon-free electricity in NJ increase by 16-20% in 2050, as greater demand for clean electricity across the region drives up import costs and NJ relies more on in-state clean energy resources. Bulk electricity supply costs in 2050 range from -17% to +5% relative to 2019 costs if all states in the region pursue 100% carbon-free electricity.

Correction: This version, published March 26, 2022, corrects an error in the calculation of 2019 New Jersey bulk electricity supply costs used as a benchmark throughout this report. All depictions of 2019 costs and comparisons to this benchmark are updated and corrected in this version.

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Keywords

clean energy, New Jersey, 100% carbon-free electricity, state policy, renewable energy, climate change mitigation, power systems, nuclear power, energy systems, macro-energy systems, energy policy

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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