• Energy Research

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.

With the close of the 117th Congress in January 2023, REPEAT Project has completed a revised, final analysis of the climate and energy system impacts of legislation passed during this landmark session. This includes detailed analysis of the combined impacts of H.R. 5376, the Inflation Reduction Act of 2022 (IRA) and H.R. 3684, the Infrastructure Investment and Jobs Act of 2021 (IIJA). This brief report previews REPEAT Project’s final revised findings on the impact of these laws on the greenhouse gas emissions trajectory of the United States. In this revised analysis, we have updated all assumptions to reflect the latest data available at year-end 20221 and improved the quality of source data and analysis on oil and gas sector methane emissions and abatement opportunities in agriculture and forestry sectors relative to our Preliminary Report on the Inflation Reduction Act released in August, 2022. This revised analysis now includes a range of three Current Policies2 scenarios (‘Conservative’, ‘Mid-range’, and ‘Optimistic’) to better reflect uncertainty about the effectiveness of IRA provisions and the potential impacts of constraints on supply chains and other rate-limiting factors. This report also presents two benchmark scenarios: a Frozen Policies scenario which only reflects policies enacted as of the start of the 117th Congress in January 2021; and a Net-Zero Pathway scenario, which reflects a cost-effective pathway to reduce U.S. greenhouse gas emissions to 50-52% below 2005 levels by 2030 and net-zero by 2050, consistent with President Biden’s climate mitigation goals.

Abstract As decarbonisation agendas mature, macro-energy systems modelling studies have increasingly focused on enhanced decision support methods that move beyond least-cost modelling to improve consideration of additional objectives and tradeoffs. One candidate is modelling to generate alternatives (MGA), which systematically explores new objectives without explicit stakeholder elicitation. This paper provides comparative testing of four existing MGA methodologies and proposes a new Combination vector selection approach. We examine each existing method’s runtime, parallelizability, new solution discovery efficiency, and spatial exploration in lower dimensional (N ⩽ 100) spaces, as well as spatial exploration for all methods in a three-zone, 8760 h capacity expansion model case. To measure convex hull volume expansion, this paper formalizes a computationally tractable high-dimensional volume estimation algorithm. We find random vector provides the broadest exploration of the near-optimal feasible region and variable Min/Max provides the most extreme results, while the two tie on computational speed. The new Combination method provides an advantageous mix of the two. Additional analysis is provided on MGA variable selection, in which we demonstrate MGA problems formulated over generation variables fail to retain cost-optimal dispatch and are thus not reflective of real operations of equivalent hypothetical capacity choices. As such, we recommend future studies utilize a parallelized combined vector approach over the set of capacity variables for best results in computational speed and spatial exploration while retaining optimal dispatch.

This report assesses the role of electricity transmission in enabling the full emissions reduction potential of the Inflation Reduction Act (IRA). Previously, REPEAT Project estimated that IRA could cut U.S. greenhouse gas emissions by roughly one billion tons per year in 2030 and reduce cumulative greenhouse gas emissions by 6.3 billion tons of CO2-equivalent over the decade (2023-2032).1 That outcome depends on more than doubling the historical pace of electricity transmission expansion over the last decade in order to interconnect new renewable resources at sufficient pace and meet growing demand from electric vehicles, heat pumps, and other electrification. While our modeling finds this outcome makes economic sense, current transmission planning, siting, permitting and cost allocation practices can all potentially impede the real-world pace of transmission expansion. We thus model the impact of constrained growth in U.S. electricity transmission on emissions outcomes and the pace of renewable electricity expansion under IRA. Summary of Findings • Failing to accelerate transmission expansion beyond the recent historical pace (~1%/year) increases 2030 U.S. greenhouse emissions by ~800 million tons per year, relative to estimated reductions in an unconstrained IRA case. Emissions are 200 million tons higher if transmission growth is limited to 1.5%/year. • Over 80% of the potential emissions reductions delivered by IRA in 2030 are lost if transmission expansion is constrained to 1%/year, and roughly 25% are lost if growth is limited to 1.5%/year. • To unlock the full emissions reduction potential of the Inflation Reduction Act, the pace of transmission expansion must more than double the rate over the last decade to reach an average of ~2.3%/year. That rate of expansion is comparable to the long-term average rate of transmission additions from 1978-2020. • To achieve IRA’s full emissions reduction potential, new clean electricity must be rapidly added to both meet growing demand from electrification and reduce fossil fuel use in the power sector. Constraining transmission growth severely limits the expansion of wind and solar power. • If electricity transmission cannot be expanded fast enough, power sector emissions and associated pollution and public health impacts could increase significantly as gas and coal-fired power plants produce more to meet growing demand from electric vehicles and other electrification spurred by IRA. • If transmission cannot be expanded faster than recent historical rates (~1%/year), growing demand from electric vehicles and other electrification spurred by IRA results in over 110 million tons of additional coal consumption in 2030 than a No IRA case and roughly 250 million tons more than if transmission expansion is unconstrained. • Expanding transmission more rapidly enables growth of wind and solar power and substantially reduces U.S. natural gas consumption, which falls 17% from 2021 levels in the unconstrained IRA case. In contrast, if transmission expansion is limited to 1%/year, natural gas use increases to 4% above 2021 levels in 2030 and remains elevated through 2035.

This report describes the national-scale energy system and greenhouse gas emissions impacts of the Inflation Reduction Act (IRA, H.R. 5376 as amended), as released by the Senate Democratic Leadership on July 27, 2022 and signed into law on August 16, 2022. The report also reflects prior REPEAT Project analysis of the impacts of the Infrastructure Investment and Jobs Act (IIJA, H.R. 3684), which was signed into law in November 2021, and the Build Back Better Act (BBBA, H.R. 5376), which passed the House of Representatives on November 19, 2021. All results for IRA and BBBA include impacts from enactment of the Bipartisan Infrastructure Law (IIJA). The report also presents two ‘benchmark’ scenarios: Frozen Policies, which captures the impacts of state and federal policies and regulations as of the start of the 117th Congress and inauguration of President Biden in January 2021; and Net-Zero Pathway, a cost-optimized pathway to reduce economy-wide U.S. greenhouse gas emissions 50% below 2005 levels by 2030 and net-zero by 2050. This report contains macro-energy system modeling results including impact on greenhouse gas emissions, a break-down of sectoral reductions, and estimated impacts on U.S. energy expenditures and capital investment in energy supply infrastructure. The report also discusses the impact of variation in future U.S. oil and gas production on U.S. emissions and exports. Given the preliminary nature of this analysis and significant uncertainty about future outcomes, all results in this report should be considered approximate and may be updated or refined by subsequent analysis. This work has not been subject to formal peer review.

As the availability of weather-dependent, zero marginal cost resources such as wind and solar power increases, a variety of flexible electricity loads, or `demand sinks', could be deployed to use intermittently available low-cost electricity to produce valuable outputs. This study provides a general framework to evaluate any potential demand sink technology and understand its viability to be deployed cost-effectively in low-carbon power systems. We use an electricity system optimization model to assess 98 discrete combinations of capital costs and output values that collectively span the range of feasible characteristics of potential demand sink technologies. We find that candidates like hydrogen electrolysis, direct air capture, and flexible electric heating can all achieve significant installed capacity (>10% of system peak load) if lower capital costs are reached in the future. Demand sink technologies significantly increase installed wind and solar capacity while not significantly affecting battery storage, firm generating capacity, or the average cost of electricity.

Abstract Expanding transmission capacity is likely a bottleneck that will restrict variable renewable energy (VRE) deployment required to achieve ambitious emission reduction goals. Interconnection and inter-zonal transmission buildout may be displaced by the optimal sizing of VRE to grid connection capacity and by the co-location of VRE and battery resources behind interconnection. However, neither of these capabilities is commonly captured in macro-energy system models. We develop two new functionalities to explore the substitutability of storage for transmission and the optimal capacity and siting decisions of renewable energy and battery resources through 2030 in the Western Interconnection of the United States. Our findings indicate that modeling optimized interconnection and storage co-location better captures the full value of energy storage and its ability to substitute for transmission. Optimizing interconnection capacity and co-location can reduce total grid connection and shorter-distance transmission capacity expansion on the order of 10% at storage penetration equivalent to 2.5%–10% of peak system demand. The decline in interconnection capacity corresponds with greater ratios of VRE to grid connection capacity (an average of 1.5–1.6 megawatt (MW) PV:1 MW inverter capacity, 1.2–1.3 MW wind:1 MW interconnection). Co-locating storage with VREs also results in a 9%–13% increase in wind capacity, as wind sites tend to require longer and more costly interconnection. Finally, co-located storage exhibits higher value than standalone storage in our model setup (up to ∼43%–45%). Given the coarse representation of transmission networks in our modeling, this outcome likely overstates the real-world importance of storage co-location with VREs. However, it highlights how siting storage in grid-constrained locations can maximize the value of storage and reduce transmission expansion.