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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 991 records · Page 55

Comparing projections of industrial energy demand and greenhouse gas emissions in long-term energy models

The industry sector consumes more energy and emits more greenhouse gas (GHG) emissions than any other end-use sector. Integrated assessment models (IAMs) and energy system models have been widely used to evaluate climate policy at a global level, and include a representation of industrial energy use. In this study, the projected industrial energy use and accompanying GHG emissions, as well as the model structure of multiple long-term energy models are compared. The models show varying degrees to which energy consumption is decoupled from GDP growth in the future. In all models, the sector remains mostly (>50%) reliant on fossil energy through 2100 in a reference scenario (i.e., absent emissions mitigation policies), though there is significant divergence in the projected ability to switch to alternative fuels to mitigate GHG emissions. Among the set analyzed here, the more technologically detailed models tend to have less capacity for switching from fossil fuels to electricity. This highlights the importance of understanding of economy-wide mitigation responses and costs as an area for future improvement. Analyzing industry subsector material and energy use details can improve the ability to interpret results, and provide insight in feasibility of how emissions reduction can be achieved.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Valuing variable renewable energy for peak demand requirements

The capacity credit for a generator is the fraction of its nameplate capacity that can contribute to meeting the system's resource adequacy. However, estimating the capacity credit of variable renewable energy is challenging due to the variability, uncertainty, and spatial diversity of the renewable resources. This study uses the Regional Energy Deployment System to quantify the impacts on the U.S. power sector through 2050 from misestimations of renewable capacity credit. Results show that small underestimates of the renewable capacity credit have little impact on system buildout, but that large underestimates (>50%) can reduce solar photovoltaic deployment by nearly 100 GW (50%) and wind by up to 43 GW (22.8%) in 2030s. Such large differences are possible because the capacity credit for variable renewable energy can substantially impact the overall costs and value of variable renewable energy relative to other technologies. Such effects are most strongly felt in the mid-term but are less relevant over the long-term due to the declining value of variable resources. Underestimating the capacity credit of variable renewable energy leads to increased system costs and emissions. Conversely, overvaluing the capacity credit of variable renewable energy reduces system costs at the risk of lower reliability.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗