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Reducing our reliance on carbon-intensive energy sources is vital for reducing the carbon footprint of the electric grid. Although the grid is seeing increasing deployments of clean, renewable sources of energy, a significant portion of the grid demand is still met using traditional carbon-intensive energy sources. In this paper, we study the problem of using energy storage deployed in the grid to reduce the grid's carbon emissions. While energy storage has previously been used for grid optimizations such as peak shaving and smoothing intermittent sources, our insight is to use distributed storage to enable utilities to reduce their reliance on their less efficient and most carbon-intensive power plants and thereby reduce their overall emission footprint. We formulate the problem of emission-aware scheduling of distributed energy storage as an optimization problem, and use a robust optimization approach that is well-suited for handling the uncertainty in load predictions, especially in the presence of intermittent renewables such as solar and wind. We evaluate our approach using a state of the art neural network load forecasting technique and real load traces from a distribution grid with 1,341 homes. Our results show a reduction of >0.5 million kg in annual carbon emissions --- equivalent to a drop of 23.3% in our electric grid emissions.
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Data Center Environmental Burden Reduction Through On-Site Renewable Power Generation
Abstract The energy demands from data centers contribute greatly to water scarcity footprint and carbon emissions. Understanding the use of on-site renewable power generation is an important step to gain insight into making data centers more sustainable. This novel study examines the impact of on-site solar or wind energy on data center water scarcity usage effectiveness (WSUE) and carbon usage effectiveness (CUE) at a U.S. county scale for a given data center size, water consumption level, and energy efficiency. The analysis uncovers combinations of specific metrics associated with grid-based carbon emissions and water scarcity footprint that enable predictions of the improvements anticipated when implementing on-site solar or wind energy. The implementation of on-site renewables has the most benefit in reducing carbon footprint in areas with high existing grid-based emissions such as the western side of the Appalachian Mountains (e.g., central and eastern Kentucky). The largest benefit in reducing water scarcity footprint is generally seen in counties with low water scarcity compared to adjacent areas (e.g., northern California).
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- Award ID(s):
- 2209691
- PAR ID:
- 10537553
- Publisher / Repository:
- ASME
- Date Published:
- Journal Name:
- ASME Journal of Engineering for Sustainable Buildings and Cities
- Volume:
- 5
- Issue:
- 2
- ISSN:
- 2642-6641
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1115/1.4065053
