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Title: Data centers as dispatchable loads to harness stranded power

Abstract

Here, we analyze how traditional data center placement and optimal placement of dispatchable data centers affect power grid efficiency. We use detailed network models, stochastic optimization formulations, and diverse renewable generation scenarios to perform our analysis. Our results reveal that significant spillage and stranded power will persist in power grids as wind power levels are increased. A counter-intuitive finding is that collocating data centers with inflexible loads next to wind farms has limited impacts on renewable portfolio standard (RPS) goals because it provides limited system-level flexibility. Such an approach can, in fact, increase stranded power and fossil-fueled generation. In contrast, optimally placing data centers that are dispatchable provides system-wide flexibility, reduces stranded power, and improves efficiency. In short, optimally placed dispatchable computing loads can enable better scaling to high RPS. In our case study, we find that these dispatchable computing loads are powered to 60-80% of their requested capacity, indicating that there are significant economic incentives provided by stranded power.

Authors:
 [1];  [2];  [3];  [2]
  1. Argonne National Lab. (ANL), Lemont, IL (United States)
  2. Univ. of Chicago, Chicago, IL (United States)
  3. Univ. of Wisconsin, Madison, WI (United States)
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
National Science Foundation (NSF); USDOE Office of Science (SC)
OSTI Identifier:
1366452
Grant/Contract Number:
AC02-06CH11357
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
IEEE Transactions on Sustainable Energy
Additional Journal Information:
Journal Volume: 8; Journal Issue: 1; Journal ID: ISSN 1949-3029
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; cloud computing; energy markets; green computing; power grid; renewable portfolio standard (RPS); renewable power

Citation Formats

Kim, Kibaek, Yang, Fan, Zavala, Victor M., and Chien, Andrew A.. Data centers as dispatchable loads to harness stranded power. United States: N. p., 2016. Web. doi:10.1109/TSTE.2016.2593607.
Kim, Kibaek, Yang, Fan, Zavala, Victor M., & Chien, Andrew A.. Data centers as dispatchable loads to harness stranded power. United States. doi:10.1109/TSTE.2016.2593607.
Kim, Kibaek, Yang, Fan, Zavala, Victor M., and Chien, Andrew A.. 2016. "Data centers as dispatchable loads to harness stranded power". United States. doi:10.1109/TSTE.2016.2593607. https://www.osti.gov/servlets/purl/1366452.
@article{osti_1366452,
title = {Data centers as dispatchable loads to harness stranded power},
author = {Kim, Kibaek and Yang, Fan and Zavala, Victor M. and Chien, Andrew A.},
abstractNote = {Here, we analyze how traditional data center placement and optimal placement of dispatchable data centers affect power grid efficiency. We use detailed network models, stochastic optimization formulations, and diverse renewable generation scenarios to perform our analysis. Our results reveal that significant spillage and stranded power will persist in power grids as wind power levels are increased. A counter-intuitive finding is that collocating data centers with inflexible loads next to wind farms has limited impacts on renewable portfolio standard (RPS) goals because it provides limited system-level flexibility. Such an approach can, in fact, increase stranded power and fossil-fueled generation. In contrast, optimally placing data centers that are dispatchable provides system-wide flexibility, reduces stranded power, and improves efficiency. In short, optimally placed dispatchable computing loads can enable better scaling to high RPS. In our case study, we find that these dispatchable computing loads are powered to 60-80% of their requested capacity, indicating that there are significant economic incentives provided by stranded power.},
doi = {10.1109/TSTE.2016.2593607},
journal = {IEEE Transactions on Sustainable Energy},
number = 1,
volume = 8,
place = {United States},
year = 2016,
month = 7
}

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