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Disaggregation for Networked Power Systems

Anderson, James and Zhou, Fengyu and Low, Steven H. (2018) Disaggregation for Networked Power Systems. In: 2018 Power Systems Computation Conference (PSCC). IEEE , Piscataway, NJ, pp. 1-7. ISBN 978-1-910963-10-4.

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Electricity data such as supply, demand, prices, and line flows, are sensitive. Utility companies, understandably do not want to, in fact often cannot, make this data publicly available. However, such data is critical in many fundamental areas in power systems research. As a compromise, aggregated data sets are sometimes made available. In such a setting it may be the case that data is aggregated over a geographical region and time. This forces researchers to try and “invert” the data to obtain dis aggregated data sets. In this paper we rigorously formulate the disaggregation problem for networked power systems and present two algorithms that provide solutions to the DC version of the problem. We show that it is possible to invert the data, but that does not imply that ground truth solutions are obtained, thus the utility companies maintain a notion of privacy. The aim of this paper is to highlight the potential benefits to both the research community and utility companies of releasing aggregated data.

Item Type:Book Section
Related URLs:
URLURL TypeDescription
Anderson, James0000-0002-2832-8396
Zhou, Fengyu0000-0002-2639-6491
Low, Steven H.0000-0001-6476-3048
Additional Information:© 2018 IEEE. This work is supported the ARPA-E GRID-DATA program and grant DE-AR0000699, with partial support from NSF grants CCF 1637598, ECCS 1619352, CNS 1545096, and DTRA through grant HDTRA 1-15-1-0003.
Funding AgencyGrant Number
Advanced Research Projects Agency-Energy (ARPA-E)DE-AR0000699
Defense Threat Reduction Agency (DTRA)HDTRA 1-15-1-0003
Record Number:CaltechAUTHORS:20181102-085439162
Persistent URL:
Official Citation:J. Anderson, F. Zhou and S. H. Low, "Disaggregation for Networked Power Systems," 2018 Power Systems Computation Conference (PSCC), Dublin, 2018, pp. 1-7. doi: 10.23919/PSCC.2018.8442521
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:90607
Deposited By: Tony Diaz
Deposited On:02 Nov 2018 16:30
Last Modified:16 Nov 2021 03:34

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