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Data Files for Real-Time Energy Disaggregation of a Distribution Feeder's Demand

Creator:

Mathieu, Johanna L, Balzano, Laura, and Ledva, Gregory S

Description:

This data set contains the relevant time series for constructing and testing electricity load models within the related paper. The files within are a '.mat' file that contains the data and a 'readme.txt' file detailing the contents of the data.

Keyword:

Output feedback, Online learning, Machine learning, Real-time filtering, and Energy disaggregation

Discipline:

Engineering
Inferring the behavior of distributed energy resources from incomplete measurements (project outputs)

Creator:

Ledva, Gregory S., Zhe, Du, Peterson, Sarah, Balzano, Laura, and Mathieu, Johanna L.

Description:

This is the code that resulted from NSF grant ECCS-1508943, "Inferring the behavior of distributed energy resources from incomplete measurements." The project focused on developing control, estimation, and modeling methods for residential demand response and electric distribution networks. The talks, papers, and poster in Deep Blue: http://hdl.handle.net/2027.42/149480

Keyword:

online learning, energy disaggregation, residential demand response, networked control, Kalman filter, and frequency regulation

Citation to related publication:

Ledva, Gregory S., Laura Balzano, and Johanna L. Mathieu. "Inferring the behavior of distributed energy resources with online learning." 2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton). IEEE, 2015. https://doi.org/10.1109/ALLERTON.2015.7447003, Ledva, Gregory S., and Johanna L. Mathieu. "A linear approach to manage input delays while supplying frequency regulation using residential loads." 2017 American Control Conference (ACC). IEEE, 2017. https://doi.org/10.23919/ACC.2017.7963041, Ledva, Gregory S., Laura Balzano, and Johanna L. Mathieu. "Exploring Connections Between a Multiple Model Kalman Filter and Dynamic Fixed Share with Applications to Demand Response." 2018 IEEE Conference on Control Technology and Applications (CCTA). IEEE, 2018. https://doi.org/10.1109/CCTA.2018.8511493, Ledva, Gregory S., et al. "Disaggregating Load by Type from Distribution System Measurements in Real Time." Energy Markets and Responsive Grids. Springer, New York, NY, 2018. 413-437. https://doi.org/10.1007/978-1-4939-7822-9_17, Ledva, Gregory S., Sarah Peterson, and Johanna L. Mathieu. "Benchmarking of Aggregate Residential Load Models Used for Demand Response." 2018 IEEE Power & Energy Society General Meeting (PESGM). IEEE, 2018. https://doi.org/10.1109/PESGM.2018.8585847, Ledva, Gregory S., et al. "Managing communication delays and model error in demand response for frequency regulation." IEEE Transactions on Power Systems 33.2 (2018): 1299-1308. https://doi.org/10.1109/TPWRS.2017.2725834, Ledva, Gregory S., Laura Balzano, and Johanna L. Mathieu. "Real-time energy disaggregation of a distribution feeder's demand using online learning." IEEE Transactions on Power Systems 33.5 (2018): 4730-4740. https://doi.org/10.1109/TPWRS.2018.2800535, and Talks, papers, and poster in Deep Blue: http://hdl.handle.net/2027.42/149480

Discipline:

Engineering

Data Files for Real-Time Energy Disaggregation of a Distribution Feeder's Demand

Inferring the behavior of distributed energy resources from incomplete measurements (project outputs)

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Data Files for Real-Time Energy Disaggregation of a Distribution Feeder's Demand

Inferring the behavior of distributed energy resources from incomplete measurements (project outputs)

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