no code implementations • 16 Dec 2022 • Rongxing Hu, Kai Ye, Hyeonjin Kim, Hanpyo Lee, Ning Lu, Di wu, PJ Rehm
This paper presents a coordinative demand charge mitigation (DCM) strategy for reducing electricity consumption during system peak periods.
no code implementations • 9 Dec 2022 • Kai Ye, Hyeonjin Kim, Yi Hu, Ning Lu, Di wu, PJ Rehm
This paper presents a modified sequence-to-point (S2P) algorithm for disaggregating the heat, ventilation, and air conditioning (HVAC) load from the total building electricity consumption.
no code implementations • 29 Nov 2022 • Yiyan Li, Lidong Song, Yi Hu, Hanpyo Lee, Di wu, PJ Rehm, Ning Lu
We propose a Generator structure consisting of a coarse network and a fine-tuning network.
no code implementations • 3 Oct 2022 • Yi Hu, Yiyan Li, Lidong Song, Han Pyo Lee, PJ Rehm, Matthew Makdad, Edmond Miller, Ning Lu
This paper presents a deep-learning framework, Multi-load Generative Adversarial Network (MultiLoad-GAN), for generating a group of synthetic load profiles (SLPs) simultaneously.
no code implementations • 1 Oct 2022 • Han Pyo Lee, PJ Rehm, Matthew Makdad, Edmond Miller, Ning Lu
To ensure the credibility of the identification results, utility engineers conduct field verification for all 13 feeders.
no code implementations • 19 Sep 2022 • Hyeonjin Kim, Kai Ye, Han Pyo Lee, Rongxing Hu, Ning Lu, Di wu, PJ Rehm
The residual load profiles are processed using ICA for HVAC load extraction.
no code implementations • 20 Nov 2021 • Han Pyo Lee, Mingzhi Zhang, Mesut Baran, Ning Lu, PJ Rehm, Edmond Miller, Matthew Makdad
To improve the identification accuracy, a data segmentation method is proposed to exclude data segments that are collected when the voltage correlation between smart meters on the same phase are weakened.