Building Energy analysis Tool: developed by Anjie Jiang, master students supervised by Dr. Lu: folder
Smart House Load Disaggregation Tool version 4.0 - Developed by the following PHD students: Ming Liang and Meng Yao under the supervision of Dr. Ning Lu. No-cost licence to Duke Energy. Developed in Matlab at NCSU, it assigns load profiles from load nodes to each building down to selected end use. Based on selected features, the tool can assign 1-year controllable load profile to each load node based on features selected. folder
Feeder Load disaggregation tool - Developed by the following PHD students: by Jiyu Wang under the supervision of Dr. Ning Lu. No-cost licence to Duke Energy. Developed in Matlab at NCSU, it assigns load profiles from feeder top to load nodes. Based on selected features, the tool can assign 1-year load profile to each load node, select the number of buildings on each node based on load composition and load type. Notes, folder, GUI
Distribution volt-var control tool VLSM-based version 1 - Developed by the following PHD students: by Xiangqi Zhu under the supervision of Dr. Ning Lu
Distribution volt-var control tool version 2- Developed by the following PHD students: by David Mulcahy and Catie McEntee under the supervision of Dr. Ning Lu
Mobile microgrid controller - Developed by the following PHD students: Fuhong Xie under the supervision of Dr. Ning Lu
Mode-based Energy Storage Controller for PV-powered microgrid, Henri Gonzague, under the supervision of Dr. Ning LU. Patent pending.
Mobile Microgrid Controller, Fuhong Xie, under the supervision of Dr. Ning LU, Patent Pending.
Residential PV and Energy Storage Sizing Tool, Xiangqi Zhu, under the supervision of Dr. Ning Lu, patent pending.
Resource rewarding methods, Maziar Vanouni, under the supervision of Dr. Ning Lu, patent pending.
A rain-flow based battery lifetime estimation algorithm, Xinda Ke, under the supervision of Dr. Ning Lu. folder
Microgrid Hardware-in-the-loop simulation tool - Developed by the following PHD students: by Long Qian, Fuhong Xie, Hui Yu under the supervision of Dr. Lubkeman,Dr. Ning Lu, and Dr. Srdjan, Lukic, respectively
Technology Diffusion Tools for Electric Vehicle impact study, Lisha Sun, under the supervision of Dr. Lubkeman.
Distributed volt-var control tool, Developed by the following PHD students: Yue Shi, Keith Dsouze, and Valliappan Muthukaruppan under the supervision of Dr. Mesut Baran
OPENDSS code converter: Developed in Python at NCSU, it converts CYME code to OPENDSS code and generates OPENDSS code based on selected load, EV, and PV profiles.
Transmission-Distribution System Co-simulation Platform: This platform runs on OPAL-RT. It is a real-time, hard-ware-in-the-loop, co-simulation platform that can conduct closed-loop testing of power system protection, control, and energy management algorithms. The transmission and distribution network model and data used in the platform are developed based on actual utility data sets including 50+ power distribution feeders in North Carolina area and 15 minutes load profiles from 12,000 smart meter data. The use of the actual feeder data is under Non-disclosure Agreements. The platform is developed together with Total SA and Pacific Northwest National lab. Sine 2016, the team has been working on projects for developing real-time co-simulation technologies funded by Total SA and DOE SETO through the SUNLAMP and ASSIST programs. our industry partners include Total SA, NYPA, Duke Energy, ElectriCities, Wilson Energy, New River Electrical Corporation, and Roanoke Electric Cooperative.
Project website: https://www.researchgate.net/project/Enabling-high-penetration-of-distributed-PV-through-the-optimization-of-sub-transmission-voltage-regulation
Zone-based, Optimization-based, and Machine learning based volt-var control algorithms. Projects funded by ARPA-E. We work with ABB on developing machine-learning based tools for grid edge devices.
Optimiation-based: Catie McEntee.
Meta-learning based load forecasting tool. Projects funded by DOE ASSIST and ARPA-E. Yiyan Li: https://www.youtube.com/watch?v=hiUMqhTXOLM. https://www.youtube.com/watch?v=i8bUvGi9rC8
Detector Site based 2-4 hour ahead PV power fluctuation forecasting tool. Yiyan Li. https://arxiv.org/abs/2111.08809
FeederGan: a GAN-based synthetic feeder and load data generation tool. Project funded by DOE-ASSIST. Ming Liang.
ProfileSR-GAN: a GAN based Super-Resolution Method for Generating High-Resolution Load Profiles, Lidong Song and Yiyan Li. http://arxiv.org/abs/2107.09523,
Flexibility Region Estimation Tool: for estimating the operational flexibility of aggregated Distributed Energy Resources. Mingzhi Zhang. https://arxiv.org/abs/2110.07406.
Data-driven Phase Identification Tool: For estimating smart meter phase using smart meter data as inputs. Hanpyo Lee. http://arxiv.org/abs/2111.10500
ASSIST Platform
Energy management systems by Ashwin, Valli and Rongxing.
Situation Awareness
ProfileSR-GAN: a GAN based Super-Resolution Method for Generating High-Resolution Load Profiles, Lidong Song and Yiyan Li. http://arxiv.org/abs/2107.09523,
Meta-learning based load forecasting tool. Projects funded by DOE ASSIST and ARPA-E. Yiyan Li: https://www.youtube.com/watch?v=hiUMqhTXOLM. https://www.youtube.com/watch?v=i8bUvGi9rC8
FeederGan: a GAN-based synthetic feeder and load data generation tool. Project funded by DOE-ASSIST. Ming Liang.
Detector Site based 2-4 hour ahead PV power fluctuation forecasting tool. Yiyan Li. https://arxiv.org/abs/2111.08809
Review of Low-Voltage Load Forecasting: https://low-voltage-loadforecasting.github.io/
PECAN Street Database: PV and house load profiles
Weather data: NOAA (National Centers for Environmental Information): https://www.ncdc.noaa.gov/cdo-web/
Solar or wind data: from NREL: https://sam.nrel.gov/weather-data.html