| HVAC load Disaggregation using Low-resolution Smart Meter Data M Liang, Y Meng, N Lu, D Lubkeman, A Kling 2019 IEEE Power & Energy Society Innovative Smart Grid Technologies …, 2019 | 34 | 2019 |
| FeederGAN: Synthetic feeder generation via deep graph adversarial nets M Liang, Y Meng, J Wang, DL Lubkeman, N Lu IEEE Transactions on Smart Grid 12 (2), 1163-1173, 2020 | 20 | 2020 |
| Kernel-based electric vehicle charging load modeling with improved latin hypercube sampling M Liang, W Li, J Yu, L Shi 2015 IEEE Power & Energy Society General Meeting, 1-5, 2015 | 16 | 2015 |
| A Data-Driven Pivot-Point-Based Time-Series Feeder Load Disaggregation Method J Wang, X Zhu, M Liang, Y Meng, A Kling, DL Lubkeman, N Lu IEEE Transactions on Smart Grid 11 (6), 5396-5406, 2020 | 14 | 2020 |
| Design of Energy Storage Friendly Regulation Signals using Empirical Mode Decomposition Y Meng, M Liang, JF DeCarolis, N Lu 2019 IEEE Power & Energy Society General Meeting (PESGM), 1-5, 2019 | 10 | 2019 |
| A Cost Benefit Study of using Energy Storage to Provide Regulation Services Y Meng, M Liang, N Lu 2019 IEEE Power & Energy Society Innovative Smart Grid Technologies …, 2019 | 5 | 2019 |
| Impacts of Zero Net Energy Buildings on Customer Energy Savings and Distribution System Planning M Liang, J Wang, Y Meng, N Lu, D Lubkeman, A Kling 2019 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), 2561-2565, 2019 | 4 | 2019 |
| A Machine Learning-Based Approach for Synthetic Distribution Feeder Generation M Liang North Carolina State University, 2020 | | 2020 |
Ning LuNorth Carolina State UniversityVerified email at ncsu.edu
