A Statistical Selection Approach of Dynamic Load Model Parameters
- https://doi.org/10.2991/icmra-15.2015.135How to use a DOI?
- Load model; Time-variation; Multiple linear regression
Since real load characteristics are time-varying all along, load model parameters built on some historical data are only valid within limited scenarios. A real-time dynamic load model parameter selection method based on multiple linear regression (MLR) is proposed to find the load model parameters that are best matched with real time system operation condition from load model parameters history database. And along with the database size growing larger, the load model parameter matching accuracy will become higher and higher. The effectiveness and accuracy of the proposed method are verified on field measurement data collected from a substation in a metropolitan area of China.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yulong Huang AU - Xun Chen PY - 2015/04 DA - 2015/04 TI - A Statistical Selection Approach of Dynamic Load Model Parameters BT - Proceedings of the 3rd International Conference on Mechatronics, Robotics and Automation PB - Atlantis Press SP - 699 EP - 706 SN - 2352-538X UR - https://doi.org/10.2991/icmra-15.2015.135 DO - https://doi.org/10.2991/icmra-15.2015.135 ID - Huang2015/04 ER -