Abstract
Accurate load models are critical for power system analysis and operation. A large amount of research work has been done on load modeling. Most of the existing research focuses on developing load models, while little has been done on developing formal load model verification and validation (V&V) methodologies or procedures. Most of the existing load model validation is based on qualitative rather than quantitative analysis. In addition, not all aspects of model V&V problem have been addressed by the existing approaches. To complement the existing methods, this paper proposes a novel load model verification and validation framework that can systematically and more comprehensively examine load model’s effectiveness and accuracy. Statistical analysis, instead of visual check, quantifies the load model’s accuracy, and provides a confidence level of the developed load model for model users. The analysis results can also be used to calibrate load models. The proposed framework can be used as a guidance to systematically examine load models for utility engineers and researchers. The proposed method is demonstrated through analysis of field measurements collected from a utility system.
Document Type
Article
Publication Date
11-22-2017
Digital Object Identifier (DOI)
https://doi.org/10.1515/ijeeps-2017-0070
Repository Citation
Jiao, Xiangqing; Liao, Yuan; and Nguyen, Thai, "Load Model Verification, Validation and Calibration Framework by Statistical Analysis on Field Data" (2017). Electrical and Computer Engineering Faculty Publications. 18.
https://uknowledge.uky.edu/ece_facpub/18
Notes/Citation Information
Published in International Journal of Emerging Electric Power Systems, v. 18, issue 6, 20170070, p. 1-7.
© 2017 Walter de Gruyter GmbH, Berlin/Boston.
The copyright holder has granted the permission for posting the article here.