Comparison of load models using artificial neural networks and recursive least-squares identification

Dianli Xitong Zidonghue/Automation of Electric Power Systems

Volumn 20, Issue 5, 1996, Pages

  Qiu, Xiaoyan ^a   Li, Xingyuan ^a   Song, Yonghua ^a   Liu, Hongchao ^a   Liu, Junyong ^a  

^a SICHUAN UNIVERSITY   (China)

Author keywords

Artificial neural networks; Load model; Recursive least squares identification

Indexed keywords

EID: 4243186233     PISSN: 10001026     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (10)

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3. IEEE Task Force. Load Representation for Dynamic Performance Analysis. IEEE Trans Power Systems. 1993. 5, 8 (2): 472-482
4. Bai Jianhua, Shen Shande, Gao Jingde. The Identification of Physically Based Power Systems Load Model. Beijing: ICPST' 94, 1994: 681-683
5. Lin L, Chen Y T et al, Chiou C Y. Power Systems Using the Measurement Approach. IEEE Trans on Power Systems, 1993. 2, 8 (1)
6. Sagars V, Nutukki V, Pao D. Artifical Neural Networks and Their Applications to Power Systems - A Bibliographical Survey. Electric Power System Research, 1993, 28: 67-69
7. He Renmu, Germond A. Comparison of Dynamic Load Models Extrapolation Using Neural Networks and Trditional Methods, Proceeding of 3rd International Conference on Neural Networks and Their Application, Japan: 1993. 7
8. Han Xinxiao, He Renmu . Electric Load Modeling Using Selforganizing Neural Network, Beijing: ICPST'94, 1994: 676-680
9. Shen Shande, et al. Artifical Neural Networks for Power System Dynamic Modeling. Beijing: ICPST'94, 1994: 318-321