Dynamic load modeling of an Egyptian primary distribution system using neural networks-Reference-Cited by-同舟云学术

Dynamic load modeling of an Egyptian primary distribution system using neural networks

Published:2007-11 Issue:9 Volume:29 Page:637-649
ISSN:0142-0615
Container-title:International Journal of Electrical Power & Energy Systems
language:en
Short-container-title:International Journal of Electrical Power & Energy Systems

Author:

Abdelaziz A.Y.,Badr M.A.L.,Younes A.H.

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Reference25 articles.

1. IEEE Task Force Report. Bibliography on load models for power flow and dynamic performance simulation. IEEE Trans Power Syst 1995;10(1):523–538.

2. IEEE Committee Report. System load dynamics-simulation effects on determination of load constants. IEEE Trans 1973;PAS-92(2):600–609.

3. IEEE Task Force Report. Load representation for dynamic performance analysis. IEEE Trans Power Syst 1993:8(2).

4. The application of load models of electric appliances to distribution system analysis;Chen;IEEE Trans Power Syst,1995

5. Varma K, Mathur R, Rogers G, Kundor P. Modeling effects of system frequency variation in long-term stability studies. Paper 95 SM 537-1 PWRS, 1995 IEEE/PES summer meeting, Portland; July 23–27, 1995.

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Processing and Filtering Digital Fault Recorder Events for Load Model Estimation;2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe);2021-10-18

2. Load modeling from smart meter data using neural network methods;2021 22nd IEEE International Conference on Industrial Technology (ICIT);2021-03-10

3. AN EFFECTIVE MODEL FOR CARBON DIOXIDE EMISSIONS PREDICTION: COMPARISON OF ARTIFICIAL NEURAL NETWORKS LEARNING ALGORITHMS;International Journal of Computational Intelligence and Applications;2014-09

4. Average value based model for electrical distribution system load dynamics;International Journal of Electrical Power & Energy Systems;2012-12

5. Evaluation of lightning performance of transmission lines protected by metal oxide surge arresters using artificial intelligence techniques;Energy Systems;2012-06-19