A parameter identification method of power grid load model based on edge computing in IoT environment-Reference-Cited by-同舟云学术

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A parameter identification method of power grid load model based on edge computing in IoT environment

Published:2021-01-03 Issue: Volume: Page:
ISSN:1868-5137
Container-title:Journal of Ambient Intelligence and Humanized Computing
language:en
Short-container-title:J Ambient Intell Human Comput

Author:

Xiao Jun,Situ You,Yuan Weideng,Feng Bo

Funder

Science and Technology Project of Dongguan Power Supply Bureau of Guangdong Power Grid Co., Ltd

Publisher

Springer Science and Business Media LLC

Subject

General Computer Science

Link

http://link.springer.com/content/pdf/10.1007/s12652-020-02717-1.pdf

Reference24 articles.

1. Canyurt OE (2017) Three different applications of genetic algorithm search techniques on oil demand estimation. Energy Convers Manag 21:69–73. https://doi.org/10.1016/j.enconman.2006.03.009

2. Canyurt OE, Ozturk HK (2018) Application of genetic algorithm technique on demand estimation of fossil fuels in Turkey. Energy Pol 25:211–226. https://doi.org/10.1016/j.enpol.2008.03.010

3. Canyurt OE, Ozturk HK, Hepbasli A (2016) Estimating the Turkish residential - commercial energy output based on genetic algorithm approaches. Energy Pol 45:1011–1019. https://doi.org/10.1016/j.enpol.2003.11.001

4. Carolin SP, Somasundaram M (2016) Data loss protection and data security using agents for cloud environment. In: 2016 International conference on computing technologies and intelligent data engineering (ICCTIDE), IEEE. https://doi.org/10.1109/ICCTIDE.2016.7725349

5. Dan H, Ma J, He RM (2018) A real application of measurement based load modeling in large-scale power grids and its validation. IEEE Trans Power Syst 24:1756–1764. https://doi.org/10.1109/TPWRS.2009.2030298

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