Open Access
Issue |
MATEC Web Conf.
Volume 139, 2017
2017 3rd International Conference on Mechanical, Electronic and Information Technology Engineering (ICMITE 2017)
|
|
---|---|---|
Article Number | 00176 | |
Number of page(s) | 4 | |
DOI | https://doi.org/10.1051/matecconf/201713900176 | |
Published online | 05 December 2017 |
- Yao Wei, Cheng Shijie, et al. Application of HVDC technology in grid – connected offshore wind farm CEP, 40 (2007) [Google Scholar]
- Liu Lin, Ge Xu Bo, and so on. China ‘s offshore wind power development status and analysis. ETE, 24(2012) [Google Scholar]
- Wang Jingquan, Cheng Jiansheng, Li Feng. On the construction of offshore wind farms in China. CES, 12(2010) [Google Scholar]
- Yin Yufen. Influence of temperature on regional load characteristics. GEPr, 24(2011) [Google Scholar]
- Li Canbing, Shang Jincheng, Zhu Shouzhen, and so on. Analysis of Energy Consumption Caused by Cumulative Effect of Temperature on Temperature Regulation Load. Power System Automation, 34(2010): 30–33. [Google Scholar]
- KYUNG BS., SEONG KH., JUNG WP., et a1. Hybrid load forecasting method with analysis of temperature sensitivities. IEEE Trans Oil Power Systems, 21(2006):869—876. [CrossRef] [Google Scholar]
- Zhang Limin, Fu Hongjun, Li Yuyan, et al. Estimation of Cooling Load Ratio of Air Conditioning and Its Influence on Voltage Stability. Relays, 33 (2005): 33–36. [Google Scholar]
- TONG Shulin, WEN Fushuan. Calculation and analysis of the annual maximum high-temperature related load in the energy saving and emission reduction environment in Guangdong Province. Journal of North China Electric Power University, 37(2010):32–37. [Google Scholar]
- TAO Yong, SHEN Ying. Influence of summer weather condition on regional air conditioning loads. East ChinaElectric Power, 34(2006):29–30. [Google Scholar]
- Moazzami M, Khodabakhshian A. Hooshmand R. A new hybrid day-ahead peak load forecasting method for Iran’s National Grid. Appl Energy 101(2013):489–501. [CrossRef] [Google Scholar]
- Lawan S, Abidin W, Masri T, Chai W, Baharun A. Wind power generation via ground wind station and topographical feedforward neural network (T-FFNN) model for small-scale applications. Journal Of Cleaner Production 143(2017):1246–1259. [CrossRef] [Google Scholar]
- WANG Jun-tao. Study on Optimized BP Neural Network Algorithm Based on Genetic Algorithm. Small and Medium Enterprises Management and Technology, 4 (2017). [Google Scholar]
- Wang J, Shang L, Chen S, et al. Application of fuzzy classification by evolutionary neural network in incipient fault detection of power transformer. IEEE International Joint Conference on Neural Networks, (2004) [Google Scholar]
- Han Liqun. Artificial neural network theory, design and application. Beijing. Chemical Industry Press. (2007) [Google Scholar]
- Huang NE., Shen Z, Long SR., et al. The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-Stationary Time Series Analysis. Proceedings Mathematical Physical & Engineering Sciences, 454 (1998):903–995. [CrossRef] [Google Scholar]
- Vapnik VN. The nature of statistical learning theory. New York Springer, (1995). [Google Scholar]
- Mukherjee S, Osuna E, Girosi F. Nonlinear prediction of chaotic time series using support vector machines. Proceedings of IEEE NNSP, (1997) [Google Scholar]
- Yan Pingfan, Zhang Changshui. Artificial neural network and simulated evolutionary computation. Beijing: Tsinghua University Press, (2005) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.