E3S Web Conf.
Volume 237, 20213rd International Symposium on Architecture Research Frontiers and Ecological Environment (ARFEE 2020)
|Number of page(s)||6|
|Section||Energy Conservation and Emission Reduction, Energy Science|
|Published online||09 February 2021|
- G. Yang. Research on Joint Optimization Decision of Electric Energy Main Market and Auxiliary Service Market[D], SJTU(2011) [Google Scholar]
- G. Huang. Research on the Development Potential of Electric Energy Substitution and Its Economic and Environmental Benefit[D], NCEPU (2019) [Google Scholar]
- X. L. Zhao, M. Wang, Y. Zhao, Q. B. Wu. Improved model of compensation mechanism for peak shaving auxiliary service based on capacity difference of thermal power units[J]. Automat Electron Power Sys. 04:57-61 (2013) [Google Scholar]
- H. P. Zhang, D. B. Gao, J. N. Zhang, Z. Xu. The Development Road of Northeast Electric Power Peak Shaving Auxiliary Service Market[J]. China Power Enterprise Management, 28:26-29 (2018). [Google Scholar]
- Y. S. Zhang, J. Zhang, T. T. Feng. Research on the Economic Compensation Mechanism of China’s Nuclear Power Plants’ Peak Shaving Auxiliary Service[J]. Power Syst Technol. 07:2131-2138 (2017) [Google Scholar]
- Y. H. He, M. Zhou, Z. Y. Long, J. Xu. The operation mode of typical foreign electricity balance market and its enlightenment to China[J]. Power Sys Techno. 11:3520-3528 (2018) [Google Scholar]
- L. Qi, B. Cheng, R. Zhao, X. J. Gao. Cost and benefit analysis of providing peak shaving auxiliary services for coal-fired thermal power units[J]. Power Syst and Big Data, 10:23-29 (2019) [Google Scholar]
- P. S. Dai. Research on the Price Formation Mechanism of China’s Electricity Market[D]. XMU (2004) [Google Scholar]
- F. Xu, C. Q. Ge, X. Wu, M. J. Zhu, M. F. Tu. The market mechanism and clearing model of peak shaving auxiliary services in regional power grids[J], Automat Electron Power Sys. 16:109-120 (2019). [Google Scholar]
- J. F. hu. Research on Cost Allocation Mechanism and Model of Auxiliary Services for Wind Power Access[D]. NCEPU (2014) [Google Scholar]
- Xing Y, Nurul A. Chowdhury. Mid-term electricity market clearing price forecasting: A multiple SVM approach[J]. Int J Electr Power Energy Syst. 58(2014). [Google Scholar]
- Xing Yan, Nurul A. Chowdhury. Mid-term electricity market clearing price forecasting utilizing hybrid support vector machine and auto-regressive moving average with external input[J]. Int J Electr Power Energy Syst. 63(2014). [Google Scholar]
- Zhang JL, Tan ZF. Day-ahead electricity price forecasting using WT, CLSSVM and EGARCH model. Int J Electr Power Energy Syst. 45:362–8 (2013). [Google Scholar]
- X. C. Liu, J. Shen, Y. G. Li. A Generalized Auto-Re gressive Conditional Heteroscedasticity Model fo r System Marginal Price Forecasting Based on Weighted Double Gaussian Distribution[J]. Pow-e r Sys Techno, 1:139-144 (2010). [Google Scholar]
- Q. Wei, S. J. Cheng, W. B. Huang, G. W. Ma, C. H. Tao. Fo recasting method of spot market clearing price based on random forest regression, Proc Chin Soc Electrical Eng, 1-10 (2020). [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.