Market clearing price forecast for power peak shaving auxiliary service

Dunnan Liu; Mengjiao Zou; Yue Zhang; Lingxiang Wang; Tingting Zhang; Mingguang Liu

doi:10.1051/e3sconf/202123702007

All issues

Volume 237 (2021)

E3S Web Conf., 237 (2021) 02007

References

Open Access

Issue		E3S Web Conf. Volume 237, 2021 3^rd International Symposium on Architecture Research Frontiers and Ecological Environment (ARFEE 2020)


Article Number		02007
Number of page(s)		6
Section		Energy Conservation and Emission Reduction, Energy Science
DOI		https://doi.org/10.1051/e3sconf/202123702007
Published online		09 February 2021

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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]
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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]

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[1] G. Yang. Research on Joint Optimization Decision of Electric Energy Main Market and Auxiliary Service Market[D], SJTU(2011) [Google Scholar]

[2] G. Huang. Research on the Development Potential of Electric Energy Substitution and Its Economic and Environmental Benefit[D], NCEPU (2019) [Google Scholar]

[3] 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]

[4] 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]

[5] 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]

[6] 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]

[7] 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]

[8] P. S. Dai. Research on the Price Formation Mechanism of China’s Electricity Market[D]. XMU (2004) [Google Scholar]

[9] 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]

[10] J. F. hu. Research on Cost Allocation Mechanism and Model of Auxiliary Services for Wind Power Access[D]. NCEPU (2014) [Google Scholar]

[11] 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]

[12] 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]

[13] 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]

[14] 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]

[15] 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]