LAPSE:2018.0646
Published Article
LAPSE:2018.0646
Multi-Time Scale Rolling Economic Dispatch for Wind/Storage Power System Based on Forecast Error Feature Extraction
Li Han, Rongchang Zhang, Xuesong Wang, Yu Dong
September 21, 2018
This paper looks at the ability to cope with the uncertainty of wind power and reduce the impact of wind power forecast error (WPFE) on the operation and dispatch of power system. Therefore, several factors which are related to WPFE will be studied. By statistical analysis of the historical data, an indicator of real-time error based on these factors is obtained to estimate WPFE. Based on the real-time estimation of WPFE, a multi-time scale rolling dispatch model for wind/storage power system is established. In the real-time error compensation section of this model, the previous dispatch plan of thermal power unit is revised according to the estimation of WPFE. As the regulating capacity of thermal power unit within a short time period is limited, the estimation of WPFE is further compensated by using battery energy storage system. This can not only decrease the risk caused by the wind power uncertainty and lessen wind spillage, but also reduce the total cost. Thereby providing a new method to describe and model wind power uncertainty, and providing economic, safe and energy-saving dispatch plan for power system. The analysis in case study verifies the effectiveness of the proposed model.
Keywords
battery energy storage system, factor feature extraction, multi-time scale rolling dispatch, real-time error compensation, wind power accommodation, wind power forecast error
Suggested Citation
Han L, Zhang R, Wang X, Dong Y. Multi-Time Scale Rolling Economic Dispatch for Wind/Storage Power System Based on Forecast Error Feature Extraction. (2018). LAPSE:2018.0646
Author Affiliations
Han L: School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221116, China
Zhang R: School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221116, China
Wang X: School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China
Dong Y: School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221116, China
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Journal Name
Energies
Volume
11
Issue
8
Article Number
E2124
Year
2018
Publication Date
2018-08-15
ISSN
1996-1073
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PII: en11082124, Publication Type: Journal Article
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https://doi.org/10.3390/en11082124
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Sep 21, 2018
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