Day-Ahead Dynamic Assessment of Consumption Service Reserve Based on Morphological Filter

Xinlei Cai, Naixiao Wang, Qinqin Cai (), Hengzhen Wang, Zhangying Cheng, Zhijun Wang, Tingxiang Zhang and Ying Xu
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Xinlei Cai: Electric Power Dispatching and Control Center of Guangdong Power Grid Co., Ltd., Guangzhou 510220, China
Naixiao Wang: Electric Power Dispatching and Control Center of Guangdong Power Grid Co., Ltd., Guangzhou 510220, China
Qinqin Cai: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Hengzhen Wang: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Zhangying Cheng: Electric Power Dispatching and Control Center of Guangdong Power Grid Co., Ltd., Guangzhou 510220, China
Zhijun Wang: Electric Power Dispatching and Control Center of Guangdong Power Grid Co., Ltd., Guangzhou 510220, China
Tingxiang Zhang: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Ying Xu: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China

Energies, 2023, vol. 16, issue 16, 1-11

Abstract: With the development goal of a low-cost and low-carbon reserve market, this paper proposes a dynamic assessment method for day-ahead consumption service reserve demand considering the forecast error of uncertainty power. The iterative self-organizing data analysis techniques algorithm is adopted to cluster the historical actual power into typical scenarios. In addition, the online matching between the typical scenario and the day-ahead forecast power is conducted. In order to realize the hierarchical quantification of reserve demand, the reserve resources in the whole power system are classified according to their response time. Furthermore, the mathematical morphology filter based on the structural elements that are consistent with the response time of the hierarchical reserve resources is initially applied to decompose the historical forecast error of the matched scenarios. The simulation results verify that the proposed dynamic assessment effectively reduces the reserve cost on the basis of being able to cope with multi-time-scale power fluctuations.

Keywords: consumption service reserve; dynamic assessment; ISODATA clustering algorithm; morphological filter (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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