A Novel Allocation Strategy Based on the Model Predictive Control of Primary Frequency Regulation Power for Multiple Distributed Energy Storage Aggregators

Tian Mao, Shan He, Yingcong Guan (), Mingbo Liu, Wenmeng Zhao, Tao Wang and Wenjun Tang
Additional contact information
Tian Mao: Electric Power Research Institute, China Southern Power Grid, Guangzhou 510663, China
Shan He: Shenzhen Power Supply Company, China Southern Power Grid, Shenzhen 518067, China
Yingcong Guan: College of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China
Mingbo Liu: College of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China
Wenmeng Zhao: Electric Power Research Institute, China Southern Power Grid, Guangzhou 510663, China
Tao Wang: Electric Power Research Institute, China Southern Power Grid, Guangzhou 510663, China
Wenjun Tang: Shenzhen Power Supply Company, China Southern Power Grid, Shenzhen 518067, China

Energies, 2023, vol. 16, issue 17, 1-21

Abstract: As the amount of distributed energy storage (DES) in a power system continues to increase, it will not be long before there are multiple DES aggregators participating in frequency regulation, and the realization of their coordinated control is a critical topic of current research. This study focused on the primary frequency regulation (PFR) power allocation strategy among multiple DES aggregators participating in PFR. This study first calculated the PFR demand according to a system frequency response model of the power system with DESs. Next, a PFR power allocation model of DES aggregators was developed based on model predictive control. The objective of this model was to minimize the overall frequency regulation cost while satisfying all of the constraints of DESs. Finally, the distributed interior point method was used to solve the model rapidly. The correctness and effectiveness of the proposed model and algorithm were verified on two unified transmission and distribution systems with DES aggregators used to supply the PFR service. The results revealed that the proposed model could effectively allocate PFR power to the various types of energy storage, with the additional benefits of slowing down the shift in the state of charge for energy storage units and ensuring the continuity of energy storage participation in frequency regulation.

Keywords: distributed energy storage aggregator; primary frequency regulation; frequency response model; model predictive control; distributed interior point method (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
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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