A Frequency Support Approach for Hybrid Energy Systems Considering Energy Storage

Dahu Li, Hongyu Zhou (), Yuan Chen, Yue Zhou, Yuze Rao and Wei Yao
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Dahu Li: State Grid Hubei Electric Power Co., Ltd., Wuhan 430077, China
Hongyu Zhou: School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Yuan Chen: China Hubei Emission Exchange, Wuhan 430070, China
Yue Zhou: State Grid Hubei Electric Power Co., Ltd., Wuhan 430077, China
Yuze Rao: State Grid Hubei Electric Power Co., Ltd., Wuhan 430077, China
Wei Yao: School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China

Energies, 2023, vol. 16, issue 10, 1-16

Abstract: In hybrid energy systems, the intermittent and fluctuating nature of new energy sources poses major challenges for the regulation and control of power systems. To mitigate these challenges, energy storage devices have gained attention for their ability to rapidly charge and discharge. Collaborating with wind power (WP), energy storage (ES) can participate in the frequency control of regional power grids. This approach has garnered extensive interest from scholars worldwide. This paper proposes a two-region load frequency control model that accounts for thermal power, hydropower, ES, and WP. To address complex, nonlinear optimization problems, the dingo optimization algorithm (DOA) is employed to quickly obtain optimal power dispatching commands under different power disturbances. The DOA algorithm’s effectiveness is verified through the simulation of the two-region model. Furthermore, to further validate the proposed method’s optimization effect, the DOA algorithm’s optimization results are compared with those of the genetic algorithm (GA) and proportion method (PROP). Simulation results show that the optimization effect of DOA is more significant than the other methods.

Keywords: hybrid energy system; energy storage; wind power; support frequency; dingo optimization algorithm (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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