Optimization of the Fast Frequency Regulation Strategy for Energy Storage-Assisted Photovoltaic Power Stations

Authors

  • Jiayun Zhou School of Control and Computer Engineering, North China Electric Power University, Changping 102206, Beijing, China

DOI:

https://doi.org/10.13052/dgaej2156-3306.3923

Keywords:

Primary frequency regulation, photovoltaic energy storage hybrid system, equivalent droop control, adaptive droop control

Abstract

Photovoltaic (PV) power generation is characterized by randomness and intermittency, resulting in unpredictable fluctuations in output power. This presents a significant challenge to the stable operation of the grid. To address this issue, the integration of energy storage systems provides a solution to mitigate the volatility of PV output, ensuring stability and precise control. In this study, we propose an ASS-Elman-based equivalent droop control strategy for PV power stations participating in grid frequency regulation. Furthermore, a joint PV-energy storage frequency regulation system is developed. For energy storage power stations actively engaged in grid frequency regulation, we employ an adaptive droop control strategy to enhance the traditional droop control method by incorporating additional frequency control strategies. We validate the effectiveness of the proposed strategies through simulation using MATLAB/SIMULINK. The results demonstrate that these strategies maximize the potential of energy storage and PV systems to comprehensively regulate frequency and significantly improve primary frequency regulation performance.

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Author Biography

Jiayun Zhou, School of Control and Computer Engineering, North China Electric Power University, Changping 102206, Beijing, China

Jiayun Zhou is currently pursuing a Master’s degree in the Control Science and Engineering program at North China Electric Power University. His research primarily centers around the optimization of rapid frequency control strategies for photovoltaic energy storage systems, power electronic modeling, grid integration of photovoltaic energy storage systems, and the utilization of energy storage technology for enhancing response speed and operational flexibility. The objective of his work is to address the safety and stability concerns in large-scale grid-connected power generation. Specifically, his focus areas include droop control, inertia control, EADRC control, fuzzy control applied to frequency regulation in photovoltaic energy storage systems, and the application of reinforcement learning algorithms.

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Published

2024-02-03

How to Cite

Zhou, J. . (2024). Optimization of the Fast Frequency Regulation Strategy for Energy Storage-Assisted Photovoltaic Power Stations. Distributed Generation &Amp; Alternative Energy Journal, 39(02), 263–296. https://doi.org/10.13052/dgaej2156-3306.3923

Issue

Section

Renewable Power & Energy Systems