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Coordinated Control Strategies for Enhancing Frequency Stability of Photovoltaic and Storage Networking Systems
JIANG Shouqi, ZHANG Haifeng, FU Gui, XIN Yechun, WANG Lixin
Electric Power Construction ›› 2025, Vol. 46 ›› Issue (8) : 138-149.
PDF(3090 KB)
PDF(3090 KB)
Coordinated Control Strategies for Enhancing Frequency Stability of Photovoltaic and Storage Networking Systems
[Objective] To cope with the frequency stability problems caused by the low inertia and weak damping of new power systems with an increasing proportion of new energy installations and to ensure the stable operation of the power system，a coordinated control strategy for the active frequency support of a photovoltaic storage grid-connected system with the participation of multiple subjects is proposed to meet the frequency regulation requirements under different operating conditions of the photovoltaic systems configured with energy storage. [Methods] The proposed method analyzes the frequency regulation demand of the system under different operating conditions according to the power regulation margin and unbalanced power of the synchronous machine and designs a self-synchronous control strategy for the grid-connected inverter that transmits the frequency change information while proactively supporting inertia. It proposes a multi-timescale frequency regulation control strategy for a photovoltaic storage system that considers the dead zone of the frequency regulation. The proposed method designs the value of the dead zone of the photovoltaic frequency regulation based on the power regulation margin of the synchronous machine and designs its control parameter and self-service control strategy based on the storage state of the energy charge. It designs the control parameters and adaptive recovery strategy based on the power regulation margin of the synchronous machine. [Results] The real-time digital simulation results of the grid-connected photovoltaic storage system showed that compared with the frequency regulation effect under the existing control method，the proposed control strategy could improve the frequency minimum point by more than 10% under different disturbing conditions，significantly improving the frequency regulation performance of the system. [Conclusions] The proposed coordinated control strategy of frequency active support for a grid-connected optical storage system with the participation of multiple subjects enables the optical storage system to have the adaptive switching function of inertia support and primary frequency regulation under different disturbing conditions，giving full play to the frequency regulation capability of the synchronous machine while ensuring the frequency stability of the system. Simultaneously，the energy storage adaptively recovers to the initial operating state，effectively improving the frequency stability of the system under different operating conditions.
photovoltaic and energy storage grid-connected system / self-synchronization / inertia support / primary frequency regulation / frequency stability
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This paper uses super capacitor energy storage to assist photovoltaic units in frequency modulation, and proposes an energy storage frequency modulation control strategy suitable for the scene of frequency change caused by power fluctuation and fault disturbance. In this strategy, when the frequency is in the frequency modulation dead zone or the photovoltaic unit is in the fault stage, the photovoltaic unit will not participate in the system frequency modulation. In the recovery stage, when the frequency offset exceeds the frequency modulation dead zone or the fault is cleared, the energy storage system assists the photovoltaic unit to provide primary frequency modulation power or inertia support power to the power grid. After verification, the strategy comprehensively enhances the frequency stability of high proportion photovoltaic system.
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锂电池荷电状态(state of charge，SOC)估计技术是保证电力储能和电动汽车合理应用的核心技术，也是锂电池系统控制运营、监测维护的基础。在锂电池实际应用中，其表现出非线性、时变性、影响因素复杂性和不确定性的问题，造成了荷电状态估计难度大、精度不高和适应能力不足。为此，众多锂电池荷电状态估计算法及改进策略应运而生。与此同时，部分研究人员针对不同估计方法和改进策略的实现方式和优缺点开展了分析与对比，但相关综述对估计方法的技术特点和适用性方面的论述不足且缺乏系统性总结。本文首先分析了锂电池荷电状态估计的影响因素和测试标准；然后从基于实验计算的传统方法、基于电池模型的滤波类算法、基于数据驱动的机器学习技术以及数模混合估计方法四个方面开展对比分析，归纳总结各类方法的技术特点、实现过程、适用条件、难题痛点以及应用优势，系统全面地论述了现有锂电池荷电状态估计技术的研究重点和应用现状；最后，展望了锂电池荷电状态估计算法的未来研究方向。
The lithium battery state of charge (SOC) estimation technology is the core technology to ensure the reasonable application of electric energy storage and electric vehicles, as well as the control, operation, monitoring, and maintenance of lithium battery systems. It demonstrates the problems of nonlinearity, time variability, complexity, and uncertainty of influencing factors in the practical application of lithium batteries, thereby resulting in the difficulty, low accuracy, and insufficient adaptability of the state of charge estimation. As a result, numerous lithium battery state of charge estimation algorithms and improvement strategies have emerged. At the same time, some researchers have analyzed and compared the implementation methods, advantages, and disadvantages of various estimation methods, and improvement strategies, but the relevant review lacks a systematic summary and insufficient discussion on the technical characteristics and applicability of estimation methods. To begin, this paper examines the influencing factors and test standards of lithium battery state of charge estimation. Next, the traditional methods based on experimental calculation, filtering algorithms based on battery model, data-driven machine learning technology, and digital-analog hybrid estimation methods are compared and analyzed, as well as technical characteristics, implementation process, applicable conditions, problems, pain points, and application advantages. The research focus and application status of the existing state of charge estimation technology for lithium batteries are systematically and comprehensively discussed. Finally, future research directions for lithium battery state of charge estimation algorithms are proposed. |
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