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提升光储并网系统频率稳定性的协调控制策略
Coordinated Control Strategies for Enhancing Frequency Stability of Photovoltaic and Storage Networking Systems
【目的】为应对新能源装机占比日益增长的新型电力系统低惯量、弱阻尼引发的频率稳定问题，确保电力系统稳定运行，提出了光储并网系统多主体参与的频率主动支撑协调控制策略，以满足配置储能的光伏系统不同运行工况下的频率调控需求。【方法】所提方法根据同步机的功率调节裕度与不平衡功率分析了不同工况下系统的调频需求，设计了并网逆变器自同步控制策略，在主动支撑惯量的同时传递频率变化信息；提出了计及调频死区的光储系统多时间尺度调频控制策略，根据同步机功率调节裕度设计了光伏调频死区值，并结合储能荷电状态约束设计了其控制参数及自适应恢复策略。【结果】光储并网系统实时数字仿真结果表明，相较于现有控制方式下的调频效果，所提控制策略在不同扰动工况下，频率最低点均能提升10%以上，显著改善了系统的频率调节性能。【结论】所提光储并网系统多主体参与的频率主动支撑协调控制策略，使光储系统具备不同扰动工况下惯量支撑与一次调频自适应切换的功能，在保证系统频率稳定的同时充分发挥了同步机的调频能力，同时使储能自适应恢复至初始运行状态，有效提升了系统在不同工况下的频率稳定性。
[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.
光储并网系统 / 自同步 / 惯量支撑 / 一次调频 / 频率稳定
photovoltaic and energy storage grid-connected system / self-synchronization / inertia support / primary frequency regulation / frequency stability
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该文采用超级电容储能辅助光伏机组进行调频,提出一种适用于功率波动、故障扰动引起频率变化场景的储能调频控制策略。该策略在频率处于调频死区或光伏机组处于故障阶段下,光伏机组不参与系统调频;频率偏移量超过调频死区或故障清除后的恢复阶段,储能系统辅助光伏机组向电网提供一次调频功率或惯量支撑功率。经验证,该策略全面增强高占比光伏系统频率稳定性。
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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Aiming at the problem that PV power station with the control strategy of photovoltaic virtual synchronous generator （PV-VSG） participating in power system primary frequency control, and considering the partial shadow conditions, an active power reserve PV-VSG control strategy based on the adaptive virtual inertia is proposed. The particle swarm optimization algorithm is used to realize the maximum power point tracking and de-loading operation of PV array for grid frequency regulation under partial shadow conditions, and the virtual inertia is regulated adaptively according to the characteristics of grid frequency under different stages in the variation process, so that the frequency overshoot can be reduced and the recovery speed can be accelerated. Furthermore, in order to reasonably distribute the active power among PV-VSGs in the power plant under frequency regulation mode, an active power distribution strategy based on the equal adjustable capacity ratio is adopted, which makes each PV unit in the plant has the same active power margin for frequency regulation, so the over-regulation problem of some PV units can be avoided. Finally, simulation analyses are carried out by taking a 10 MW solar power plant participating in primary frequency regulation as an example to verify the effectiveness of the proposed control strategy.
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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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