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1.国网甘肃省电力公司 电力科学研究院,甘肃 兰州 730070
2.四川大学 电气工程学院,四川 成都 610065
Received:06 July 2023,
Revised:31 July 2023,
Published Online:28 August 2023,
Published:20 March 2024
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刘文飞,赖辉,杨勇,等.基于光伏动态电流参考值的两级式光伏并网系统低电压穿越控制策略[J].工程科学与技术,2024,56(2):55–67
Liu Wenfei,Lai Hui,Yang Yong,et al.Low-voltage ride-through control strategy for two-stage grid-connected PV systems based on dynamic current reference value[J].Advanced Engineering Sciences,2024,56(2):55–67
刘文飞,赖辉,杨勇,等.基于光伏动态电流参考值的两级式光伏并网系统低电压穿越控制策略[J].工程科学与技术,2024,56(2):55–67 DOI: 10.15961/j.jsuese.202300509.
Liu Wenfei,Lai Hui,Yang Yong,et al.Low-voltage ride-through control strategy for two-stage grid-connected PV systems based on dynamic current reference value[J].Advanced Engineering Sciences,2024,56(2):55–67 DOI: 10.15961/j.jsuese.202300509.
随着光伏接入容量的不断提升,电网电压跌落时光伏脱网会影响系统稳定运行,因此光伏系统应具备低电压穿越(LVRT)能力。然而,目前常用的两级式光伏并网系统LVRT控制策略存在光伏动态响应慢及控制效果受限于光伏
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特性曲线的数学模型精度等问题,且未考虑局部阴影条件下的适用性。基于此,提出一种基于光伏动态电流参考值的LVRT控制策略。首先,在建立两级式光伏并网系统及光伏电池
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特性数学模型的基础上,分别对目前常用的基于定直流母线电压和基于光伏
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特性曲线的LVRT控制的原理及不足进行了分析。其次,针对前级boost电路的控制构造了具有自适应收敛特性的光伏输出电流动态参考值以对光伏工作点进行直接调整。该策略无需对光伏
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特性曲线数学模型进行求解,避免求解误差的同时加快了光伏动态响应速度。此外,在最大功率跟踪(MPPT)算法中引入故障解耦模块,在电网低电压故障期间对MPPT输出电压参考值进行锁定,避免MPPT无效运算带来的电压参考值偏移,使系统在故障结束时能以最快速度恢复至最大功率点。最后,通过仿真将所提策略与目前常用的基于定直流母线电压和基于光伏
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特性曲线的LVRT控制策略在多种环境条件下进行对比。仿真结果表明:与定直流母线电压控制策略相比,所提策略下光伏动态响应快;与现有基于光伏
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特性曲线的控制策略相比,所提策略不受
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特性误差的影响,在辐照度变化尤其局部阴影条件下均能很好地实现低电压穿越。
With the continuous increase in photovoltaic (PV) access capacity
voltage sag in the grid when the PV is off-grid can adversely impact the stable operation of the system. Therefore
it is imperative for the PV system to possess low-voltage ride-through (LVRT) capability. However
the existing PV LVRT strategy
which is based on a fixed DC bus voltage
indirectly adjusts PV output power according to changes in the DC bus voltage
resulting in a slow dynamic response. A two-stage PV LVRT control strategy based on the PV power–voltage (
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) characteristic curve directly controls PV output power based on the inverter’s output active power during a fault. However
a drawback is that the PV voltage and current reference values must be obtained through model solving
and the model accuracy is susceptible to the completeness of the PV nameplate and irradiance. Moreover
the LVRT effect under partial shadow shading scenarios has not been considered. To address these challenges
a dynamic current reference value-based LVRT control strategy for two-stage grid-connected PV systems is introduced
specifically designed for partial shading scenarios. Initially
a mathematical model is established based on the characteristics of the two-stage grid-connected PV system and PV cells. The strengths and weaknesses of existing LVRT control strategies are analyzed. Subsequently
a dynamic current reference value with adaptive convergence characteristics is constructed
and its convergence under scenarios of uniform illumination and local shadow shading is examined. The pre-stage boost circuit is employed to control PV output current using the set dynamic current reference value. This adjustment of the PV operating point accelerates the dynamic response of the PV system and mitigates errors caused by model solutions. Additionally
a fault decoupling module is incorporated into the maximum power tracking algorithm
enabling the system to lock the maximum power point tracking output voltage reference value by switching input quantities during a fault. This facilitates a quick system recovery to the maximum power point after the fault concludes. Finally
the proposed strategy is compared with fixed DC bus voltage control and PV
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curve-based LVRT control strategies under various environmental conditions through simulation. The results indicate that the proposed strategy exhibits a faster dynamic response compared to the fixed DC bus voltage control strategy. Moreover
in comparison to the control strategy based on the
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characteristic curve of PV
the proposed strategy effectively achieves LVRT under different irradiance levels
particularly in partial shadow shading conditions
making it more adaptable to varying environmental conditions.
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