基于模糊神经网络的光伏发电系统功率控制方法

并网光伏发电系统的故障穿越是大规模新能源接入电网和灵活调控的技术难题,针对传统光伏发电系统在电网故障条件下穿越控制策略的不足,提出一种基于模糊神经网络的光伏发电系统功率控制方法。在电网电压突变和跌落情况下能够快速地调整光伏发电系统的工作模式,以适应光伏阵列最大输出功率和并网逆变器额定容量以及最大输出电流的限制,具有稳定性强、跟踪速度快等优点。给出了控制策略总体架构,详细阐述了电网故障控制器运行模式切换策略,建立了模糊神经网络算法的数学模型和实现流程。最后,在Matlab/Simulink平台下搭建了系统仿真模型,仿真结果验证了所提出控制策略的有效性。...

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Published in电测与仪表 Vol. 54; no. 2; pp. 46 - 51
Main Author 陆畅 智勇军 周志锋
Format Journal Article
LanguageChinese
Published 国网河南省电力公司平顶山供电公司,河南平顶山,467001 2017
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ISSN1001-1390

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Abstract 并网光伏发电系统的故障穿越是大规模新能源接入电网和灵活调控的技术难题,针对传统光伏发电系统在电网故障条件下穿越控制策略的不足,提出一种基于模糊神经网络的光伏发电系统功率控制方法。在电网电压突变和跌落情况下能够快速地调整光伏发电系统的工作模式,以适应光伏阵列最大输出功率和并网逆变器额定容量以及最大输出电流的限制,具有稳定性强、跟踪速度快等优点。给出了控制策略总体架构,详细阐述了电网故障控制器运行模式切换策略,建立了模糊神经网络算法的数学模型和实现流程。最后,在Matlab/Simulink平台下搭建了系统仿真模型,仿真结果验证了所提出控制策略的有效性。
AbstractList 并网光伏发电系统的故障穿越是大规模新能源接入电网和灵活调控的技术难题,针对传统光伏发电系统在电网故障条件下穿越控制策略的不足,提出一种基于模糊神经网络的光伏发电系统功率控制方法。在电网电压突变和跌落情况下能够快速地调整光伏发电系统的工作模式,以适应光伏阵列最大输出功率和并网逆变器额定容量以及最大输出电流的限制,具有稳定性强、跟踪速度快等优点。给出了控制策略总体架构,详细阐述了电网故障控制器运行模式切换策略,建立了模糊神经网络算法的数学模型和实现流程。最后,在Matlab/Simulink平台下搭建了系统仿真模型,仿真结果验证了所提出控制策略的有效性。
TM93; 并网光伏发电系统的故障穿越是大规模新能源接入电网和灵活调控的技术难题,针对传统光伏发电系统在电网故障条件下穿越控制策略的不足,提出一种基于模糊神经网络的光伏发电系统功率控制方法.在电网电压突变和跌落情况下能够快速地调整光伏发电系统的工作模式,以适应光伏阵列最大输出功率和并网逆变器额定容量以及最大输出电流的限制,具有稳定性强、跟踪速度快等优点.给出了控制策略总体架构,详细阐述了电网故障控制器运行模式切换策略,建立了模糊神经网络算法的数学模型和实现流程.最后,在Matlab/Simulink平台下搭建了系统仿真模型,仿真结果验证了所提出控制策略的有效性.
Abstract_FL Fault ride-through (FRT) techniques are crucial for the large-scale grid-integration and flexible control of the grid-connected PV generation systems.In order to overcome the drawbacks of conventional FRT solutions for the PV generation systems under grid fault conditions,a new power control strategy based on fuzzy-neural networks (FNN) has been proposed for the PV generation systems.The operation modes can be flexibly adjusted to adapt abrupt changes and voltage sag of grid voltage,thus the maximum output power of PV panels and maximum inverter power rating and current rating can be taken into consideration.The benefits of enhanced stability characteristics and tracking performance can be achieved.The overall controller architecture and the operation modes are presented,and the mathematical model and the flow-chart of the fuzzy-neural network algorithm are given in detail.Finally,the system simulation model is established by using Matlab/Simulink,and the effectiveness of the presented control strategy for PV system has been confirmed by the simulation results.
Author 陆畅 智勇军 周志锋
AuthorAffiliation 国网河南省电力公司平顶山供电公司,河南平顶山467001
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Zhi Yongjun
Zhou Zhifeng
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DocumentTitleAlternate Power control strategies for PV generation system based on fuzzy-neural networks
DocumentTitle_FL Power control strategies for PV generation system based on fuzzy-neural networks
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Issue 2
Keywords fuzzy-neural networks
fault ride-through
power control
功率控制
光伏发电
PV generation
模糊神经网络
故障穿越
Language Chinese
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Notes Lu Chang, Zhi Yongjun, Zhou Zhifeng ( Pingdingshan Power Supply Company, State Grid He' nan Power Compan'y, Pingdingshan 467001, He' nan, China)
23-1202/TH
PV generation, fuzzy-neural networks, fault ride-through, power control
Fault ride-through (FRT) techniques are crucial for the large-scale grid-integration and flexible control of the grid-connected PV generation systems. In order to overcome the drawbacks of conventional FRT solutions for the PV generation systems under grid fault conditions, a new power control strategy based on fuzzy-neural networks (FNN) has been proposed for the PV generation systems. The operation modes can be flexibly adjusted to adapt abrupt changes and voltage sag of grid voltage, thus the maximum output power of PV panels and maximum inverter power rating and current rating can be taken into consideration. The benefits of enhanced stability characteristics and tracking performance can be achieved. The overall controller architecture and the operation modes are presented, and the ma
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Snippet 并网光伏发电系统的故障穿越是大规模新能源接入电网和灵活调控的技术难题,针对传统光伏发电系统在电网故障条件下穿越控制策略的不足,提出一种基于模糊神经网络的光伏发电...
TM93; 并网光伏发电系统的故障穿越是大规模新能源接入电网和灵活调控的技术难题,针对传统光伏发电系统在电网故障条件下穿越控制策略的不足,提出一种基于模糊神经网络的光...
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SubjectTerms 光伏发电
功率控制
故障穿越
模糊神经网络
Title 基于模糊神经网络的光伏发电系统功率控制方法
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