光伏系统用新型混合模糊神-经网络和风力发电机组用RBFNSM的并网运行模式智能混合发电系统

doi:10.1007/s11708-017-0446-x

Frontiers in Energy

2019, Vol. 13

Issue (1): 131-148 https://doi.org/10.1007/s11708-017-0446-x

本期目录

光伏系统用新型混合模糊神-经网络和风力发电机组用RBFNSM的并网运行模式智能混合发电系统

REZVANI Alireza¹(

), ESMAEILY Ali², ETAATI Hasan³, MOHAMMADINODOUSHAN Mohammad⁴

¹. Department of Electrical Engineering, Save Branch, Islamic Azad University, Saveh 3919715179, Iran
². Deparment of Electrical Engineering, Karaj Branch,Islamic Azad University, Karaj 3148635731, Iran
³. Iran Water an Power Resources Development Company (IWPCO), Iran
⁴. Deparment of Electrical Engineering, Science and Research Branch,Islamic Azad University,Tehran 1477893855, Iran

Intelligent hybrid power generation system using new hybrid fuzzy-neural for photovoltaic system and RBFNSM for wind turbine in the grid connected mode

Alireza REZVANI¹(

), Ali ESMAEILY², Hasan ETAATI³, Mohammad MOHAMMADINODOUSHAN⁴

¹. Department of Electrical Engineering, Saveh Branch, Islamic Azad University, Saveh 3919715179, Iran Water and Power Resources Development Company (IWPCO), Iran
². Department of Electrical Engineering, Karaj Branch, Islamic Azad University, Karaj 3148635731, Iran
³. Iran Water and Power Resources Development Company (IWPCO), Iran
⁴. Department of Electrical Engineering, Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran

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摘要:

光伏发电作为一种可再生能源，其发展速度越来越快。然而，由于依赖于天气条件，光伏系统的缺点是其间歇性。因此，风力发电被认为有助于光伏发电系统稳定可靠的负荷输出，从而提高整个发电系统在并网模式下的动态性能。本文提出了一种基于光伏和风力发电机组的智能混合发电系统的拓扑结构。为了获取最大功率，在光伏系统中采用了混合模糊神经最大功率点跟踪（MPPT）方法。与传统方法相比，混合模糊神经方法的平均跟踪效率提高了约2个百分点。风力机的俯仰角由径向基函数网络滑模（RBFNSM）控制。仿真结果显示了不同的条件下实际功率值与所提出方法的比较。所得结果验证了本文提出方法的有效性和优越性，该方法具有鲁棒性、快速响应和良好的性能。利用Matlab/Simulink建立了三相并网智能混合系统的详细数学模型和控制方法。

Abstract：

Photovoltaic (PV) generation is growing increasingly fast as a renewable energy source. Nevertheless, the drawback of the PV system is intermittent because of depending on weather conditions. Therefore, the wind power can be considered to assist for a stable and reliable output from the PV generation system for loads and improve the dynamic performance of the whole generation system in the grid connected mode. In this paper, a novel topology of an intelligent hybrid generation system with PV and wind turbine is presented. In order to capture the maximum power, a hybrid fuzzy-neural maximum power point tracking (MPPT) method is applied in the PV system. The average tracking efficiency of the hybrid fuzzy-neural is incremented by approximately two percentage points in comparison with the conventional methods. The pitch angle of the wind turbine is controlled by radial basis function network-sliding mode (RBFNSM). Different conditions are represented in simulation results that compare the real power values with those of the presented methods. The obtained results verify the effectiveness and superiority of the proposed method which has the advantages of robustness, fast response and good performance. Detailed mathematical model and a control approach of a three-phase grid-connected intelligent hybrid system have been proposed using Matlab/Simulink.

Key words： photovoltaic wind turbine hybrid system fuzzy logic controller genetic algorithm RBFNSM

收稿日期: 2016-05-06 出版日期: 2019-03-20

通讯作者: REZVANI Alireza E-mail: alireza.rezvani.saveh@gmail.com

Corresponding Author(s): Alireza REZVANI

引用本文:

REZVANI Alireza, ESMAEILY Ali, ETAATI Hasan, MOHAMMADINODOUSHAN Mohammad. 光伏系统用新型混合模糊神-经网络和风力发电机组用RBFNSM的并网运行模式智能混合发电系统[J]. Frontiers in Energy, 2019, 13(1): 131-148.
Alireza REZVANI, Ali ESMAEILY, Hasan ETAATI, Mohammad MOHAMMADINODOUSHAN. Intelligent hybrid power generation system using new hybrid fuzzy-neural for photovoltaic system and RBFNSM for wind turbine in the grid connected mode. Front. Energy, 2019, 13(1): 131-148.

链接本文:

https://academic.hep.com.cn/fie/CN/10.1007/s11708-017-0446-x
https://academic.hep.com.cn/fie/CN/Y2019/V13/I1/131

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