首页 | 本学科首页   官方微博 | 高级检索  
     

基于云层分布规律与太阳光跟踪的光伏电站MPPT策略
引用本文:陶仁峰,李凤婷,李永东,付林,辛超山.基于云层分布规律与太阳光跟踪的光伏电站MPPT策略[J].电力系统自动化,2018,42(5):25-33.
作者姓名:陶仁峰  李凤婷  李永东  付林  辛超山
作者单位:可再生能源发电与并网技术教育部工程研究中心(新疆大学), 新疆维吾尔自治区乌鲁木齐市 830047,可再生能源发电与并网技术教育部工程研究中心(新疆大学), 新疆维吾尔自治区乌鲁木齐市 830047,清华大学电机工程与应用电子系, 北京市 100084,国网新疆电力有限公司经济技术研究院, 新疆维吾尔自治区乌鲁木齐市 830002,国网新疆电力有限公司经济技术研究院, 新疆维吾尔自治区乌鲁木齐市 830002
基金项目:新疆维吾尔自治区自然科学基金资助项目(2016D01C036)
摘    要:针对现有光伏系统最大功率点跟踪(MPPT)较少考虑诸如光照等外界因素或即使考虑也多做定性分析的问题,提出一种基于云层分布规律与太阳光跟踪的大规模光伏电站MPPT策略。首先,分析云层对太阳光的散射、折射与遮挡效应,结合区域云层分布规律,构建太阳光跟踪装置(以下简称检测球)有效指导半径模型以及在光伏电站中优化布点模型;其次,依据光伏板输出功率差异,提出太阳光辐照强度边界自寻优划分方法,并基于光伏板与检测球间相对位置,建立检测球指导光伏板姿态调整数学模型。最后,采用粒子群优化算法获取单个光伏板最大功率点,进而实现光伏电站MPPT。以西北某光伏电站为背景,仿真验证了所提策略的正确性。

关 键 词:最大功率点跟踪  云层分布规律  太阳光跟踪  光照强度自适应划分  遗传算法
收稿时间:2017/7/24 0:00:00
修稿时间:2017/11/10 0:00:00

MPPT Strategy of Photovoltaic Station Based on Cloud Distribution Pattern and Sunlight Tracking
TAO Renfeng,LI Fengting,LI Yongdong,FU Lin and XIN Chaoshan.MPPT Strategy of Photovoltaic Station Based on Cloud Distribution Pattern and Sunlight Tracking[J].Automation of Electric Power Systems,2018,42(5):25-33.
Authors:TAO Renfeng  LI Fengting  LI Yongdong  FU Lin and XIN Chaoshan
Affiliation:Engineering Research Center of Education Ministry for Renewable Energy Power Generation and Grid Technology (Xinjiang University), Urumqi 830047, China,Engineering Research Center of Education Ministry for Renewable Energy Power Generation and Grid Technology (Xinjiang University), Urumqi 830047, China,Department of Electrical Engineering, Tsinghua University, Beijing 100084, China,Economic Research Institute of State Grid Xinjiang Electric Power Co. Ltd., Urumqi 830002, China and Economic Research Institute of State Grid Xinjiang Electric Power Co. Ltd., Urumqi 830002, China
Abstract:Considering external factors such as sunlight and so on are not considered or just qualitatively analysed by the maximum power point tracking(MPPT)method in current photovoltaic(PV)system, a MPPT strategy of large-scale PV station based on cloud distribution pattern and sunlight tracking is proposed. Firstly, the scattering, refraction and shadowing effect of sunlight caused by the cloud are analyzed. The confidence guiding radius model of sunlight tracking device(called detecting ball)is proposed and the layout model is optimized in PV plant considering the region cloud distribution pattern. Secondly, the adaptive partitioning method of sunlight intensity based on output power difference of PV panels is presented and the attitude adjustment model of PV panel is established based on the relative position between PV panel and detecting ball. Finally, the maximum power point of PV panel is obtained by using the particle swarm optimization algorithm and MPPT of PV plant is realized. An example of PV station in Northwest China is used to verify the correctness of the proposed strategy.
Keywords:maximum power point tracking(MPPT)  cloud distribution pattern  sunlight tracing  adaptive sunlight intensity partitioning  genetic algorithm
本文献已被 CNKI 等数据库收录!
点击此处可从《电力系统自动化》浏览原始摘要信息
点击此处可从《电力系统自动化》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号