文章摘要
陶仁峰,李凤婷,李永东,等.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. DOI: 10.7500/AEPS20170724005.
TAO Renfeng,LI Fengting,LI Yongdong, et al.MPPT Strategy of Photovoltaic Station Based on Cloud Distribution Pattern and Sunlight Tracking[J].Automation of Electric Power Systems,2018,42(5):25-33. DOI: 10.7500/AEPS20170724005.
基于云层分布规律与太阳光跟踪的光伏电站MPPT策略
MPPT Strategy of Photovoltaic Station Based on Cloud Distribution Pattern and Sunlight Tracking
DOI:10.7500/AEPS20170724005
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
KeyWords: maximum power point tracking(MPPT)  cloud distribution pattern  sunlight tracing  adaptive sunlight intensity partitioning  genetic algorithm
上网日期:2018-01-23
基金项目:新疆维吾尔自治区自然科学基金资助项目(2016D01C036)
作者单位E-mail
陶仁峰 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  
李凤婷 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 xjlft2009@sina.com 
李永东 清华大学电机工程与应用电子系, 北京市 100084  
付林 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  
辛超山 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  
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。
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.
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