摘要
光伏电池板(电池板)积灰可降低透光率、引起热斑效应、腐蚀玻璃表面,实时监测积灰状态,及时清洗积灰将为光伏电站带来显著的经济效益。提出一种电池板积灰状态发电效率监测方法,构建电功率损失率随积灰时间变化的渐近型预测模型,并建立电池板积灰费用评估数学模型,以年累计电量损失费与清洗维护费之和最小化来确定最佳清洗周期。实例分析表明:蒙东地区50MW光伏电站积灰43天时电功率损失率达到15.32%,最佳清洗周期为20.3天,与当前现场固定清洗周期90天比较,将积灰经济损失由18.96万元·MW^-1×a^-1降至12.85万元·MW^-1×a^-1,占发电收益比例由15.3%降到10.4%;装机容量和年累计清洗时间对最佳清洗周期无显著影响,但并网电价越低、单位面积清洗费用越高时,最佳清洗周期越长。
Dust deposition on photovoltaic (PV) modules can reduce transmission rate, cause hot spot effect and corrode glass surface. On-line monitoring of dust condition and timely cleaning dust could bring remarkable economic benefits for PV power plants. A module efficiency monitoring method in dust condition was presented, and a prediction model of electric power loss rate with the dust accumulating time was established. Aiming at minimizing the sum of power loss cost and cleaning maintenance cost caused by dust, an estimation mathematical model of modules dust cost was presented to optimize optimal cleaning cycle. The example analysis results show that: the power loss rate of a 50MW PV power plant can reach 15.32% after dust accumulated for 43 days in eastern Inner Mongolia, the optimum cleaning cycle is 20.3 days, compared with the site operation condition of cleaning cycle of 90 days, the annual dust cost of unit capacity plant is reduced from 189600yuan·MW^-1·a^-1 to 128500yuan·MW^-1·a^-1. Moreover, dust economic losses accounted for the proportion of PV power plant revenue can be reduced from 15.3% to 10.4% by cleaning optimization. The installed capacity and the annual accumulated cleaning time have no significant impact on the optimal cleaning cycle. However, the lower electricity price and the higher cleaning cost per unit area can result in longer optimal cleaning period.
作者
赵波
张姝伟
曹生现
王恭
许兆鹏
崔立业
李晓刚
ZHAO Bo;ZHANG Shuwei;CAO Shengxian;WANG Gong;XU Zhangpeng;CUI Liye;LI Xiaogang(School of Automation Engineering, Northeast Electric Power University, Jilin 132012, Jilin Province, China;Science and Technology Development Branch, Jilin Electric Power CO., LTD., Changchun 130012, Jilin Province, China)
出处
《中国电机工程学报》
EI
CSCD
北大核心
2019年第14期4205-4212,共8页
Proceedings of the CSEE
基金
国家自然科学基金项目(51606035,61503072)
吉林电力股份有限公司科学技术项目(JDGF-KJGS-2016-004)~~
关键词
电池板积灰
状态监测
电功率损失率
预测模型
清洗周期
费用评估
dust of photovoltaic modules
monitoring of dust condition
power loss rate
prediction model
cleaning cycle
cost estimation
