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当前位置: 首页 > 文章 > 光伏发电短期功率预测模型与电站监控系统设计 山东农业大学学报(自然科学版) 2016 (1) 83-87
Position: Home > Articles > The Short-term Prediction Model of Photovoltaic Grid Power Generation and the Design for Monitoring System of a Power Station Journal of Shandong Agricultural University(Natural Science Edition) 2016 (1) 83-87

光伏发电短期功率预测模型与电站监控系统设计

作  者：
林嵩
单  位：
浙江工业职业技术学院
关键词：
光伏发电系统;功率预测模型;电站监控系统
摘  要：
目前大规模光伏并网发电系统的输出功率波动大、随机性强,为准确预测光伏电站的输出功率以解决大规模光伏并网发电给电网造成的调峰、调度等难题。通过开发能实时监测环境辐照强度、温度、湿度、风向、风速等环境参数的低成本小型气象站和光伏电站监控系统来监测光伏电站的运行状况和采集气象与电站输出功率的数据,并应用于气象条件聚类识别和小波神经网络光伏发电系统短期发电功率预测模型上,以实现大规模光伏并网发电系统输出功率的精确预测,对大规模光伏并网发电系统的推广应用具有重要意义。
译  名：
The Short-term Prediction Model of Photovoltaic Grid Power Generation and the Design for Monitoring System of a Power Station
作  者：
LIN Song;Zhejiang Industry Polytechnic College;
关键词：
Photovoltaic power generation system;;power prediction model;;photovoltaic power station monitoring system
摘  要：
At present, there is a large fluctuation and randomicity in output power of the large-scale photovoltaic(pv) grid power generation system. To accurately predict the output power in order to solve problems of peak regulation and schedule in photovoltaic grid, this paper set up a low cost small meteorological station real-time monitoring the environment parameters such as radiation intensity, temperature, humidity, wind direction, wind speed etc. and a monitoring system to monitor the operation condition of the photovoltaic power station and gather the data of meteorology to apply to the identification of the meteorological conditions and the prediction model of a short-term power in the photovoltaic power generation system of wavelet neural network so as to realize the accurate prediction for an output power in the large-scale photovoltaic(pv) grid power system and it could have an important significance to generate and apply in a large-scale photovoltaic(pv) grid power generation system.

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