Power Forecasting of Photovoltaic Generation
Power Forecasting of Photovoltaic Generation
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光伏发电功率预测
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
I. H. Mahammed
中科院分区：
文献类型：
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作者：
S. H. Oudjana;A. Hellal;I. H. Mahammed
——光伏发电量预测是可再生能源电力系统规划和运行的重要任务。本文探讨了神经网络（NN）的应用，利用数据采集系统，利用包括全球辐照度和加尔达亚市（阿尔及利亚南部）温度在内的天气数据库，研究未来一周光伏发电预测系统的设计。进行了仿真并讨论了结果，表明神经网络技术能够减少光伏发电预测误差。
— Photovoltaic power generation forecasting is an important task in renewable energy power system planning and operating. This paper explores the application of neural networks (NN) to study the design of photovoltaic power generation forecasting systems for one week ahead using weather databases include the global irradiance, and temperature of Ghardaia city (south of Algeria) using a data acquisition system. Simulations were run and the results are discussed showing that neural networks Technique is capable to decrease the photovoltaic power generation forecasting error.