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Forecasting of 5MW solar photovoltaic power plant generation using generalized neural network

机译:广义神经网络5MW太阳能光伏发电厂的预测

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. The percentage of renewable energy sources such as solar, wind power and biomass in the energy mix of India is increasing every year. Solar power variability is an important issue for grid integration of solar photovoltaic power plants. The main objective of this paper is to forecast the power generated in a 5 MW solar PV plant owned by Gujarat Power Corporation Limited (GPCL) at Charanka solar park, Gujarat. Charanka is a location with an average of320 sunny days in a year. Average solar insolation available here is 5.7???6.0 kWh/m2 per day. Data obtained from 1st March 2014???31st August 2014 is used for analysis purposes. In this paper a two stage procedure is used referred to as GNN (Generalized Neural Network) model. In the primary stage pre-processing is done on the raw data followed by neural network model for forecasting.
机译:。可再生能源的百分比,如太阳能,风力和生物量在印度的能量组合中每年都在增加。太阳能变化是太阳能光伏发电厂网格集成的重要问题。本文的主要目标是预测古吉拉特古吉拉邦古吉拉特电力公司(GPCL)拥有的5兆瓦太阳能光伏电厂生产的权力。 Charanka是一个平均每年320阳光灿烂的日子的位置。这里提供的平均太阳能缺失为5.7 ???每天6.0 kWh / m2。从2014年3月1日获得的数据?2014年8月31日用于分析目的。在本文中,使用了两个阶段程序被称为GNN(广义神经网络)模型。在初级阶段预处理是在原始数据上完成的,然后是用于预测的神经网络模型。

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