Estimation of Electricity Production from Photovoltaic Panels

Vamsi Bulusu, Yann Busnel, N. Montavont
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Abstract

The electricity grid is evolving to a distributed infrastructure in which smart grids integrating renewable energies will become dominant. Because of the limited capacity of the battery to store the energy produced at certain time of the day, it is necessary to shift the consumption to when the electricity is actually produced. This paper deals with the estimation of solar panel production in order to forecast when and how much electricity will be available. We propose an Artificial Neural Network model to predict the hourly production of photovoltaic (PV) plants. We evaluate our approach over a large dataset of solar panel electricity production over a period of seven years.
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光伏板发电量的估算
电网正在向分布式基础设施发展,其中集成可再生能源的智能电网将占据主导地位。由于电池存储一天中特定时间产生的能量的容量有限,因此有必要将消耗转移到实际产生电力的时候。本文讨论了太阳能电池板生产的估计,以预测何时以及有多少电力可用。我们提出了一个人工神经网络模型来预测光伏电站的小时产量。我们在七年的太阳能电池板电力生产的大型数据集上评估了我们的方法。
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