利用支持向量回归预测太阳能潜力

Subham Shaw, M. Prakash
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引用次数: 2

摘要

太阳能是最常用的可再生能源之一。为了获得可靠的太阳能输出,必须对太阳辐射进行预测。本文建立了加尔各答新阿里波雷的太阳辐射预报模型。利用容易获得的气象参数,如温度、压力和湿度作为输入,建立预测模型。利用2011-2012年的两年数据,建立了基于支持向量回归(SVR)的太阳辐射预测模型。利用统计指标、均方根误差(RMSE)和决定系数$(\ mathm {R}^{2})$对预测模型的结果进行了验证。结果表明,与文献中已有的模型相比,所建立的模型具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forecasting Solar Potential Using Support Vector Regression
Solar energy is one of the most commonly used renewable energy resources. To obtain reliable output from solar energy, prediction of solar radiation is necessary. In this paper, a solar radiation prediction model has been developed for New Alipore, Kolkata. Easily available meteorological parameters like temperature, pressure and humidity have been utilized as inputs, to build the prediction model. Two years data (2011–2012) have been used to develop the Support Vector Regression (SVR) based solar radiation prediction model. The results obtained from the prediction model have been validated with the help of statistical metrics, Root-Mean-Square Error (RMSE) and Coefficient of Determination $(\mathrm{R}^{2})$. The results signifies that the performance of the developed model is better in comparison with the models existing in the literature.
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