Estimating Global Solar Irradiance for Optimal Photovoltaic System

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• 作者：Sungwon Kim^a ; ^{swkim1968@dyu.ac.kr" class="auth_mail" title="E-mail the corresponding author} ; Youngmin Seo^b ; Vijay P. Singh^c
• 关键词：Solar Irradiance ; ANFIS ; WANFIS ; SVMs ; WSVMs ; Photovoltaic system
• 刊名：Procedia Engineering
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：154
• 期：Complete
• 页码：1237-1242
• 全文大小：613 K

文摘

The objective of this study is to develop the hybrid model for estimating solar irradiance and investigate its accuracy for optimal photovoltaic system. The hybrid model is wavelet-based support vector machines (WSVMs) and wavelet-based adaptive-neuro fuzzy inference system (WANFIS). Wavelet decomposition is employed to decompose the global solar irradiance time series components into approximation and detail components. These decomposed time series are then used as input to support vector machines (SVMs) modules in the WSVMs model and adaptive-neuro fuzzy inference system (ANFIS) modules in the WANFIS. Based on statistical indices, results indicate that WSVMs and WANFIS can successfully be used for the estimation of global solar irradiance at Big bend, Carbondale, Champaign, and Springfield stations in Illinois.