A RSCMAC Based Forecasting for Solar radiance with Meteorological Data and Wavelet Analysis

碩士 === 健行科技大學 === 電子工程系碩士班 === 103 === In recent years, due to the impact of global warming, many countries pay attention to renewable energy. Under the government strongly promotion, total installed capacity of renewable energy generation systems is increased year by year. Among the renewable ene...

Full description

Bibliographic Details
Main Authors: Hsing-Yang Chou, 周幸洋
Other Authors: 江青瓒
Format: Others
Language:zh-TW
Published: 2015
Online Access:http://ndltd.ncl.edu.tw/handle/19678682562338028399
id ndltd-TW-103CYU05428027
record_format oai_dc
spelling ndltd-TW-103CYU054280272016-08-28T04:12:12Z http://ndltd.ncl.edu.tw/handle/19678682562338028399 A RSCMAC Based Forecasting for Solar radiance with Meteorological Data and Wavelet Analysis 基於RSCMAC結合氣象資料與小波分析之太陽照射度預測系統 Hsing-Yang Chou 周幸洋 碩士 健行科技大學 電子工程系碩士班 103 In recent years, due to the impact of global warming, many countries pay attention to renewable energy. Under the government strongly promotion, total installed capacity of renewable energy generation systems is increased year by year. Among the renewable energy sources, PV( Photovoltaic ) system is one of the most important energy. Because of the power generation of PV systems changes as the solar irradiance varies, its power generation is not stable and affects overall electricity grid configuration, scheduling and stability. Therefore, accurately predict PV system power generation is very important for regional power dispatch. Solar irradiance is the most important factor to effect PV system power generation. This study focuses on solar irradiance short-term prediction; use RSCMAC (Recurrent Simple addressing structure for Cerebellar Model Articulation Controller) as the basis to combine meteorological data and wavelet analysis to establish a solar irradiance prediction model. Furthermore, this study uses the peak value and the amount of change of solar irradiance to establish standard wave training patterns to be used in solar irradiance prediction model, this can solved the training and testing deviation caused by weather forecast error, training wave not generalized, etc. Excellent performance is obtained from simulation test results. 江青瓒 2015 學位論文 ; thesis 121 zh-TW
collection NDLTD
language zh-TW
format Others
sources NDLTD
description 碩士 === 健行科技大學 === 電子工程系碩士班 === 103 === In recent years, due to the impact of global warming, many countries pay attention to renewable energy. Under the government strongly promotion, total installed capacity of renewable energy generation systems is increased year by year. Among the renewable energy sources, PV( Photovoltaic ) system is one of the most important energy. Because of the power generation of PV systems changes as the solar irradiance varies, its power generation is not stable and affects overall electricity grid configuration, scheduling and stability. Therefore, accurately predict PV system power generation is very important for regional power dispatch. Solar irradiance is the most important factor to effect PV system power generation. This study focuses on solar irradiance short-term prediction; use RSCMAC (Recurrent Simple addressing structure for Cerebellar Model Articulation Controller) as the basis to combine meteorological data and wavelet analysis to establish a solar irradiance prediction model. Furthermore, this study uses the peak value and the amount of change of solar irradiance to establish standard wave training patterns to be used in solar irradiance prediction model, this can solved the training and testing deviation caused by weather forecast error, training wave not generalized, etc. Excellent performance is obtained from simulation test results.
author2 江青瓒
author_facet 江青瓒
Hsing-Yang Chou
周幸洋
author Hsing-Yang Chou
周幸洋
spellingShingle Hsing-Yang Chou
周幸洋
A RSCMAC Based Forecasting for Solar radiance with Meteorological Data and Wavelet Analysis
author_sort Hsing-Yang Chou
title A RSCMAC Based Forecasting for Solar radiance with Meteorological Data and Wavelet Analysis
title_short A RSCMAC Based Forecasting for Solar radiance with Meteorological Data and Wavelet Analysis
title_full A RSCMAC Based Forecasting for Solar radiance with Meteorological Data and Wavelet Analysis
title_fullStr A RSCMAC Based Forecasting for Solar radiance with Meteorological Data and Wavelet Analysis
title_full_unstemmed A RSCMAC Based Forecasting for Solar radiance with Meteorological Data and Wavelet Analysis
title_sort rscmac based forecasting for solar radiance with meteorological data and wavelet analysis
publishDate 2015
url http://ndltd.ncl.edu.tw/handle/19678682562338028399
work_keys_str_mv AT hsingyangchou arscmacbasedforecastingforsolarradiancewithmeteorologicaldataandwaveletanalysis
AT zhōuxìngyáng arscmacbasedforecastingforsolarradiancewithmeteorologicaldataandwaveletanalysis
AT hsingyangchou jīyúrscmacjiéhéqìxiàngzīliàoyǔxiǎobōfēnxīzhītàiyángzhàoshèdùyùcèxìtǒng
AT zhōuxìngyáng jīyúrscmacjiéhéqìxiàngzīliàoyǔxiǎobōfēnxīzhītàiyángzhàoshèdùyùcèxìtǒng
AT hsingyangchou rscmacbasedforecastingforsolarradiancewithmeteorologicaldataandwaveletanalysis
AT zhōuxìngyáng rscmacbasedforecastingforsolarradiancewithmeteorologicaldataandwaveletanalysis
_version_ 1718380450601238528