Multi-model short-term solar irradiance prediction based on different cloud types
碩士 === 國立中央大學 === 資訊工程學系 === 103 === Renewable energy is growing quickly in the modern society. Many countries have devoted themselves to the development of renewable power. And solar energy is one of the most important renewable energy. To overcome its unstable nature and achieve better utilization...
Main Authors: | , |
---|---|
Other Authors: | |
Format: | Others |
Language: | zh-TW |
Published: |
2015
|
Online Access: | http://ndltd.ncl.edu.tw/handle/2a7pu5 |
id |
ndltd-TW-103NCU05392101 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-TW-103NCU053921012019-05-15T22:08:47Z http://ndltd.ncl.edu.tw/handle/2a7pu5 Multi-model short-term solar irradiance prediction based on different cloud types 基於不同雲種之多模型短期日射量預測 Hsin-Hao Huang 黃信豪 碩士 國立中央大學 資訊工程學系 103 Renewable energy is growing quickly in the modern society. Many countries have devoted themselves to the development of renewable power. And solar energy is one of the most important renewable energy. To overcome its unstable nature and achieve better utilization, forecasting short-term solar irradiance precisely is a crucial issue. This paper proposes a short-term irradiance prediction framework that based on automatic cloud classification. The cloud types are classified according to the features extracted from all-sky images. Multiple regression models are constructed by different cloud types using historical clearness indices or irradiance values as features. Moreover, ramp-down events are detected and the predicted irradiance is corrected on ramp-down events. The amount of correction is determined by the features extracted from the all-sky images. We also design a Kalman-filter based prediction model with time-varying system matrix. Afterwards, we fuse the prediction results of the regressor and the Kalman filter predictor. Finally, we validate the proposed system with two different datasets. Experiments have shown that incorporating cloud type information can capture different characteristics of irradiance variation under different cloud types. Also, the design of time-varying system matrix is able to improve the prediction accuracy. Hsu-Yung Cheng 鄭旭詠 2015 學位論文 ; thesis 62 zh-TW |
collection |
NDLTD |
language |
zh-TW |
format |
Others
|
sources |
NDLTD |
description |
碩士 === 國立中央大學 === 資訊工程學系 === 103 === Renewable energy is growing quickly in the modern society. Many countries have devoted themselves to the development of renewable power. And solar energy is one of the most important renewable energy. To overcome its unstable nature and achieve better utilization, forecasting short-term solar irradiance precisely is a crucial issue. This paper proposes a short-term irradiance prediction framework that based on automatic cloud classification. The cloud types are classified according to the features extracted from all-sky images. Multiple regression models are constructed by different cloud types using historical clearness indices or irradiance values as features. Moreover, ramp-down events are detected and the predicted irradiance is corrected on ramp-down events. The amount of correction is determined by the features extracted from the all-sky images. We also design a Kalman-filter based prediction model with time-varying system matrix. Afterwards, we fuse the prediction results of the regressor and the Kalman filter predictor. Finally, we validate the proposed system with two different datasets. Experiments have shown that incorporating cloud type information can capture different characteristics of irradiance variation under different cloud types. Also, the design of time-varying system matrix is able to improve the prediction accuracy.
|
author2 |
Hsu-Yung Cheng |
author_facet |
Hsu-Yung Cheng Hsin-Hao Huang 黃信豪 |
author |
Hsin-Hao Huang 黃信豪 |
spellingShingle |
Hsin-Hao Huang 黃信豪 Multi-model short-term solar irradiance prediction based on different cloud types |
author_sort |
Hsin-Hao Huang |
title |
Multi-model short-term solar irradiance prediction based on different cloud types |
title_short |
Multi-model short-term solar irradiance prediction based on different cloud types |
title_full |
Multi-model short-term solar irradiance prediction based on different cloud types |
title_fullStr |
Multi-model short-term solar irradiance prediction based on different cloud types |
title_full_unstemmed |
Multi-model short-term solar irradiance prediction based on different cloud types |
title_sort |
multi-model short-term solar irradiance prediction based on different cloud types |
publishDate |
2015 |
url |
http://ndltd.ncl.edu.tw/handle/2a7pu5 |
work_keys_str_mv |
AT hsinhaohuang multimodelshorttermsolarirradiancepredictionbasedondifferentcloudtypes AT huángxìnháo multimodelshorttermsolarirradiancepredictionbasedondifferentcloudtypes AT hsinhaohuang jīyúbùtóngyúnzhǒngzhīduōmóxíngduǎnqīrìshèliàngyùcè AT huángxìnháo jīyúbùtóngyúnzhǒngzhīduōmóxíngduǎnqīrìshèliàngyùcè |
_version_ |
1719126449304109056 |