A mutated hybrid Cuckoo Search Artificial neural network for Grid-Connected Photovoltaic system output prediction / Norfarizani Nordin
This thesis presents a hybrid technique for predicting the AC power output from a Grid-Connected Photovoltaic (GCPV) system. Initially, the prediction was conducted using six classical Multi-Layer Feedforward Neural Network (MLFNN) models. These models were developed based on different sets of input...
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| フォーマット: | 学位論文 |
| 言語: | English |
| 出版事項: |
2019
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| オンライン･アクセス: | https://ir.uitm.edu.my/id/eprint/91415/1/91415.pdf https://ir.uitm.edu.my/id/eprint/91415/ |
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| 要約: | This thesis presents a hybrid technique for predicting the AC power output from a Grid-Connected Photovoltaic (GCPV) system. Initially, the prediction was conducted using six classical Multi-Layer Feedforward Neural Network (MLFNN) models. These models were developed based on different sets of inputs. A key feature for developing these models is the inclusion of time-series inputs. The inclusion of time-series inputs to the network is important as the solar irradiance, ambient temperature and module temperature have different time-constant; i.e. they have different rate of change as the climate changes. |
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