Taiwan is currently promoting energy transformation and has set "promote green energy, increase natural gas, reduce coal-fired, achieve nuclear-free" as the principle for clean energy development. Solar photovoltaic (PV) is one of the renewable energy sources currently supported and promoted by the government. The Bureau of Energy, Ministry of Economic Affairs (MOEBOE) has planned a target for renewable energy to reach 27 GW (with a 20% share of renewable energy in electricity generation) by 2025. The goal for the installation of solar PV systems has been set at 20GW. Taiwan's installed capacity of solar PV systems was 9.157 GW by the end of October 2022. However, with the continuous growth and expansion of solar PV system installations, and the overall system must be exposed to the outdoors for a long time, the probability of component aging and failure is relatively higher, making the operation and maintenance (O&M) of PV systems increasingly important. Therefore, to promote Taiwan's energy transformation and address PV O&M issues, this paper combined artificial intelligence (AI) algorithms, internet of things (IoT), human-machine interfaces (HMI), and smartphone Apps to carry out fault diagnosis research on PV modules and develop related PV (O&M) strategies to promote the development of Taiwan's solar PV industry.
Shiue-Der Lu, National Chin-Yi University of Technology, Taiwan
Meng-Hui Wang, National Chin-Yi University of Technology, Taiwan
Chia-Chun Wu, National Chin-Yi University of Technology, Taiwan
Chien-Kuo Chang, National Taiwan University of Science and Technology, Taiwan
About the Presenter(s)
Professor Shiue-Der Lu is a University Associate Professor/Senior Lecturer at National Chin-Yi University of Technology in Taiwan
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