{"title":"太阳能发电预测的关键问题和未来趋势","authors":"Yuan-Kang Wu, Cheng-Liang Huang","doi":"10.1109/ECICE55674.2022.10042953","DOIUrl":null,"url":null,"abstract":"Owing to the effect of cloud, solar irradiance is intermittent and causes uncertainty in power system operations. Thus, accurate solar power forecasting helps system operators reduce the risk and cost of generator scheduling. Compared to wind power forecasting, solar power forecasting has a higher challenge because the prediction of solar irradiance is difficult. However, the curve of solar irradiance includes a daily pattern. Thus, statistical methods or deep learning models capture the important characteristics of solar power generation, which improves forecasting accuracy. This study summarizes essential issues about solar power forecasting, including potential training models, data processing, efficient weather classification, and other corresponding technologies. In addition, possible trends for solar power forecasts are also addressed.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Key Issues and Future Trends on Solar Power Forecasting\",\"authors\":\"Yuan-Kang Wu, Cheng-Liang Huang\",\"doi\":\"10.1109/ECICE55674.2022.10042953\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Owing to the effect of cloud, solar irradiance is intermittent and causes uncertainty in power system operations. Thus, accurate solar power forecasting helps system operators reduce the risk and cost of generator scheduling. Compared to wind power forecasting, solar power forecasting has a higher challenge because the prediction of solar irradiance is difficult. However, the curve of solar irradiance includes a daily pattern. Thus, statistical methods or deep learning models capture the important characteristics of solar power generation, which improves forecasting accuracy. This study summarizes essential issues about solar power forecasting, including potential training models, data processing, efficient weather classification, and other corresponding technologies. In addition, possible trends for solar power forecasts are also addressed.\",\"PeriodicalId\":282635,\"journal\":{\"name\":\"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECICE55674.2022.10042953\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECICE55674.2022.10042953","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Key Issues and Future Trends on Solar Power Forecasting
Owing to the effect of cloud, solar irradiance is intermittent and causes uncertainty in power system operations. Thus, accurate solar power forecasting helps system operators reduce the risk and cost of generator scheduling. Compared to wind power forecasting, solar power forecasting has a higher challenge because the prediction of solar irradiance is difficult. However, the curve of solar irradiance includes a daily pattern. Thus, statistical methods or deep learning models capture the important characteristics of solar power generation, which improves forecasting accuracy. This study summarizes essential issues about solar power forecasting, including potential training models, data processing, efficient weather classification, and other corresponding technologies. In addition, possible trends for solar power forecasts are also addressed.