{"title":"基于地球同步卫星的太阳辐照度预报系统","authors":"Zhenzhou Peng, Shinjae Yoo, Dantong Yu, D. Huang","doi":"10.1109/SmartGridComm.2013.6688042","DOIUrl":null,"url":null,"abstract":"Solar irradiance variability, left unmitigated, will threat the stability of grid system, and might incur significant economical impacts. This paper focuses on a pipeline to predict solar irradiance from 30 minutes to 5 hours using geostationary satellite. It consists of two parts: cloud motion estimation and solar irradiance prediction using the estimated satellite images. The main challenge is image noise at all levels of processing from motion estimation to irradiance prediction. To overcome this problem, we propose to use optical flow motion estimation, and subsequently combine multiple evidences together using robust support vector regression (SVR). Our systematic evaluation shows significant improvements over the baseline in both motion estimation and irradiance prediction.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":"{\"title\":\"Solar irradiance forecast system based on geostationary satellite\",\"authors\":\"Zhenzhou Peng, Shinjae Yoo, Dantong Yu, D. Huang\",\"doi\":\"10.1109/SmartGridComm.2013.6688042\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Solar irradiance variability, left unmitigated, will threat the stability of grid system, and might incur significant economical impacts. This paper focuses on a pipeline to predict solar irradiance from 30 minutes to 5 hours using geostationary satellite. It consists of two parts: cloud motion estimation and solar irradiance prediction using the estimated satellite images. The main challenge is image noise at all levels of processing from motion estimation to irradiance prediction. To overcome this problem, we propose to use optical flow motion estimation, and subsequently combine multiple evidences together using robust support vector regression (SVR). Our systematic evaluation shows significant improvements over the baseline in both motion estimation and irradiance prediction.\",\"PeriodicalId\":136434,\"journal\":{\"name\":\"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"30\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SmartGridComm.2013.6688042\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SmartGridComm.2013.6688042","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Solar irradiance forecast system based on geostationary satellite
Solar irradiance variability, left unmitigated, will threat the stability of grid system, and might incur significant economical impacts. This paper focuses on a pipeline to predict solar irradiance from 30 minutes to 5 hours using geostationary satellite. It consists of two parts: cloud motion estimation and solar irradiance prediction using the estimated satellite images. The main challenge is image noise at all levels of processing from motion estimation to irradiance prediction. To overcome this problem, we propose to use optical flow motion estimation, and subsequently combine multiple evidences together using robust support vector regression (SVR). Our systematic evaluation shows significant improvements over the baseline in both motion estimation and irradiance prediction.