{"title":"一种实用的发电自动化神经网络方法","authors":"Mahmoud Moghavvemi, Soo Siang Yang, M. Kashem","doi":"10.1109/EMPD.1998.705543","DOIUrl":null,"url":null,"abstract":"This paper presents a practical artificial neural network (ANN) based technique for the automation of power generation scheduling based on the consumer's load profile. A multi-layered neural network with backpropagation learning algorithm is used to predict the required power generation to fulfill the consumer's demands. The proposed technique has been applied to a typical co-generation power plant of 4/spl times/8 MW rating. Test results indicates that the ANN model can automatically perform generator scheduling accurately.","PeriodicalId":434526,"journal":{"name":"Proceedings of EMPD '98. 1998 International Conference on Energy Management and Power Delivery (Cat. No.98EX137)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"A practical neural network approach for power generation automation\",\"authors\":\"Mahmoud Moghavvemi, Soo Siang Yang, M. Kashem\",\"doi\":\"10.1109/EMPD.1998.705543\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a practical artificial neural network (ANN) based technique for the automation of power generation scheduling based on the consumer's load profile. A multi-layered neural network with backpropagation learning algorithm is used to predict the required power generation to fulfill the consumer's demands. The proposed technique has been applied to a typical co-generation power plant of 4/spl times/8 MW rating. Test results indicates that the ANN model can automatically perform generator scheduling accurately.\",\"PeriodicalId\":434526,\"journal\":{\"name\":\"Proceedings of EMPD '98. 1998 International Conference on Energy Management and Power Delivery (Cat. No.98EX137)\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of EMPD '98. 1998 International Conference on Energy Management and Power Delivery (Cat. No.98EX137)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EMPD.1998.705543\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of EMPD '98. 1998 International Conference on Energy Management and Power Delivery (Cat. No.98EX137)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EMPD.1998.705543","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A practical neural network approach for power generation automation
This paper presents a practical artificial neural network (ANN) based technique for the automation of power generation scheduling based on the consumer's load profile. A multi-layered neural network with backpropagation learning algorithm is used to predict the required power generation to fulfill the consumer's demands. The proposed technique has been applied to a typical co-generation power plant of 4/spl times/8 MW rating. Test results indicates that the ANN model can automatically perform generator scheduling accurately.