Ding Kai, Huaming Pan, Li Wei, Qian Yi-min, Wang Ying, Xia Xian-yong
{"title":"基于信息分布扩散理论的电压暂降经济损失预测","authors":"Ding Kai, Huaming Pan, Li Wei, Qian Yi-min, Wang Ying, Xia Xian-yong","doi":"10.1109/ICHQP46026.2020.9177916","DOIUrl":null,"url":null,"abstract":"Voltage sag brings economic losses that are difficult to measure for industrial users. The use of sag monitoring information and related indices for forecasting is the key to solving this problem. In order to realize the rapid and reasonable prediction of the losses results in the early stage of the event, this paper proposes a voltage sag economic losses prediction model based on information distribution and diffusion theory. Firstly, the method principle of information distribution and diffusion theory is explained. Based on the existing research, the severity of sag and economic losses are discussed. Then, considering the close causal relationship between them, the article established the fuzzy relationship between severity and economic losses based on information diffusion theory. Subsequently, the information distribution theory is used to fuzzify the severity index data, and the fuzzy relationship is used to predict the economic losses of existing samples. Finally, the actual data is analyzed, and the results show that the proposed method has less error in prediction results, and can provide data support and reference basis for user production decision quickly in the early stage of the event, which has important practical significance and application value.","PeriodicalId":436720,"journal":{"name":"2020 19th International Conference on Harmonics and Quality of Power (ICHQP)","volume":"184 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Prediction of Voltage Sag Economic Losses based on Information Distribution and Diffusion Theory\",\"authors\":\"Ding Kai, Huaming Pan, Li Wei, Qian Yi-min, Wang Ying, Xia Xian-yong\",\"doi\":\"10.1109/ICHQP46026.2020.9177916\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Voltage sag brings economic losses that are difficult to measure for industrial users. The use of sag monitoring information and related indices for forecasting is the key to solving this problem. In order to realize the rapid and reasonable prediction of the losses results in the early stage of the event, this paper proposes a voltage sag economic losses prediction model based on information distribution and diffusion theory. Firstly, the method principle of information distribution and diffusion theory is explained. Based on the existing research, the severity of sag and economic losses are discussed. Then, considering the close causal relationship between them, the article established the fuzzy relationship between severity and economic losses based on information diffusion theory. Subsequently, the information distribution theory is used to fuzzify the severity index data, and the fuzzy relationship is used to predict the economic losses of existing samples. Finally, the actual data is analyzed, and the results show that the proposed method has less error in prediction results, and can provide data support and reference basis for user production decision quickly in the early stage of the event, which has important practical significance and application value.\",\"PeriodicalId\":436720,\"journal\":{\"name\":\"2020 19th International Conference on Harmonics and Quality of Power (ICHQP)\",\"volume\":\"184 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 19th International Conference on Harmonics and Quality of Power (ICHQP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICHQP46026.2020.9177916\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 19th International Conference on Harmonics and Quality of Power (ICHQP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICHQP46026.2020.9177916","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Prediction of Voltage Sag Economic Losses based on Information Distribution and Diffusion Theory
Voltage sag brings economic losses that are difficult to measure for industrial users. The use of sag monitoring information and related indices for forecasting is the key to solving this problem. In order to realize the rapid and reasonable prediction of the losses results in the early stage of the event, this paper proposes a voltage sag economic losses prediction model based on information distribution and diffusion theory. Firstly, the method principle of information distribution and diffusion theory is explained. Based on the existing research, the severity of sag and economic losses are discussed. Then, considering the close causal relationship between them, the article established the fuzzy relationship between severity and economic losses based on information diffusion theory. Subsequently, the information distribution theory is used to fuzzify the severity index data, and the fuzzy relationship is used to predict the economic losses of existing samples. Finally, the actual data is analyzed, and the results show that the proposed method has less error in prediction results, and can provide data support and reference basis for user production decision quickly in the early stage of the event, which has important practical significance and application value.