{"title":"基于卷积和LSTM模型的电价预测","authors":"D. Mittal, Shaowu Liu, Guandong Xu","doi":"10.1109/BESC51023.2020.9348313","DOIUrl":null,"url":null,"abstract":"Electricity Market uses Demand and Supply chain strategy. Also, it is prone to random fluctuations that directly impact profit. Therefore forecasting demand becomes very important to mitigate the consequences of price dynamics. This paper proposes a Deep Learning model using Long Short Term Memory (LSTM) and Convolution Neural Network to forecast future electricity prices on the Australian electricity market and compares them with other state of the art models. We have selected evaluation metrics to prove that our model outperforms the other existing models for electricity price prediction.","PeriodicalId":224502,"journal":{"name":"2020 7th International Conference on Behavioural and Social Computing (BESC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Electricity Price Forecasting using Convolution and LSTM Models\",\"authors\":\"D. Mittal, Shaowu Liu, Guandong Xu\",\"doi\":\"10.1109/BESC51023.2020.9348313\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Electricity Market uses Demand and Supply chain strategy. Also, it is prone to random fluctuations that directly impact profit. Therefore forecasting demand becomes very important to mitigate the consequences of price dynamics. This paper proposes a Deep Learning model using Long Short Term Memory (LSTM) and Convolution Neural Network to forecast future electricity prices on the Australian electricity market and compares them with other state of the art models. We have selected evaluation metrics to prove that our model outperforms the other existing models for electricity price prediction.\",\"PeriodicalId\":224502,\"journal\":{\"name\":\"2020 7th International Conference on Behavioural and Social Computing (BESC)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 7th International Conference on Behavioural and Social Computing (BESC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BESC51023.2020.9348313\",\"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 7th International Conference on Behavioural and Social Computing (BESC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BESC51023.2020.9348313","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Electricity Price Forecasting using Convolution and LSTM Models
Electricity Market uses Demand and Supply chain strategy. Also, it is prone to random fluctuations that directly impact profit. Therefore forecasting demand becomes very important to mitigate the consequences of price dynamics. This paper proposes a Deep Learning model using Long Short Term Memory (LSTM) and Convolution Neural Network to forecast future electricity prices on the Australian electricity market and compares them with other state of the art models. We have selected evaluation metrics to prove that our model outperforms the other existing models for electricity price prediction.