{"title":"利用深度神经网络分析风电对电价的影响","authors":"Neeraj Kumar, M. M. Tripathi","doi":"10.1109/INDIACom51348.2021.00026","DOIUrl":null,"url":null,"abstract":"The Development scenario for renewable energy across the globe is changing rapidly in terms of capacity addition and grid interconnection. The impact of wind energy on electricity price is significant and it is an important task for power system planners to forecast the price in light of its variability. The impact of wind energy penetration on electricity price using Support Vector Regression (SVR) and Deep Neural Network (DNN) has been investigated for the Austria Electricity market. From the evaluation metrics calculation, it is observed that the DNN model performs better over SVR for the available dataset. The MAPE Value for DNN model was found 5.384 for the available dataset.","PeriodicalId":415594,"journal":{"name":"2021 8th International Conference on Computing for Sustainable Global Development (INDIACom)","volume":"33 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Impact Analysis of wind Energy on Electricity Price using Deep Neural Network\",\"authors\":\"Neeraj Kumar, M. M. Tripathi\",\"doi\":\"10.1109/INDIACom51348.2021.00026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Development scenario for renewable energy across the globe is changing rapidly in terms of capacity addition and grid interconnection. The impact of wind energy on electricity price is significant and it is an important task for power system planners to forecast the price in light of its variability. The impact of wind energy penetration on electricity price using Support Vector Regression (SVR) and Deep Neural Network (DNN) has been investigated for the Austria Electricity market. From the evaluation metrics calculation, it is observed that the DNN model performs better over SVR for the available dataset. The MAPE Value for DNN model was found 5.384 for the available dataset.\",\"PeriodicalId\":415594,\"journal\":{\"name\":\"2021 8th International Conference on Computing for Sustainable Global Development (INDIACom)\",\"volume\":\"33 3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 8th International Conference on Computing for Sustainable Global Development (INDIACom)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INDIACom51348.2021.00026\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 8th International Conference on Computing for Sustainable Global Development (INDIACom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDIACom51348.2021.00026","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Impact Analysis of wind Energy on Electricity Price using Deep Neural Network
The Development scenario for renewable energy across the globe is changing rapidly in terms of capacity addition and grid interconnection. The impact of wind energy on electricity price is significant and it is an important task for power system planners to forecast the price in light of its variability. The impact of wind energy penetration on electricity price using Support Vector Regression (SVR) and Deep Neural Network (DNN) has been investigated for the Austria Electricity market. From the evaluation metrics calculation, it is observed that the DNN model performs better over SVR for the available dataset. The MAPE Value for DNN model was found 5.384 for the available dataset.