{"title":"利用机器学习进行中期能源需求分析:以孟加拉国某分区城市住宅公寓为例","authors":"Halima Haque, Md. Abdur Razzak","doi":"10.1109/GlobConHT56829.2023.10087732","DOIUrl":null,"url":null,"abstract":"Being the innovation, machine learning has indisputably dominated energy consumption prediction from home to the industry all over the world. Many approaches have been acknowledged throughout the past decade to upgrade the energy demand which is not an alien to Bangladesh. Moreover, the energy consumption has been classified according to the convenience for both builders as well as end-users. As a consequence, such analysis has led to short, medium, and long-term consumption concept in forecasting of energy. This paper explores the energy demand analysis using conventional machine learning models for medium-term energy consumption. It also reviews the detail possibilities of energy consumption along with challenges. A forecast of power consumption based on a dataset of a residential apartment for a year has been presented with related parameters and results. Even an anticipated energy management plan has been discussed for Bangladesh.","PeriodicalId":355921,"journal":{"name":"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Medium-term Energy Demand Analysis using Machine Learning: A Case Study on a Residential Apartment in a Divisional City of Bangladesh\",\"authors\":\"Halima Haque, Md. Abdur Razzak\",\"doi\":\"10.1109/GlobConHT56829.2023.10087732\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Being the innovation, machine learning has indisputably dominated energy consumption prediction from home to the industry all over the world. Many approaches have been acknowledged throughout the past decade to upgrade the energy demand which is not an alien to Bangladesh. Moreover, the energy consumption has been classified according to the convenience for both builders as well as end-users. As a consequence, such analysis has led to short, medium, and long-term consumption concept in forecasting of energy. This paper explores the energy demand analysis using conventional machine learning models for medium-term energy consumption. It also reviews the detail possibilities of energy consumption along with challenges. A forecast of power consumption based on a dataset of a residential apartment for a year has been presented with related parameters and results. Even an anticipated energy management plan has been discussed for Bangladesh.\",\"PeriodicalId\":355921,\"journal\":{\"name\":\"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)\",\"volume\":\"130 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GlobConHT56829.2023.10087732\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GlobConHT56829.2023.10087732","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Medium-term Energy Demand Analysis using Machine Learning: A Case Study on a Residential Apartment in a Divisional City of Bangladesh
Being the innovation, machine learning has indisputably dominated energy consumption prediction from home to the industry all over the world. Many approaches have been acknowledged throughout the past decade to upgrade the energy demand which is not an alien to Bangladesh. Moreover, the energy consumption has been classified according to the convenience for both builders as well as end-users. As a consequence, such analysis has led to short, medium, and long-term consumption concept in forecasting of energy. This paper explores the energy demand analysis using conventional machine learning models for medium-term energy consumption. It also reviews the detail possibilities of energy consumption along with challenges. A forecast of power consumption based on a dataset of a residential apartment for a year has been presented with related parameters and results. Even an anticipated energy management plan has been discussed for Bangladesh.