M. M. Raja Paul, S. Amosedinakaran, A. Bhuvanesh, R. Kannan, M. Moses, A. Ramkumar
{"title":"Prediction of Tamil Nadu's Annual Electricity Consumption Using Adaptive Neuro-fuzzy network","authors":"M. M. Raja Paul, S. Amosedinakaran, A. Bhuvanesh, R. Kannan, M. Moses, A. Ramkumar","doi":"10.1109/C2I456876.2022.10051551","DOIUrl":null,"url":null,"abstract":"In this study, the electricity consumption is forecasted for 10 years from 2021 to 2030 using Adaptive Neuro Fuzzy Inference System (ANFIS) technique from the historical data. State GDP (State Gross Domestic Product), population and income rate are chosen as the independent input variables. In this study, four different model have been developed based on independent input variables for instance type A (State GDP, and population), type B (population and in-come rate), type C (State GDP and income rate) and type D (State GDP, population and income rate). The electricity consumption is the independent output variables for all the models. The different models have been developed to show the impact of independent input variables while predicting the electricity consumption. 3 scenarios are developed according with growth rates of input variables. The simulation results are verified with the National Electricity Plan (NEP) of India.","PeriodicalId":165055,"journal":{"name":"2022 3rd International Conference on Communication, Computing and Industry 4.0 (C2I4)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 3rd International Conference on Communication, Computing and Industry 4.0 (C2I4)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/C2I456876.2022.10051551","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this study, the electricity consumption is forecasted for 10 years from 2021 to 2030 using Adaptive Neuro Fuzzy Inference System (ANFIS) technique from the historical data. State GDP (State Gross Domestic Product), population and income rate are chosen as the independent input variables. In this study, four different model have been developed based on independent input variables for instance type A (State GDP, and population), type B (population and in-come rate), type C (State GDP and income rate) and type D (State GDP, population and income rate). The electricity consumption is the independent output variables for all the models. The different models have been developed to show the impact of independent input variables while predicting the electricity consumption. 3 scenarios are developed according with growth rates of input variables. The simulation results are verified with the National Electricity Plan (NEP) of India.