{"title":"基于基本灰色预测模型的东盟电力消费预测","authors":"J. Kluabwang, Santipab Kothale, S. Yukhalang","doi":"10.1109/ICPEI47862.2019.8944952","DOIUrl":null,"url":null,"abstract":"Association of South-East Asia Nations or briefly called ASEAN is now operating among ten membership countries, Indonesia, Philippine, Singapore, Malaysia, Thailand, Myanmar, Lao, Cambodia, Vietnam and Brunei to enhance their people be well-being approach. Electricity plays an important role in many activities supporting these developments. To supply adequately and efficiently for demand requested can protect the electric power system blackout. This paper presented an application of traditional grey prediction model, GM(1,1), to study in forecasting the electricity consumption of ASEAN. Methodology applied here is to compare forecasting performance between summation of electricity from all ASEAN countries to be one series or separation of each country and then summing back at the end. All estimation and prediction has elaborated by using GM(1,1). International energy agency (IEA) provided useful data which is divided into two categories, first for modelling between year 2000 to 2012 and second for testing between year 2013 to 2016. The mean absolute percentage error (MAPE) was used to measure quality of the process when the smaller value of MAPE is shown, the higher accuracy is also obtained. Experimental results show that the summation method obtained its MAPEs of modelling and testing 0.67% and 2.43%, respectively, and otherwise, separation method had its average MAPEs in modelling 3.94% and testing 5.76%. As the results, the summation method can outperform the separation method and the winner forecasts that ASEAN will reach electricity consumption to 1,168.68 TWh in 2020.","PeriodicalId":128066,"journal":{"name":"2019 International Conference on Power, Energy and Innovations (ICPEI)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Using Basic Grey Prediction Model to Forecast Electricity Consumption of ASEAN\",\"authors\":\"J. Kluabwang, Santipab Kothale, S. Yukhalang\",\"doi\":\"10.1109/ICPEI47862.2019.8944952\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Association of South-East Asia Nations or briefly called ASEAN is now operating among ten membership countries, Indonesia, Philippine, Singapore, Malaysia, Thailand, Myanmar, Lao, Cambodia, Vietnam and Brunei to enhance their people be well-being approach. Electricity plays an important role in many activities supporting these developments. To supply adequately and efficiently for demand requested can protect the electric power system blackout. This paper presented an application of traditional grey prediction model, GM(1,1), to study in forecasting the electricity consumption of ASEAN. Methodology applied here is to compare forecasting performance between summation of electricity from all ASEAN countries to be one series or separation of each country and then summing back at the end. All estimation and prediction has elaborated by using GM(1,1). International energy agency (IEA) provided useful data which is divided into two categories, first for modelling between year 2000 to 2012 and second for testing between year 2013 to 2016. The mean absolute percentage error (MAPE) was used to measure quality of the process when the smaller value of MAPE is shown, the higher accuracy is also obtained. Experimental results show that the summation method obtained its MAPEs of modelling and testing 0.67% and 2.43%, respectively, and otherwise, separation method had its average MAPEs in modelling 3.94% and testing 5.76%. As the results, the summation method can outperform the separation method and the winner forecasts that ASEAN will reach electricity consumption to 1,168.68 TWh in 2020.\",\"PeriodicalId\":128066,\"journal\":{\"name\":\"2019 International Conference on Power, Energy and Innovations (ICPEI)\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Power, Energy and Innovations (ICPEI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPEI47862.2019.8944952\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Power, Energy and Innovations (ICPEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPEI47862.2019.8944952","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using Basic Grey Prediction Model to Forecast Electricity Consumption of ASEAN
Association of South-East Asia Nations or briefly called ASEAN is now operating among ten membership countries, Indonesia, Philippine, Singapore, Malaysia, Thailand, Myanmar, Lao, Cambodia, Vietnam and Brunei to enhance their people be well-being approach. Electricity plays an important role in many activities supporting these developments. To supply adequately and efficiently for demand requested can protect the electric power system blackout. This paper presented an application of traditional grey prediction model, GM(1,1), to study in forecasting the electricity consumption of ASEAN. Methodology applied here is to compare forecasting performance between summation of electricity from all ASEAN countries to be one series or separation of each country and then summing back at the end. All estimation and prediction has elaborated by using GM(1,1). International energy agency (IEA) provided useful data which is divided into two categories, first for modelling between year 2000 to 2012 and second for testing between year 2013 to 2016. The mean absolute percentage error (MAPE) was used to measure quality of the process when the smaller value of MAPE is shown, the higher accuracy is also obtained. Experimental results show that the summation method obtained its MAPEs of modelling and testing 0.67% and 2.43%, respectively, and otherwise, separation method had its average MAPEs in modelling 3.94% and testing 5.76%. As the results, the summation method can outperform the separation method and the winner forecasts that ASEAN will reach electricity consumption to 1,168.68 TWh in 2020.