{"title":"基于LEAP模型的中巴经济走廊能源发电项目建模与分析","authors":"Saba Ejaz, M. Aamir, M. A. Khan, Babar Ashfaq","doi":"10.1109/ICOMET.2018.8346410","DOIUrl":null,"url":null,"abstract":"In any developing economy, long term forecasting of energy demand and supply is important for planning the power projects. China-Pakistan Economic Corridor (CPEC) is a burning topic of fundamental research in energy projects due to reliance on energy imports and of sustainable development. This paper presents progress on the CPEC energy policies and an overview of energy demands & supplies to CPEC energy projects. An outline of the past developments in the energy projects in the Pakistan has been explained. Finally, Long-range Energy Alternatives Planning System (LEAP) model has been used for CPEC energy projects. In this paper, modeling and analysis of existing energy power projects and CPEC energy projects are performed using LEAP model and the results are compared. We have presented three scenarios that are Reference Scenario (RE), Coal Scenario (COA) and Renewable Scenario (REN) to forecast CPEC energy projects in LEAP that was performed from 2013 to 2030. Results indicated that Coal scenario is better while considering environmental and economic effects. This research is beneficial to the forecasting of the role of CPEC energy projects in order to meet high electrical energy in future here in Pakistan. Expected barriers to the change in the energy mix are discussed and are presented from predictable sources of renewable energy sources.","PeriodicalId":381362,"journal":{"name":"2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Modeling and analysis of CPEC energy power projects using LEAP model\",\"authors\":\"Saba Ejaz, M. Aamir, M. A. Khan, Babar Ashfaq\",\"doi\":\"10.1109/ICOMET.2018.8346410\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In any developing economy, long term forecasting of energy demand and supply is important for planning the power projects. China-Pakistan Economic Corridor (CPEC) is a burning topic of fundamental research in energy projects due to reliance on energy imports and of sustainable development. This paper presents progress on the CPEC energy policies and an overview of energy demands & supplies to CPEC energy projects. An outline of the past developments in the energy projects in the Pakistan has been explained. Finally, Long-range Energy Alternatives Planning System (LEAP) model has been used for CPEC energy projects. In this paper, modeling and analysis of existing energy power projects and CPEC energy projects are performed using LEAP model and the results are compared. We have presented three scenarios that are Reference Scenario (RE), Coal Scenario (COA) and Renewable Scenario (REN) to forecast CPEC energy projects in LEAP that was performed from 2013 to 2030. Results indicated that Coal scenario is better while considering environmental and economic effects. This research is beneficial to the forecasting of the role of CPEC energy projects in order to meet high electrical energy in future here in Pakistan. Expected barriers to the change in the energy mix are discussed and are presented from predictable sources of renewable energy sources.\",\"PeriodicalId\":381362,\"journal\":{\"name\":\"2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOMET.2018.8346410\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOMET.2018.8346410","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling and analysis of CPEC energy power projects using LEAP model
In any developing economy, long term forecasting of energy demand and supply is important for planning the power projects. China-Pakistan Economic Corridor (CPEC) is a burning topic of fundamental research in energy projects due to reliance on energy imports and of sustainable development. This paper presents progress on the CPEC energy policies and an overview of energy demands & supplies to CPEC energy projects. An outline of the past developments in the energy projects in the Pakistan has been explained. Finally, Long-range Energy Alternatives Planning System (LEAP) model has been used for CPEC energy projects. In this paper, modeling and analysis of existing energy power projects and CPEC energy projects are performed using LEAP model and the results are compared. We have presented three scenarios that are Reference Scenario (RE), Coal Scenario (COA) and Renewable Scenario (REN) to forecast CPEC energy projects in LEAP that was performed from 2013 to 2030. Results indicated that Coal scenario is better while considering environmental and economic effects. This research is beneficial to the forecasting of the role of CPEC energy projects in order to meet high electrical energy in future here in Pakistan. Expected barriers to the change in the energy mix are discussed and are presented from predictable sources of renewable energy sources.