{"title":"A risk management model for carbon constrained coal inventory optimization","authors":"Jiajia Yang, Junhua Zhao, F. Wen, Z. Dong","doi":"10.1109/APPEEC.2015.7380888","DOIUrl":null,"url":null,"abstract":"Based on risk management theory, a nonlinear programming model for optimizing the coal inventory is developed by taking the CVaR as a risk measuring index while considering the coal-fired power plant's carbon emission constraint and the cost of purchasing a CO2 quota. In the developed model, the objective is to minimize CVaR under a given expected profit. Some uncertain factors are taken into account such as coal price, the electricity price, coal consumption, fill rates of contracted coal and coal purchased from the coal market. Then, the developed optimization model is transformed into a linear programming problem so as to improve the computational efficiency. Finally, a case study is employed to demonstrate feasibility and efficiency of the model built, and an algorithm developed.","PeriodicalId":439089,"journal":{"name":"2015 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APPEEC.2015.7380888","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Based on risk management theory, a nonlinear programming model for optimizing the coal inventory is developed by taking the CVaR as a risk measuring index while considering the coal-fired power plant's carbon emission constraint and the cost of purchasing a CO2 quota. In the developed model, the objective is to minimize CVaR under a given expected profit. Some uncertain factors are taken into account such as coal price, the electricity price, coal consumption, fill rates of contracted coal and coal purchased from the coal market. Then, the developed optimization model is transformed into a linear programming problem so as to improve the computational efficiency. Finally, a case study is employed to demonstrate feasibility and efficiency of the model built, and an algorithm developed.