Mixed-Integer Linear Programming (MILP) Approach for Solving Derating Problems in Optimization of Thermal Power Plants Operation Considering Primary Energy Uncertainty
{"title":"Mixed-Integer Linear Programming (MILP) Approach for Solving Derating Problems in Optimization of Thermal Power Plants Operation Considering Primary Energy Uncertainty","authors":"Nur Fauziyah, N. Hariyanto","doi":"10.1109/ICPEA56918.2023.10093175","DOIUrl":null,"url":null,"abstract":"Electricity has an important role in economic development and people’s lives in a country. As the population increases, so does the demand for electricity, resulting in the problem of shortages of electricity supply which leads to huge economic losses. The important problem to be considered is the primary energy used to produce electricity, especially coal, one of the primary energies of thermal power plants where coal availability has a contribution to the non-optimal scheduling of thermal power plants operation which causes the derating problems. This paper proposes a new algorithm with combining algorithms of unit commitment and economic dispatch, coal transshipment, coal blending and inventory problems which will be implemented using Pyomo based on Python programming language with Mixed Integer Linear Programming (MILP) approach. The new algorithm is used to determine the optimal time for coal delivery and maintenance of power plants according to coal inventory. The results showed that the addition of this new algorithm provides 5.57% cheaper and more optimal power plants operation cost.","PeriodicalId":297829,"journal":{"name":"2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPEA56918.2023.10093175","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
Electricity has an important role in economic development and people’s lives in a country. As the population increases, so does the demand for electricity, resulting in the problem of shortages of electricity supply which leads to huge economic losses. The important problem to be considered is the primary energy used to produce electricity, especially coal, one of the primary energies of thermal power plants where coal availability has a contribution to the non-optimal scheduling of thermal power plants operation which causes the derating problems. This paper proposes a new algorithm with combining algorithms of unit commitment and economic dispatch, coal transshipment, coal blending and inventory problems which will be implemented using Pyomo based on Python programming language with Mixed Integer Linear Programming (MILP) approach. The new algorithm is used to determine the optimal time for coal delivery and maintenance of power plants according to coal inventory. The results showed that the addition of this new algorithm provides 5.57% cheaper and more optimal power plants operation cost.