{"title":"District Heating Simulation Model Development to Solve Optimization Problems in the Market Conditions","authors":"Aleksandrs Soročins, J. Nagla, V. Žentiņš","doi":"10.1109/RTUCON51174.2020.9316597","DOIUrl":null,"url":null,"abstract":"The paper reviews recent attempts to create and use district heating simulation by district heat companies to solve district heat network optimization problems in the market conditions. Today's market conditions determine a higher quality product to the consumer at the lowest possible prices. In order to fulfill such requirements, it is necessary to make accurate calculations, planning, and realization in life. District heat network model conformity level to reality determines the precision of planning and implementation of optimization solutions of district heat network in life. Creating of working district heat network model for simulations is a complex task where many parameters should be taken into account. In this paper, the authors examine mistakes and solutions of case study - district heat network model structure and it's conformity to the real object (5 biggest Latvian cities). Based on case study authors developed and offered methodology that provides minimal investment solutions to correctly create a model with the level of accuracy where the model can be used for correct simulations to perform a feasibility study for new consumer connection, heat load distributing between heat sources and implementing energy efficient events in interchangeability of heat supply/power supply/gas supply systems. By using the authors methodology it is possible to develop the correct district heating simulation model, analyze the conformity of the developed model to life, and determine the level of accuracy to perform the feasibility study.","PeriodicalId":332414,"journal":{"name":"2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTUCON51174.2020.9316597","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The paper reviews recent attempts to create and use district heating simulation by district heat companies to solve district heat network optimization problems in the market conditions. Today's market conditions determine a higher quality product to the consumer at the lowest possible prices. In order to fulfill such requirements, it is necessary to make accurate calculations, planning, and realization in life. District heat network model conformity level to reality determines the precision of planning and implementation of optimization solutions of district heat network in life. Creating of working district heat network model for simulations is a complex task where many parameters should be taken into account. In this paper, the authors examine mistakes and solutions of case study - district heat network model structure and it's conformity to the real object (5 biggest Latvian cities). Based on case study authors developed and offered methodology that provides minimal investment solutions to correctly create a model with the level of accuracy where the model can be used for correct simulations to perform a feasibility study for new consumer connection, heat load distributing between heat sources and implementing energy efficient events in interchangeability of heat supply/power supply/gas supply systems. By using the authors methodology it is possible to develop the correct district heating simulation model, analyze the conformity of the developed model to life, and determine the level of accuracy to perform the feasibility study.