A method for predicting consumer heat power usage was examined, for the purpose of implementing such a method in simulation models of the district heating distribution network at Stockholm Exergi. This was to enhance the results of such simulations and aid the company’s work with distribution optimization. A method based on power signatures, which are models currently used in many applications, was examined. The method aspired to describe the consumption patterns of consumers over time and temperature, categorize consumers according to these patterns and then implement the results in the simulation models. The addition of a time parameter to the signatures resulted in an improved and more consistent prediction quality. Categorizing the consumers mathematically caused only a minor decrease in the prediction quality and resulted in better prediction quality than the categorization system currently used. Stockholm Exergi is adviced to keep examining mathematical categorization of consumers as such a categorization has several advantages to the one currently used. It is also recommended to examine options to Termis for performing individual consumer predictions as the program is not well suited for it. Such options could be other software or add-ons to Termis which make such predictions more viable.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-355789 |
| Date | January 2018 |
| Creators | Stålnacke, Joakim |
| Source Sets | DiVA Archive at Upsalla University |
| Language | Swedish |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | UPTEC ES, 1650-8300 ; 18 033 |
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