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Publikācija: Short-Term Forecasting of District Heating Demand

Publication Type Full-text conference paper published in conference proceedings indexed in SCOPUS or WOS database
Funding for basic activity Research project
Defending: ,
Publication language English (en)
Title in original language Short-Term Forecasting of District Heating Demand
Field of research 2. Engineering and technology
Sub-field of research 2.2 Electrical engineering, Electronic engineering, Information and communication engineering
Authors Romāns Petričenko
Dmitrijs Soboļevskis
Antans Sauļus Sauhats
Keywords energy market, district heating, cogeneration, forecasting, error analysis
Abstract Focus of the paper is statistical data pre-processing before it applies for prediction the thermal load in district heating networks, focusing on day-ahead hourly planning. Such a planning is highly important for cogeneration plants participating in electricity wholesale markets. Article considers the possibility of correcting detected inconsistencies into district heating statistical data using forecasted values of the heat demand. The case study is based on the examples of heat supply of a large city, gas fired cogeneration power plants and real world data. The cost of errors in the prediction of heat consumption is estimated.
DOI: 10.1109/EEEIC.2018.8494362
Hyperlink: https://ieeexplore.ieee.org/document/8494362 
Reference Petričenko, R., Soboļevskis, D., Sauhats, A. Short-Term Forecasting of District Heating Demand. In: 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe 2018), Italy, Palermo, 12-15 June, 2018. Piscataway, NJ: IEEE, 2018, pp.807-812. ISBN 978-1-5386-5187-2. e-ISBN 978-1-5386-5186-5. Available from: doi:10.1109/EEEIC.2018.8494362
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ID 28465