Model of Capacity Demand under uncertain Weather
2010 (English)In: Proceedings IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), IEEE , 2010, 314-318 p.Conference paper (Refereed)
Load forecasting is important in the operation of power systems. The characteristics of the electrical energy consumption are analyzed and its variation as an effect of several weather parameters is studied. Based on historical weather and consumption data received from a distribution system operator (DSO), numerical models of load forecasting are suggested according to electrical power consumption and on daily peak power respectively. Two linear regression models are presented: simple linear regression (SLR) with one input variable (temperature) and multiple linear regressions (MLR) with several input variables. The models are validated with historical data from other years. For daily peak power demand a MLR model has the lowest error, but for prediction of energy demand a SLR model is more accurate.
Place, publisher, year, edition, pages
IEEE , 2010. 314-318 p.
climate, component, electrical distribution systems, energy consumtion, linear regression, load Forecasting, risk management, weather vulnerability
Other Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:kth:diva-33498DOI: 10.1109/PMAPS.2010.5528841ScopusID: 2-s2.0-77956428555OAI: oai:DiVA.org:kth-33498DiVA: diva2:415664
IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)
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QC 201107082011-07-082011-05-092012-02-23Bibliographically approved