Model of capacity demand under uncertain weather
Konferensbidrag (offentliggjort, men ej förlagsutgivet), 2010

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. © 2010 IEEE.

Linear regression

Risk management

Energy consumtion

Component

Load forecasting

Eelectrical distribution systems

Weather vulnerability

Climate

Författare

C.J. Wallnerström

Kungliga Tekniska Högskolan (KTH)

J Setréus

Kungliga Tekniska Högskolan (KTH)

P Hilber

Kungliga Tekniska Högskolan (KTH)

F Tong

Northwest Electric Power Design Institute

Lina Bertling Tjernberg

Chalmers, Energi och miljö, Elkraftteknik

2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2010

314-318

Ämneskategorier

Elektroteknik och elektronik

DOI

10.1109/PMAPS.2010.5528841

ISBN

978-142445723-6