Line Loss Prediction Model Design at Svenska kraftnät : Line Loss Prediction Based on Regression Analysis on Line Loss Rates and Optimisation Modelling on Nordic Exchange Flows

Abstract: Forecast and estimation on transmission line losses is a vital task in the daily operation and planning of the Swedish power system. The aim with this thesis is to design a new line loss prediction model at Svenska kraftnät (Svk), which provides a hourly forecast of the transmission line losses the next day for the Swedish bidding areas (SE1-SE4). The final goal is to reduce the additional cost related to inaccurate predictions. The developed model is based on regression analysis on historical line losses and estimated exchange flows between the adjacent bidding areas computed by linear programming. Simulation results for 2015 show that it is, with rather simple estimates and assumptions, possible to increase the prediction accuracy with up to 27% compared with the existing method and to reduce the related costs in a similar way. The study also shows that future modelling has potential to increase the precision even further and recommends a Neural Network approach as the next step.