Electricity industries around the world have significantly restructured in order to improve their economic efficiency, reliability of power systems and accountability. Accurate prediction of day-ahead electricity nodal price has now become an important activity to address the system operations and price volatility in the restructured electricity market. This will facilitate the market participa...

This paper develops hedging strategies for an electricity distributor in the Nordic electricity market who manages price and volume risk from fixed price agreements on stochastic electricity load. Whereas the distributor trades in the spot market at area prices, the financial contracts used for hedging are settled against the system price. Both the area price and the system price are correlated...

Under spot electricity pricing the price of electricity represents actual demand and supply equilibrium conditions and consumers respond to price variations so as to achieve the best cost-service tradeoff over a given time period. Using a decision modelling approach developed for prescribing consumer response to a varying electricity price, the case of space conditioning usage is analyzed in de...

This paper proposed a novel model for short term load forecast (STLF) in the electricity market. The prior electricity demand data are treated as time series. The model is composed of several neural networks whose data are processed using a wavelet technique. The model is created in the form of a simulation program written with MATLAB. The load data are treated as time series data. They are dec...

Forecasting electricity load is an important economic problem. Sometimes suited prediction methods are evaluated by benchmark scenarios, as in case of the world-wide competition within the EUNITE network. Here maximal daily electricity load has to be forecasted over a whole month given data of two years before. Because no formal model exists of how load depends on e.g. temperature or other envi...