For the purposes of the 'long' term forecasting, is the period any different than the short term's period? Are we really only changing the factors used to build the model in order to forecast the future load?
In addition, is the temperature data that was provided in the test set a forecast or the historical data? I see that the slides/pdf show that we would be using forecasts, but I wasn't sure if that was the case on the provided data.
In order to forecast the electricity price of the day ahead Dutch market I am using neural networks and real data from 2007-2011.
I constructed the X matrix as you said in the webinar for load forecasting and proved with different combinations. The one with gives me the lower MAPE value consists of 8 inputs (Hour dayOfWeek isWorkingDay prevWeekSameHourPrice prevDaySameHourPrice prev24HrAvePrice prevDayNGPrice prevWeekAveNGPrice), but I can't reduce this value more than 11%.
I need to achieve better accuracy but I don't know whar should I change. Could you send me an example of who to forecast the day ahead electricity price? My email is firstname.lastname@example.org
Thank you in advance.
Jose Francisco Bolado
I tried to run the loadscriptNN but everytime it went to fatal error. I needed to close the matlab.
I also tried to follow your webinar but there is an error in the fetchDBLoaddata. It said "Undefined function or method 'fetchDBLoadData' for input arguments of type 'char'". Please clarify this. Thank you.