PhD Thesis - Energy Systems Research Unit - University of Strathclyde

the measured (e measured ) data of every time step t, normalised by the product of themean squared average of the measured data and the total number of time steps, t o .Mathematically this is shown in equation (2.4). The smaller the resulting NVF valuethe more accurate is the predicted modelled data.- (2.4)e measured is the normalised original data used to calculate the parameters in equation(2.1), that is, the actual data derived from the REMODECE database for allappliances, whilst e modelled is the output data after Stage 1 has been applied to e measured ,that is, the data derived from the assumed sinusoidal trend equation used in Stage 1.Although the NVF should be used to compare two independent datasets, in this casethe NVF is being used as a measure to quantify how closely the modelled datafollows the measured data. Using equation (2.4) the hourly NVF, that is, the measureof how each single modelled hour value compares to the measure data on a 12 monthperiod, was deduced. Table 2.8 shows the hourly NVF averaged over all 24 hours forall appliances, the maximum hourly NVF value for each appliance underinvestigation and the hour during which this maximum error value occurs.Table 2.8 - Hourly NVF for all appliancesApplianceHourly NVF averagedover all hoursMaximum HourlyNVF; (Hour occurring)Refrigerator 0.111 0.247; (23-24)Television 1.648 9.736; (4-5)Water Heater 0.677 2.548; (6-7)Lighting 0.507 1.066; (5-6)Electric Oven 3.580 18.917; (1-2)Microwave Oven 3.135 10.869; (0-1)Washing Machine 10.773 87.683; (5-6)Dish Washer 2.757 12.406; (5-6)Total General Consumption 0.282 0.648; (7-8)The low NVF values for refrigerators, lighting and electronic appliances and the high55