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PhD Thesis - Energy Systems Research Unit - University of Strathclyde

PhD Thesis - Energy Systems Research Unit - University of Strathclyde

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the measuring period (2 weeks) to create one representative daily pr<strong>of</strong>ile <strong>of</strong> energydemand at an hourly time resolution representative <strong>of</strong> the whole month for eachappliance monitored; these are the base pr<strong>of</strong>iles to which the transformation processdescribed below is applied.2.4.2 Explaining the methodology – A three stage-processThe generation <strong>of</strong> synthetic, high resolution electrical demand data pr<strong>of</strong>iles for aparticular appliance type consists <strong>of</strong> a 3-stage transformation process, shownschematically in Figure 2.5.Fig. 2.5 - The three stage approachUsing a single REMODECE 1-day, hourly resolution appliance pr<strong>of</strong>ile as a startingpoint, 12 day-long pr<strong>of</strong>iles (one for each month <strong>of</strong> the year) at 1-minute resolutionare generated, that can also incorporate the effects <strong>of</strong> future appliances’ energyefficiencyimprovements. The specifics <strong>of</strong> the three stage process are as follows: Stage 1 – using one <strong>of</strong> the REMODECE datasets <strong>of</strong> a single appliance(comprising 1-day hourly resolution demand data for a single month <strong>of</strong> the year)as a starting point, the first transformation generates 12, 1-day hourly resolutionpr<strong>of</strong>iles, one for each month. This is achieved by applying a modifier function to43

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