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Demand profile processing methodology for information acquisition

The demand profile knowledge is vital for a wide variety of power systems studies. Furthermore, meaningful information may be obtained regarding optimization and maximization decision-making strategies that may help a wide variety of consumers optimize their facilities usage, redefine low priorities equipment operating hours, as well as promote actions seeking production increase. With the spread of Smart Grids, this data is becoming easily available through the complete system range. Therefore, this study proposes a processing methodology that aims to make the information hidden at the load profile readily accessible at any level. For this sake, two processing stages are employed, first the profile is filtered by a Windowed Sinc filter and then a linearization process is performed. To validate the methodology high, average and low demand profiles from the Centre of Excellence in Smart Grids (CERIn) were considered. The results exhibit an efficient methodology capable of clearly provide meaningful information regarding the demand profiles.