Abstract

Standard load profiles, which are representative load and generation profiles approved by regulators, are currently used for market balancing mechanism and network planning purpose. However it is observed that these profiles are not adapted to the current evolution of the power system in which consumers and distributed generation sources play a central role. Indeed standard load profiles are constructed statistically, using historical data, so their accuracy is directly related to the level of aggregation. Such profiles are representative for groups of 100 customers at least, thus they are not adapted to low voltage networks which contain small number of customers. Distribution system operators and other stakeholders are in need of appropriate models to represent a realistic load and generation behavior in many fields, such as home energy systems or local balancing mechanism. This paper provides a smart meter data based methodology to generate composite standard load profiles which more accurately matches the real load profiles from smart meters. The methodology provides a best standard load profile match for each day in the year. Best standard load profile matches are used to create the composite standard load profiles for one year. This methodology has been validated using the data-set from DG DemoNet Smart LV Grid project.

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