A statistical analysis of sampling time and load variations for residential load aggregations

The electrical load in residential systems highly depends on various types of uncertainty due to the lifestyle of the residential customers. Enhancing the knowledge on the aggregated behavior of these customers is particularly important for the distribution system operator, also with the aim of determining the potential flexibility of the residential demand and setting up the economic terms of the electricity provision to the customers. This paper addresses the impact of the sampling time interval with which the customer data are gathered on the characteristics of the aggregated electricity demand. A dedicated statistical analysis has been carried out to highlight the load variations occurring for different numbers of aggregated extra-urban residential customers. The results are represented in the form of normalized percentage load variations, using the number of samples and the maximum demand variation to construct the normalizing factor. The results indicate how the sampling time interval affects the load variations for different levels of customer aggregation.

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