Knowledge extraction from event-driven metering of electrical consumption patterns

Abstract

This paper discusses the conceptual and practical implications of adopting a new type of energy meter, based on the identification of events from measuring the power pattern and on sending information on the actual energy used in the time interval between two events. The event-driven metering (EDM) approach enables gathering data useful for setting up effective representations of the knowledge that can be extracted about the prosumers' energy usage during time. Specific comparisons between the EDM effectiveness in reconstructing the power patterns with respect to the classical time-driven metering at regular time intervals are introduced to show the remarkable advantages of the EDM approach. An enhanced average power pattern reconstruction mechanism is also presented, based on the direct reproduction of the average power at the fastest time step occurring before the event generation, and on averaging the power pattern for the remaining part of the corresponding time interval. The case study application is illustrated by using the highly variable power pattern of a residential user.