Abstract
The management of electricity consumption by household consumers requires multiple ways of consumer monitoring. One of these is the signature i(v) determined by monitoring the consumer voltage-current trajectory. The paper proposes a novel method for obtaining signatures of 2-multiple consumers, i.e., a pair of consumers connected in parallel. Signatures are obtained from samples of the voltage at the consumers’ terminals and of the total current absorbed by the consumers, measured at a frequency of only 20 Hz. Within the method, signatures are calculated using genetic algorithms (GA) and nonlinear regression, according to a procedure developed by the authors in a previous paper. The management of the data selected for the signature assignment represents the novelty. The method proposed in this paper is applied in two case studies, one concerning household consumers within the same power level, the other for household consumers of different power levels. The results confirm the possibility of obtaining signatures of i(v) type.
Highlights
Domestic consumption of electricity is increasing year after year, both by the diversity of household appliances and by their number
Selecting the subsets of points used to assign the signature; Associating the support function, choosing the fitness function, and setting up the support function for each branch separately, by nonlinear regression using genetic algorithms (GA); Validation of the solution calculated based on physical considerations
We consider below to case studies relating to two 2-m_c. Their relevance is given by the fact that in the case study 1 (CS1) the consumer consists of two consumers with power levels of the same size range, while case study 2 (CS2) consists of two consumers with power levels of different sizes
Summary
Domestic consumption of electricity is increasing year after year, both by the diversity of household appliances and by their number. A useful step in the reduction or the management of consumption as well as in the detection of events is the automatic generation of consumption maps, based on the identification of the consumers’ characteristics, including the household consumers. Three steps are taken in identifying consumers in general: the detection of an event, the recording of the power characteristics involved in defining the signature and the application of the classification/identification algorithm. In [13], the same author aims to detect several household consumers whose signatures were not included in the initial implementation of the classification/identification algorithm. In this case, the binary image of the voltage-current trajectory is considered the signature.
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