Dissertação
Uma metodologia para identificação de perdas não técnicas em unidades consumidoras irrigantes de café do estado de São Paulo
Fecha
2022-07-29Autor
Sousa, Natalia Bastos de
Institución
Resumen
Within the rural network, several factors can influence the difficulty on the part of distributors
to locate fraudulent or irregular consumer units that may be causing non-technical losses, such
as, for example, the difficulty in correlating the consumption of their irrigating customers with
occurrences of divergent consumption. than expected, due to the necessary technical
knowledge about the characteristics of each type of crop. Thus, this dissertation aims to
present a methodology for detecting possible occurrences of non-technical losses for coffee
irrigating consumer units that are CPFL Paulista's clients. For this, the study of the
phenological characteristics of the coffee tree, management attributes of the irrigation system,
and agrometeorological data essential for consumption estimates was carried out. Mapping
the expected periods of irrigation system management, the clustering by Kmeans technique
was used to group the consumer units, generating classes of consumption profiles based on
their energy billing history and the period of billed energy registration (month). These classes
and consumption (monthly) relationships are used as input to the implementation of a
Random Forest model, used as the predictive model that classifies the units based on the most
current consumptions and compares the predicted class with the class stored in the database. .
The identification of customers that may be fraudulent occurs if the predicted class is of a
lower level than the expected class for the same observed month. Complementing the
methodology, since consumer units of lower classes would not change their Consumption
Profile in the event of lower energy consumption, the consumption estimation method was
used to detect possible occurrences of non-technical losses, comparing the real consumption
with the estimated. The classification predictive model was able to detect changes in
Consumption Profiles in a satisfactory way, and the estimation model shows that, for
consumer units in the coffee growing area of São Paulo, the irrigation method is still used in a
complementary way to the farm productivity.