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Estatística
Título: AUTOMATIC SELECTION OF MODELS FOR PANEL DATA: AN APPLICATION FOR SETTING NON-TECHNICAL LOSSES TARGETS OF BRAZILIAN ELECTRICITY DISTRIBUTION UTILITIES
Autor: EDUARDO TAKAMINE CORREIA
Colaborador(es): RODRIGO FLORA CALILI - Orientador
JOSE FRANCISCO MOREIRA PESSANHA - Coorientador
Catalogação: 16/JUN/2021 Língua(s): PORTUGUESE - BRAZIL
Tipo: TEXT Subtipo: THESIS
Notas: [pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio.
[en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio.
Referência(s): [pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=53283&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=53283&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.53283
Resumo:
Non-technical electricity losses (NTL) are currently one of the main problems faced by electricity distribution utilities in Brazil. It is understood that part of these factors is not manageable by the utilities, and thus, they are passed on to consumers through electricity tariffs, following the limits defined by the Brazilian Electric Energy Agency (ANEEL). Despite the progress made by ANEEL, the methodology currently used by the Agency uses panel data to formulate these limits, however, some ad hoc measures are defined which end up resulting in loss targets that are not consistent with the reality of Brazilian distribution utilities. This dissertation aims to select models automatically for panel data, evaluating their applicability in setting non-technical loss targets. The proposed models were used in a panel data containing annual observations from 62 Brazilian electricity distribution utilities in the period from 2007 to 2017, thus generating 1,097,789 models with respect to the types of regressions in panel data, resulting in 3 potential models with NTL targets more adherent to the real possibilities of the Brazilian distribution utilities.
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