Composite Index for Identifying Anomalies in Low Voltage Systems Using Smart Meter Measurement Data

Autor(es)

Rolim, Felipe B. B. ; Trindade, Fernanda C. L. ; Cunha, Vinicius C.

• Tipo de documento: Artigo Científico
• Fonte: IEEE OPEN ACCESS JOURNAL OF POWER AND ENERGY; v. 12, p. 12-pg., 2025-01-01.

Resumo

Smart meters are essential for distribution utilities as they provide valuable data that enable efficient management of distribution systems and informed decision-making processes. A critical application of this data is identifying abnormal system operations, such as non-technical losses and high impedance faults, which can affect power quality, safety, and utility revenue. However, there is currently no consensus on how to address these issues. This study proposes a composite index that uses smart meter data, and statistical concepts to simultaneously detect and locate anomalous system operations. This index is called the "Anomaly Intensity Index" and relies on tests that evaluate local and system-wide measurements, ranking customers according to the expected anomaly intensity. The proposed approach successfully identified abnormal demand as low as 0.2 kW per phase in test cases and estimated deviated energy with less than 1% error. (AU)

• Processo FAPESP: 21/11380-5 - CPTEn - Centro Paulista de Estudos da Transição Energética
• Beneficiário: Luiz Carlos Pereira da Silva
• Modalidade de apoio: Auxílio à Pesquisa - Centros de Ciência para o Desenvolvimento
• Processo FAPESP: 20/07103-3 - Detecção de anomalias em sistemas de distribuição de energia elétrica baseada na análise de dados de sensores e medidores inteligentes
• Beneficiário: Felipe Bayma Barbosa Rolim
• Modalidade de apoio: Bolsas no Brasil - Doutorado