• español
    • English
  • Login
  • English 
    • español
    • English

UniversidaddeCádiz

Área de Biblioteca, Archivo y Publicaciones
Communities and Collections
View Item 
  •   RODIN Home
  • Producción Científica
  • Capítulos de libro
  • View Item
  •   RODIN Home
  • Producción Científica
  • Capítulos de libro
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Chapter Forty-One: Part VII: Voltage Sags and Dips, Power Quality - Chapter Forty-One: A Power Quality Instrument for the Smart Grid Monitoring based on Higher-Order Statistics

Identificadores

URI: http://hdl.handle.net/10498/35189

DOI: 10.1049/PBPO222E_ch3. 2024

URL: https://www.cambridgescholars.com/product/978-1-5275-4530-4

Files
Acceso cerrado (338.1Kb)
Statistics
View statistics
Metrics and citations
 
Share
Export
Export reference to MendeleyRefworksEndNoteBibTexRIS
Metadata
Show full item record
Author/s
Florencias Oliveros, OliviaAuthority UCA; González de la Rosa, Juan JoséAuthority UCA; Agüera Pérez, AgustínAuthority UCA; Palomares Salas, José CarlosAuthority UCA; Sierra Fernández, José MaríaAuthority UCA
Date
2020-02-24
Department
Ingeniería en Automática, Electrónica, Arquitectura y Redes de Computadores
Source
Advances in Renewable Energies and Power Quality. p 802- 820
Abstract
This chapter proposes a virtual instrument for PQ assessment based on higher-order statistics. Accompanied by a new global index, the instrument implements a monitoring strategy that triggers a measurement procedure when an electrical fault is present and a local predefined threshold is surpassed. The method helps to classify events and continuous disturbances by tracking deviations in statistical parameters from their ideal steady-state values. Designed in LabVIEWTM, the user interface includes online graphs showing variance, skewness, and kurtosis, along with hybrid representations of variance versus the cited higher-order statistics. Based on a 50 Hz 100-signal battery, which gathers different types of electrical disturbances, the instrument was validated during online measurement sessions. Using stat-vs.-stat graphs that implement cycle-to cycle surveillance, results are depicted in 2D. The graphs show that voltage sags and transients can be classified within different clusters, with a low level of uncertainty. These visualization features allow the operator to view the relevant data objectively during an online monitoring session and, if needed, enhance the report with additional data, for example if they need to claim for economic losses and potential breaches of contract.
Subjects
higher-order statistics; power quality (PQ); power quality index; electronic instrumentation; virtual instrument; real-time monitoring
Collections
  • Capítulos de libro [1603]
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
This work is under a Creative Commons License Attribution-NonCommercial-NoDerivatives 4.0 Internacional

Browse

All of RODINCommunities and CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

LoginRegister

Statistics

View Usage Statistics

Información adicional

AboutDeposit in RODINPoliciesGuidelinesRightsLinksStatisticsNewsFrequently Asked Questions

RODIN is available through

OpenAIREOAIsterRecolectaHispanaEuropeanaBaseDARTOATDGoogle Academic

Related links

Sherpa/RomeoDulcineaROAROpenDOARCreative CommonsORCID

RODIN está gestionado por el Área de Biblioteca, Archivo y Publicaciones de la Universidad de Cádiz

Contact informationSuggestionsUser Support