Scientific journal paper Q2
Clustering of wind speed time series as a tool for wind farm diagnosis
Ana Alexandra A. F. Martins (Martins, A. A.); Daniel Cardoso Vaz (Vaz, D. C.); Tiago A. N. Silva (Silva, T. A. N.); Margarida G. M. S. Cardoso (Cardoso, M.); Alda Carvalho (Carvalho, A.);
Journal Title
Mathematical and Computational Applications
Year (definitive publication)
2024
Language
English
Country
Switzerland
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Abstract
In several industrial fields, environmental and operational data are acquired with numerous purposes, potentially generating a huge quantity of data containing valuable information for management actions. This work proposes a methodology for clustering time series based on the K-medoids algorithm using a convex combination of different time series correlation metrics, the COMB distance. The multidimensional scaling procedure is used to enhance the visualization of the clustering results, and a matrix plot display is proposed as an efficient visualization tool to interpret the COMB distance components. This is a general-purpose methodology that is intended to ease time series interpretation; however, due to the relevance of the field, this study explores the clustering of time series judiciously collected from data of a wind farm located on a complex terrain. Using the COMB distance for wind speed time bands, clustering exposes operational similarities and dissimilarities among neighboring turbines which are influenced by the turbines’ relative positions and terrain features and regarding the direction of oncoming wind. In a significant number of cases, clustering does not coincide with the natural geographic grouping of the turbines. A novel representation of the contributing distances—the COMB distance matrix plot—provides a quick way to compare pairs of time bands (turbines) regarding various features.
Acknowledgements
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Keywords
Time series,Wind data,Clustering,K-medoids,COMB distance,Visual interpretation tools,Wind farm diagnosis
  • Mathematics - Natural Sciences
  • Civil Engineering - Engineering and Technology
Funding Records
Funding Reference Funding Entity
UIDB/00667/2020 Fundação para a Ciência e a Tecnologia
UIDB/05069/2020 Fundação para a Ciência e a Tecnologia
UIDB/00315/2020 Fundação para a Ciência e a Tecnologia
UIDP/00667/2020 Fundação para a Ciência e a Tecnologia