Spatio-temporal analysis of wind resource in the Iberian Peninsula with data-coupled clustering

被引:13
|
作者
Chidean, Mihaela I. [1 ]
Caamano, Antonio J. [1 ]
Ramiro-Bargueno, Julio [1 ]
Casanova-Mateo, Carlos [2 ]
Salcedo-Sanz, Sancho [3 ]
机构
[1] Univ Rey Juan Carlos, Dept Signal Theory & Commun, Madrid, Spain
[2] Univ Politecn Madrid, Dept Civil Engn Construct Infrastruct & Transport, Madrid, Spain
[3] Univ Alcala, Dept Signal Proc & Commun, Madrid, Spain
来源
关键词
Wind resource; Wind energy production; Spatio-temporal analysis; SODCC clustering; SPEED;
D O I
10.1016/j.rser.2017.06.075
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In this paper a spatio-temporal analysis of wind power resource in the Iberian Peninsula is presented. The study uses the Second-Order Data-Coupled Clustering (SODCC) algorithm over reanalysis data in the for the period 1979 - 2014. Several characteristics of the method are detailed, such as the data-coupled clustering approach of SODCC, that ensures the non-singularity of the signal subspace within each cluster. The performance of the proposed approach and specific results obtained have been discussed in a case study in the Iberian Peninsula. In these results it is possible to identify different spatio-temporal patterns of the wind data statistics depending on the initialization year. Moreover, this work also shows that there is a close relationship between these spatio-temporal patterns with the wind energy production of the area under study, so the proposed analysis can be extended to wind farms efficiency production at the time scales considered.
引用
收藏
页码:2684 / 2694
页数:11
相关论文
共 50 条
  • [21] Spatio-temporal clustering analysis and technological forecasting of nanotechnology using patent data
    Forestal, Roberto Louis
    Lee, Hsin Inn
    Pi, Shih-Ming
    Liu, Su-Houn
    [J]. TECHNOLOGY ANALYSIS & STRATEGIC MANAGEMENT, 2024, 36 (05) : 1037 - 1053
  • [22] Spatio-temporal dynamic clustering modeling for solar irradiance resource assessment
    Maldonado-Salguero, Patricia
    Carmen Bueso-Sanchez, Maria
    Molina-Garcia, Angel
    Miguel Sanchez-Lozano, Juan
    [J]. RENEWABLE ENERGY, 2022, 200 : 344 - 359
  • [23] Scalable Data-Coupled Clustering for Large Scale WSN
    Chidean, Mihaela I.
    Morgado, Eduardo
    del Arco, Eduardo
    Ramiro-Bargueno, Julio
    Caamano, Antonio J.
    [J]. IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2015, 14 (09) : 4681 - 4694
  • [24] Discovery of Patterns in Spatio-Temporal Data Using Clustering Techniques
    Aryal, Amar Mani
    Wang, Sujing
    [J]. 2017 2ND INTERNATIONAL CONFERENCE ON IMAGE, VISION AND COMPUTING (ICIVC 2017), 2017, : 990 - 995
  • [25] Dynamic model-based clustering for spatio-temporal data
    Lucia Paci
    Francesco Finazzi
    [J]. Statistics and Computing, 2018, 28 : 359 - 374
  • [26] Dynamic model-based clustering for spatio-temporal data
    Paci, Lucia
    Finazzi, Francesco
    [J]. STATISTICS AND COMPUTING, 2018, 28 (02) : 359 - 374
  • [27] Privacy preserving spatio-temporal clustering on horizontally partitioned data
    Inan, Ali
    Saygin, Yucel
    [J]. DATA WAREHOUSING AND KNOWLEDGE DISCOVERY, PROCEEDINGS, 2006, 4081 : 459 - 468
  • [28] Finding spatio-temporal patterns in climate data using clustering
    Sap, MNM
    Awan, AM
    [J]. 2005 INTERNATIONAL CONFERENCE ON CYBERWORLDS, PROCEEDINGS, 2005, : 155 - 162
  • [29] Spatio-temporal evolution of heat waves severity and expansion across the Iberian Peninsula and Balearic islands
    Diaz-Poso, Alejandro
    Lorenzo, Nieves
    Roye, Dominic
    [J]. ENVIRONMENTAL RESEARCH, 2023, 217
  • [30] Spatio-temporal changes (1956-2013) of coastal ecosystems in Southern Iberian Peninsula (Spain)
    Diez-Garretas, Blanca
    Comino, Olga
    Perena, Jaime
    Asensi, Alfredo
    [J]. MEDITERRANEAN BOTANY, 2019, 40 (01): : 111 - 119