0

Full Content is available to subscribers

Subscribe/Learn More  >

Understanding Wind Turbine Interactions Using Spatiotemporal Pattern Network

[+] Author Affiliations
Zhanhong Jiang, Soumik Sarkar

Iowa State University, Ames, IA

Paper No. DSCC2015-9784, pp. V001T05A001; 10 pages
doi:10.1115/DSCC2015-9784
From:
  • ASME 2015 Dynamic Systems and Control Conference
  • Volume 1: Adaptive and Intelligent Systems Control; Advances in Control Design Methods; Advances in Non-Linear and Optimal Control; Advances in Robotics; Advances in Wind Energy Systems; Aerospace Applications; Aerospace Power Optimization; Assistive Robotics; Automotive 2: Hybrid Electric Vehicles; Automotive 3: Internal Combustion Engines; Automotive Engine Control; Battery Management; Bio Engineering Applications; Biomed and Neural Systems; Connected Vehicles; Control of Robotic Systems
  • Columbus, Ohio, USA, October 28–30, 2015
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5724-3
  • Copyright © 2015 by ASME

abstract

This paper presents a data-driven modeling framework to understand spatiotemporal interactions among wind turbines in a large scale wind energy farm. A recently developed probabilistic graphical modeling scheme, namely the spatiotemporal pattern network (STPN) is used to capture individual turbine characteristics as well as pair-wise causal dependencies. The causal dependency is quantified by a mutual information based metric and it has been shown that it efficiently and correctly captures both temporal and spatial characteristics of wind turbines. The causal interaction models are also used for predicting wind power production by one wind turbine using observations from another turbine. The proposed tools are validated using the Western Wind Integration data set from the National Renewable Energy Laboratory (NREL).

Copyright © 2015 by ASME

Figures

Tables

Interactive Graphics

Video

Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In