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Optimizing Data Access for Wind Farm Control over Hierarchical Communication Networks
Author(s) -
Jacob Østergaard Madsen,
Mislav Findrik,
Tatiana K. Madsen,
Hans-Peter Schwefel
Publication year - 2016
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2016/5936235
Subject(s) - computer science , metric (unit) , controller (irrigation) , heuristic , telecommunications network , real time computing , packet loss , network packet , markov chain , performance metric , quality (philosophy) , distributed computing , computer network , machine learning , artificial intelligence , operations management , management , epistemology , philosophy , agronomy , economics , biology
We investigate a centralized wind farm controller which runs periodically. The controller attempts to reduce the damage a wind turbine sustains during operation by estimating fatigue based on the wind turbine state. The investigation focuses on the impact of information access and communication networks on the controller performance. We start by investigating the effects of a communication network that introduces delays in the information access for the central controller. The control performance as measured by accumulated fatigue is shown to be significantly impacted by communication delays and also by the choice of the time instances at which sensor information is accessed. In order to optimize the latter, we introduce an information quality metric and a mathematical model based on Markov chains, which are compared performance-wise to a heuristic approach for finding this parameter. This information quality metric is called mismatch probability, mmPr, and is used to express quantitatively the information accuracy in a given scenario. Lastly, measurements of different communication technologies have been performed in order to carry out the analysis in a practically relevant scenario with respect to the communication network delays. These measurements are done in regard to packet loss and communication delays, and the simulations are rerun using either the traces from the measurements or scenarios constructed from the delay parameters.

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