LogReview - Use of AIS data to optimize O&M logistics in offshore wind farms

Together with the Fraunhofer Institute for Wind Energy Systems (IWES), the Fraunhofer Center for Maritime Logistics and Services (CML) and Tractebel DOC Offshore GmbH, the Institute of Maritime Logistics (MLS) will evaluate AIS data from ships to analyze and optimize logistics processes for the operation and maintenance of offshore wind turbines. AIS (Automatic Identification System) is a radio system that continuously transmits the position, course and speed and other ship data (ship name, call sign, MMSI number, etc.) of the vessel concerned. The Institute of Maritime Logistics will be primarily responsible for the subproject "Application of AIS data for collision safety in the operational phase".

Project duration 01.07.2021-30.06.2024
Project funding funded by the German Federal Ministry for Economic Affairs and Energy (BMWi) on the basis of a resolution of the German Bundestag
Our status Project partner
Our status Jürgen Weigell
Project homepage https://www.enargus.de/pub/bscw.cgi/?op=enargus.eps2&q=logreviewq&v=10&s=10&id=4295449
Project partners The partners in the project consortium are the following:
 
  • Fraunhofer Institute for Wind Energy Systems (IWES)
  • Fraunhofer Center for Maritime Logistics and Services (CML)
  • Institute of Maritime Logistics (MLS)
  • Tractebel DOC Offshore GmbH (DOC)

Description

In the sub-project "Application of AIS data for collision safety in the operational phase" of the LogReview project, long-term position data of ships in and near offshore wind farms, recorded by the Automatic Identification System (AIS), are evaluated automatically. In addition to the automation of the near real-time evaluation, a special challenge is the large amount of data. By evaluating and analyzing the data, complex logistical processes during the operation of offshore wind farms are to be recorded, analyzed and optimized. In order to improve maritime safety and to increase the carbon footprint, the evaluation of AIS data can be used to draw conclusions about routes and about distances to other ships or stationary objects as well as about the operation and maintenance processes carried out. In this subproject, new methods for collision safety of ships with other ships or with stationary objects in the offshore wind farm or in the vicinity of an offshore wind farm will continue to be investigated. For the development of new models for collision prevention, the transfer to other areas of shipping as well as the analysis and processing of large amounts of data and their applications, both methods of machine learning and simulation are used. The subproject thus contributes significantly to the goal of the overall project "O&M Logistics Optimization in Operation" to develop a holistic, time series-based evaluation and optimization methodology for the operationally executed logistical processes in offshore wind farms.

This project is funded by the German Federal Ministry for Economic Affairs and Energy on the basis of a resolution of the German Bundestag under the funding code 03EE3051B. The responsibility for the content of this publication lies with the authors.

 

 

This project is funded by the Federal Ministry for Economic Affairs and Energy on the basis of a resolution of the German Bundestag under the funding code 03EE3051B. The authors are responsible for the content of this publication.