Development of an intelligent and efficient disposition tool for interactive and dynamic task and ressource planning for offshore wind farms

The project's aim is to develop new planning strategies for requirement-meeting and efficient maintenance of offshore wind farms. It will be the first time, that task- and resource-management between spatially separated wind turbines is enabled under inconstant operating conditions and unplanned events. An issue-related and spatial visualization provides an objective decision basis for the operator's disposition directives and route optimization.

In order to grab the complexity of influencing factors as well as variables of offshore wind farms in a completely manner, a new approach has to be developed, based on mathematical constraints and specific heuristics. This will allow the inclusion of dynamic information, their immediate geographical mapping and visualization within the wind farm as well as an immediate generation of proposals for action concerning the disposition of maintenance tasks. Based on this the prerequisites will be created which allow dynamic scheduling management of maintenance tasks precisely tailored to the requirements of offshore wind farms. This is an important contribution to a reliable, efficient and more environmentally friendly operation of such infrastructure. In a second step the developed model is then implemented in a demonstrator software module for task and resource planning and validated in live field tests at an offshore wind farm. In addition to the reduction of qualitative deficits for the optimization of logistic processes, the projects outcome is a distinct minimization of logistic cost, as means of transportation are very expensive in offshore wind farms and usually represent a bottleneck. To date, there are no solutions on the market that can adequately represent and support the planning requirements in the complex technical environment of offshore wind farms. For this reason the operation of such wind farms underlies considerable qualitative and economic deficits.