Research
In order to implement the Reliawind project it has been divided into different work packages (WP). The overall co-ordination of the entire project is run under WP-0. In this, responsibility is taken to provide support for the smooth management of the project, follow up of the progress and reporting upon it as well as organizing the project’s kick-off meeting as well as the other meetings of the project’s General Assembly. The contents of the other six work packages and expected deliverables from each are briefly described below
WP-1: Field Reliability Analysis. Identify Critical Failures and Components
Leader: GL Garrad Hassan, UK
Within any complex system, certain components will stand out as high-risk items, either because they are ‘weak points’ that are failure prone, or are absolutely essential for “normal” turbine operation, or are expensive and time-consuming to diagnose and repair.
The aim is to capture, collect, and analyze historical wind farm SCADA (Supervisory Control and Data Acquisition) datalogs and maintenance data from several sources available to the project partners to determine which components and failure modes should be subject to a more detailed work during next project phases.
Therefore, based on an empirical analysis, the deliverables of this WP are expected to be determination and identification of the “high risk items” and failure modes.
WP-2: Design for Reliability. Understand Failures and Their Mechanisms
Leader: Relex, Italy
Understanding the failure modes, their mechanisms and the physical and chemical magnitudes and variables that are involved in the phenomena allows scientists to construct logical models of failure mode growth and propagation, both in two scenarios: Within the WTG architecture and along time. These reliability models will contribute to the main project objectives in two ways: 1) Design for Reliability and 2) Condition Monitoring. Each industrial partner will construct in a coordinated fashion its applicable subsystems and component functional and reliability models and one SME partner, acting as model integrator, will assemble all previous “building blocks” in order to attain a complete full WTG reliability model.
Deliverables of this WP are expected to be the selection and specification of appropriate sensing devices for capturing the aforementioned physical and chemical magnitudes. Signals coming from these devices will later act as inputs to the logical algorithms defined in WP3.
WP-3: Algorithms. Define the Logical Architecture of an Advanced WTG Health Monitoring System
Leader: SZTAKI, Hungary
The aim is to define and integrate all the logic required to convert input signals (more than a hundred in a normal WTG) into appropriate actions. State of the art advanced expert systems and architectures will be used to detect actual failures, isolate these failures and assign them to a specific component.
Deliverables of this WP are expected to be the determination of the residual life of components experiencing impending failures, definition of maintenance actions to be taken, scheduling of these actions in an optimum sequence and, finally, provision of support for maintenance technicians and managers to make the most adequate decisions concerning maintenance policies.
WP-4: Proof of concept. Demonstrate the Principles of the Project Findings
Leader: Gamesa, Spain
All the results achieved during previous work packages will be integrated into a consistent set of tools and applications that can provide Condition Based Maintenance tools for wind turbines and wind farms. Existing protocols and standards for connectivity to current SCADA systems will be adopted and new extensions will be proposed to benefit from the findings of the project.
Deliverables of this WP are expected to be a consistent set of maintenance tools and the definition of specific software components to integrated in an extensible software framework to create a multi-agent software platform to simulate each possible turbine operational condition and WTG configuration to be modelled. An holistic wind farm software model (virtual demonstrator) is expected to be built and tested in order to verify and show the principles achieved by the project.
WP-5: Training. Train internal and external partners
Leader: Durham University, UK
The aim is to provide training to the partners and other stakeholders (directly involved in wind turbine design, operation and maintenance) about the reliability, modelling and information tools needed to enable a more reliability-minded approach to be applied in the future to these activities.
Deliverables from this WP are expected to be fully up-to-date trained engineers and researchers in the light of the expected new results in wind energy systems design, operation and maintenance.
WP-6: Dissemination. Conferences, Workshops, Web Site and Media
Leader: Durham University, UK
The aim is to disseminate the findings to the Wind Energy Sector community in the European Union (e.g. wind farm promoters, regulatory bodies, financers, insurers, certification bodies, government bodies, associations, etc.). This will be achieved through a variety of Conference, Workshop, Web site and Media initiatives. In this respect the experiences in the offshore oil and gas industry to disseminate methods to improve plant reliability will be emulated.
Deliverables from this WP are expected to be the successful organisation of conference, workshop, website and media initiatives to ensure optimal dissemination of the results of the Reliawind project.