Wind energy must be commercially competitive to be economically sustainable. This project will look to increase wind turbine availability, reduce operational costs and reduce uncertainties around energy yield

Project Insights

  • €325,982

    Total Project Costs
  • 3 yr

    Project Duration
  • 2018

    Year Funded

Project Description

This project will improve operations & maintenance (O&M) of onshore wind turbine farms in Ireland through bespoke data analytics, focusing on early and accurate downtime prediction with significantly improved wind turbine power curve forecasts. Both will be transformative with real-time capabilities and adaptable to uncertain, imperfect or poor data. The project, a combination of feasibility study and demonstration, will use authentic, real-data from several wind farms in Ireland throughout, covering an entire range of manufacturers. The improved methodologies developed will be calibrated and implemented as a software for multiple wind farms and the improvement of O&M will be demonstrated along with its ability of replication, transferability and scalability. The results will form the most authoritative evidence base around the topic for Ireland and will be a global benchmark. The impact of the developed methods will be quantified for various energy market scenarios, especially keeping the Integrated Single Electricity Market (I-SEM) in mind. The project will demonstrably lead to increased wind turbine availability, reduction in operational costs and reduction in uncertainties around energy yield. Project outputs will include demonstrated comparison with existing industrial performance against proposed enhancement, extensive field trials, development of software and benchmark repository of performance achieved.

Project Details

Total Project Cost: €325,982

Funding Agency: SEAI

Year Funded: 2018

Lead Organisation: University College Dublin

Partner Organisation(s): Trinity College Dublin

Collaborators: WFSO Ltd; Electroroute

Vikram Pakrashi

Lead Researcher

Expertise: Structural Dynamics; Structural Health Monitoring Structural Reliability; Data Analytics; Infrastructure Maintenance and Management

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