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Shoreline Wind offers a suite of market-leading products that use intelligent data integration and simulation software to optimise and execute wind farm logistics, installation and field services strategies.



Break free from the limitations of customized ERP and maximize production capability and revenue with accurate and realistic full lifecycle modelling.



Vastly reduce manual input and costly human error by leveraging the power of automation to generate work orders, assign personnel and manage resources.



Achieve safer and more responsive operations and increase cross-collaboration among teams by connecting people and data across projects and lifecycle phases.



Save up to 10% OPEX by optimizing scheduling, replanning, dispatching and deployment with real-time complex field service scenario visualizations.



Optimised usage of maintenance data to reduce O&M costs.

Onshore and offshore wind power continues to pave the way for renewable energy with a record-setting global growth of more than 93 GW of new capacity installed in 2020. But still, this growth is insufficient if the wind industry needs to be on pace with the overall ambitions of reaching net-zero by 2050. However, to enable the industry to perform better, scale projects faster and expand capacity, wind project developers and OEMs need to operate efficiently.

A key step in enabling this is by enhancing data inputs and translating them into actionable maintenance tasks and activities. A proven method for reducing O&M costs is through Shoreline’s work order schedule optimisation framework and advanced data analytics, to start leveraging the full power of a digitalised offshore and onshore wind energy sector.

Wind turbine life expectancy and maintenance based on SCADA data

The requested levels of growth and expansion require that wind operators manage their assets in a more cost-efficient way. O&M costs are among the key financial barriers to increasing the scale of wind farm projects.

According to a IHS Markit report, O&M activities are estimated to cost between $42,000 – 46,000 on average during the first 10 years of operation on a wind turbine, and these costs will only increase as wind turbines age. Wind turbines are generally required to last approximately 20-25 years, with the highest rate of errors occurring in the earlier years. If wind OEM and wind operators are able to improve the life expectancy as well as reduce failure rates related to performance, then they will see significant financial benefits.

Many OEM’s and Wind Farm Operators use SCADA data for tracking and ensuring what maintenance activity is necessary. While it is possible to use this data as a single source for performing maintenance, SCADA data also has certain limitations for enabling higher efficiency:

  • Reactive measurements: Most SCADA data is programmed to alert on failures, lower performances or certain breaches in threshold. But this data serves a more reactive purpose and will already be too late to perform any preventive activities.
  • Data limitation: While SCADA data provides precise measurements of wind turbine performance and statuses, it has some data limitations. As most failures of wind turbines are tracked to originate from unknown or untracked events, it is difficult to determine the root cause of the failure.

The SCADA-based maintenance approach fails to give a complete overview of what causes downtime and what can be done to prevent an increase in downtime or higher costs.

An industry-intelligent framework for improving planning and execution of O&M tasks

So, what can a cloud-based system like Shoreline Wind do to improve the planning and execution of maintenance activities? Well, by enhancing the usage of data for efficient planning in order to reduce time to repair and the time spent on maintaining turbines thus reducing costs.

All wind farm maintenance will include planned and unplanned activities, however with Shoreline Wind’s simulation you can apply state-of-the-art machine learning to optimise how these activities are completed.

Compared to the SCADA-based strategy mentioned above, Shoreline Wind’s system can collect all data across multiple sources via its open API integration and combine this information with intelligent optimisation. Based on all these data inputs, the work schedule optimisation engine will automatically generate the most optimal O&M strategy for planning  and executing maintenance tasks. This allows operators, OEM’s and ISP´s to implement automated capabilities for easily creating work orders, assigning personnel and managing resources – all with limited manual handling, which reduces mistakes.

Whether we are discussing, planned maintenance or corrective maintenance, it is key that digital frameworks for O&M remain highly dynamic and flexible to any changes in planning. Wind farms are always prone to unforeseen adverse events or hazards, such as harsh weather conditions, that could cause downtime for both offshore and onshore wind farms. By removing rigid reporting and planning procedures, Shoreline Wind’s service solution for O&M enables fast and easy daily planning schedules as well as dispatching. Complex re-scheduling of tasks takes minutes instead of hours and revisions can quickly be adapted and changed in accordance with operational conditions.

Another key attribute to efficient maintenance planning is with comprehensive site and asset overviews. With the Shoreline Wind platform, you will gather a customisable and real-time dashboard overview of live weather, work status, performance, transport, and personnel. This allows OEM and wind operators to efficiently monitor and analyse the progress and status of each specific wind turbine, component, subassembly or equipment, and combine it with detailed and advanced data tracking capabilities.

All in all, by enhancing your data sources with an intelligent optimisation and planning framework – maintenance becomes an integral part of your daily automated work schedule planning for executing the most cost-efficient O&M strategy.

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