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Combining complex and disparate data sources to define and deploy leaner and smarter operational strategies to improve the performance of wind farms - Phase 2

Combining complex and disparate data sources to define and deploy leaner and smarter operational strategies to improve the performance of wind farms - Phase 2
结合复杂且不同的数据源来定义和部署更精简、更智能的运营策略,以提高风电场的性能 - 第 2 阶段
批准号:
105580
负责人:
金额:
$7.06万
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2019
资助国家:
英国
项目状态:
已结题
起止时间:
2019 至 --

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英文摘要
Natural Power is an independent renewable energy consultancy and service provider, headquartered in Scotland, with a vision to 'create a better environment'. We offer support and advice at all stages of a renewable energy project from the initial planning and development phase, through to providing assistance and expertise in operations and finally decommissioning and/or repowering of the assets. We are considered leaders in the field of operational services in onshore wind due to our holistic approach to renewable asset management, combining expertise from our analytics, asset management and servicing departments.To compete within a subsidy free marketplace both onshore and offshore wind farms in the UK need to reduce operational expenditure (OPEX) and hence reduce the overall levelised cost of energy (LCoE) of wind farm projects. In addition, to maximise returns on investments there is a drive to extend the life of operational assets and in order to do this the remaining useful life of the assets must be determined. Adopting a data driven approach is essential to ensure efficient decision making in these key areas.For the wind farms that Natural Power manage and service there is increased demand to provide leaner, smarter and more efficient services. To remain industry leading while being cost competitive it is essential that data are integrated into the decision-making process for the ongoing management of wind farms. An example of a success to date includes analysing data generated on common faults on turbines and combining our analysis and mechanical expertise to determine which faults can be automatically reset as opposed to being manually reset. This metric saves on average, seven hours of downtime per fault.Taking a data driven approach to wind farm operation will allow proactive maintenance to be undertaken at a time where the wind forecast is for low wind, reducing the overall financial impact of the turbine repair. This will also allow smart management of the site technicians to ensure they are targeting the areas which will have the biggest financial impact first. The main challenge is that the data are complex and disparate, as part of this project we are looking to combine data and analysis to produce actionable tasks.The knowledge gained from the data analytics not only benefits Natural Power but the entire industry since more electricity will available from renewable energy sources and this fits firmly with Natural Power's vision.
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