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WindEurope: Analysis of Operating Wind Farms Conference 2018.

Key details

15 May - 16 May 2018

About the event

While wind power costs have been increasingly competitive over the past years, it is still essential to improve the overall performance of the technology, and the growing use of big data in wind power assets operations and maintenance is going to be a major part of that. For this reason, the 2018 edition of Analysis of Operating Wind Farms will focus on big data and innovative approaches to boost performance and optimise O&M strategies.  

In order to achieve their desired production and revenue goals, wind farm operators must understand and manage the performance analysis of wind farms. The programme will address new insights and improved operations technology which are needed to increase efficiency and profits, essential for wind energy companies that have recently experienced swinging national energy policies.

LR presenting


Speaker: Nathan Hill, Specialist - Energy Resource Services

SESSION 4, Part 1 - Post-construction yield analysis and reanalysis
Reconciling the past with the present: the impact of developments in reanalysis data on pre- and post-construction yield analysis

The study focusses on four primary reanalysis sources, MERRA, MERRA-2, ERA-Interim and ERA 5. A comparison is made with known consistent reference sources across the globe in order to benchmark each source's performance and further understand how this performs over time. The results and conclusions made enable an increased level of understanding of the accuracy of each of the reanalysis data sources – and how bias varies over time and geographical location. Project owners, investors and consultants working on those projects will be able to better benchmark their asset performance based on the presented insights into long-term wind trends.


PO.42: Active maintenance optimisation of a large offshore wind farm based on mesoscale day-ahead power forecasts.

Presenter: Ken Tay, Research Engineer
The scheduling of planned maintenance for offshore wind farms often does not take into account the value of the energy lost whilst maintaining individual wind turbines. Typical strategies involve the use of a passive scheduling strategy : this work demonstrates that the passive approach is inefficient based on real offshore wind farm data and quantifies the benefit of active optimisation strategies. We developed a methodology to actively schedule maintenance activities based on a day-ahead power forecast.

PO.37: Optimising the performance of a small wind farm through wind turbine power modes.

Presenter: Matthew Zhang, Specialist - Energy Resource Services
Using power modes within the wind turbine controller, this study attempts to optimise the performance of a small onshore wind farm without significant changes of the control system, or any risk of increased loading or significant production losses due to alternative strategies such as wake bending and wind sector management. Following an analysis of the operational SCADA data, the tuning of the wake model and an understanding of the power modes already specified within the control system, several different configurations are analysed.

PO.04: Visualisation and automation, data to decisions.

Presenter: Matthew Zhang, Specialist - Energy Resource Services
Through working with wind farm owners, it has become clear that improvements in performance are hampered by limited access to comprehensive turbine operational and contextual information. New software tools developed enabled both an increase in revenue from electricity generated and a reduction in operational costs, due for instance to on-site interventions. We have succeeded in automating the display of key relationships and combination of data and trained data science tools so as to automate the process of diagnosis and simulation of future operation.

Video: technical insights from LR's energy resource experts.

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