Tim Rubert

Crack Monitoring of Operational Wind Turbine Foundations

The degradation of onshore, reinforced-concrete wind turbine foundations is usually assessed via above-ground inspections, or through lengthy excavation campaigns that suspend wind power generation. Foundation cracks can and do occur below ground level, and while sustained measurements of crack behaviour could be used to quantify the risk of water ingress and reinforcement corrosion, these cracks have not yet been monitored during turbine operation. Here, we outline the design, fabrication and field installation of subterranean fibre-optic sensors for monitoring the opening and lateral displacements of foundation cracks during wind turbine operation. We detail methods for in situ sensor characterisation, verify sensor responses against theoretical tower strains derived from wind speed data, and then show that measured crack displacements correlate with monitored tower strains. Our results show that foundation crack opening displacements respond linearly to tower strain and do not change by more than ±5 μm. Lateral crack displacements were found to be negligible. We anticipate that the work outlined here will provide a starting point for real-time, long-term and dynamic analyses of crack displacements in future. Our findings could furthermore inform the development of cost-effective monitoring systems for ageing wind turbine foundations.

Field Demonstration of Real-Time Wind Turbine Foundation Strain Monitoring

Onshore wind turbine foundations are generally over-engineered as their internal stress states are challenging to directly monitor during operation. While there are industry drivers to shift towards more economical foundation designs, making this transition safely will require new monitoring techniques, so that the uncertainties around structural health can be reduced. This paper presents the initial results of a real-time strain monitoring campaign for an operating wind turbine foundation. Selected reinforcement bars were instrumented with metal packaged optical fibre strain sensors prior to concrete casting. In this paper, we outline the sensors’ design, characterisation and installation, and present 67 days of operational data. During this time, measured foundation strains did not exceed 95 μϵ, and showed a strong correlation with both measured tower displacements and the results of a foundation finite element model. The work demonstrates that real-time foundation monitoring is not only achievable, but that it has the potential to help operators and policymakers quantify the conservatism of their existing design codes.

Preliminary characterization of metal-packaged fiber Bragg gratings under fatigue loading

This paper presents preliminary results for metal-packaged fiber Bragg grating strain and temperature sensors designed specifically for structural health monitoring in civil engineering applications. The laboratory experiments show that the in-house manufactured metal-packaged sensors are sufficiently resilient, under dynamic loading, to successfully undergo a million cycle fatigue test without adverse deterioration in performance. In addition, from the thermal characterization of the devices, a conclusion can be drawn that the metal-packaged sensors offer superior performance over sensors assembled using epoxy bonding. These early results are very promising, inspiring confidence in the adopted methodologies, and giving the mandate to proceed with more detailed laboratory testing to evaluate reliability and lifetime of the transducers in the future work.

Wireless concrete strength monitoring of wind turbine foundations

Wind turbine foundations are typically cast in place, leaving the concrete to mature under environmental conditions that vary in time and space. As a result, there is uncertainty around the concrete’s initial performance, and this can encourage both costly over-design and inaccurate prognoses of structural health. Here, we demonstrate the field application of a dense, wireless thermocouple network to monitor the strength development of an onshore, reinforced-concrete wind turbine foundation. Up-to-date methods in fly ash concrete strength and maturity modelling are used to estimate the distribution and evolution of foundation strength over 29 days of curing. Strength estimates are verified by core samples, extracted from the foundation base. In addition, an artificial neural network, trained using temperature data, is exploited to demonstrate that distributed concrete strengths can be estimated for foundations using only sparse thermocouple data. Our techniques provide a practical alternative to computational models, and could assist site operators in making more informed decisions about foundation design, construction, operation and maintenance.

Lifetime Extension Cost Database (6 x 900 kW Wind Farm)

This tool serves as an add-on for the following journal paper The Economics of Onshore Wind Turbine Lifetime Extension based on Levelised Cost of Energy in the UK in order to explore LCOE2 of the lifetime extension period by varying any combination of the mean wind speed, turbulence intensity, Cp_Max, and Weibull Shape Factor. Results are only valid for the LCOE model presented in the aforementioned journal paper.

The effect of upscaling and performance degradation on onshore wind turbine lifetime extension decision making

Ever greater rated wind turbine generators (WTGs) are reaching their end of design life in the near future. In addition, first research approaches quantified the impact of long-term performance degradation of WTGs. As a consequence, this work is aimed at discussing and analysing the impact of upscaling and performance degradation on the economics of wind turbine lifetime extension. Findings reveal that the lifetime extension levelised cost of energy (LCOE2) of an 18 MW wind farm comprising of 0.5 MW rated WTGs are within the order of £23.52 per MWh. Alternatively, if the same wind farm consists of fewer 2 or 3 MW WTGs, the LCOE2 reduces to £16.56 or £15.49 per MWh, respectively. Further, findings reveal that an annual performance degradation of 1.6% (0.2%) increases LCOE2 by 34-41% (3.6-4.3%).