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- Strain measurements of wind turbine support structures (1)
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Support structures of offshore wind turbines are subject to cyclic stresses generated by different time-variant random loadings such as wind, waves, and currents in combinationwith the excitation by the rotor. In the design phase, the cyclic demand on wind turbine support structure is calculated and forecasted with semi or fully probabilistic engineering models. In some cases, additional cyclic stresses may be induced by construction deviations, unbalanced rotor masses and structural dynamic phenomena such as, for example, the Sommerfeld effect. Both, the significant uncertainties in the design and a validation of absence of unforeseen adverse dynamic phenomena necessitate the employment of measurement Systems on the support structures. The quality of the measurements of the cyclic demand on the support structures depends on (a) the precision of the measurement System consisting of sensors, amplifier and data normalization and (b) algorithms for analyzing and converting data to structural health information. This paper presents the probabilistic modelling and analysis of uncertainties in strain measurements performed for the purposes of reconstructing stress resultants in wind turbine towers.
It is shown how the uncertainties in the strain measurements affect the uncertainty in the individual components of the reconstructed forces and moments. The analysis identifies the components of the vector of stress resultants that can be reconstructed with sufficient precision.
Due to the energy transition in Germany and the European Union, the relevance of renewable energy is steadily increasing. Besides hydropower and solar energy, offshore and onshore wind energy already forms a major part of renewables energies and will also be further expanded in the future (COMMISSION, 2020). In addition to the investments in the expansion of renewable energy, further research and development should focus on reducing the levelized cost of energy (LCoE) of wind energy to improve its market position.
The LCoE is the average net cost of electricity generated by a power plant that converts a certain type of energy into electrical power. The LCoE is estimated as the ratio of the discounted lifetime costs (i.e. capital expenditures (CAPEX) plus operational expenditures (OPEX)) to the discounted sum of the annual energy production (AEP) over its lifetime. For an offshore wind farm, the CAPEX contain the investment costs for the structures and remaining parts of the wind farm. The OPEX include the cost related to the structural integrity management (SIM) and the operation and maintenance of the remaining parts. The AEP is a function of the number of turbines, the nominal (turbine) capacity, the nominal capacity availability factor, the turbine availability, and the feed in tariff.
Several options are available to reduce the LCoE of a wind farm. For example, the energy production can be increased by increasing the turbine availability. Another option is to optimize the SIM and thus reduce the OPEX. To study the influence of SIM on the LCoE of a wind farm, we perform a variance-based sensitivity analysis of the LCoE (Saltelli et al., 2008). In this analysis, the importance of a given parameter influencing the LCoE is measured in term of its first-order sensitivity index, which quantifies the contribution the parameter to the variance of the LCoE. The CAPEX and OPEX are decomposed into costs related to the structures and costs associated to the remaining parts of the wind farm. The mean value of the CAPEX and OPEX related to the structures and the remaining parts are determined based on a literature study. The OPEX related to the structures are assumed to be in accordance with the requirements and regulations of German Hydrographic Authority (Hydrographie, 2015). They amount to 1.6% of the total OPEX for an average scenario (Martinez-Luengo and Shafiee, 2019).
The determined sensitivity indices for the parameters influencing the LCoE are shown (Figure 1). The nominal capacity, the nominal capacity availability factor, the turbine availability factor, and the feed in tariff have the highest (first-order) sensitivity indices. The CAPEX and OPEX for the wind turbine support structures have small sensitivity indices. It can be concluded that an optimization of the SIM may have negligible influence on the LCoE. However, an extension of the service life by means of structural health information (Thöns et al., 2017) may have an effect due to its reasonable influence on the LCoE .
In the present paper, an approach for updating the continuous stress range distribution of a welded connection of a wind turbine support structure with predicted information from strain measurements is presented. Environmental conditions, such as wind or, in offshore fields, waves and currents, in combination with rotor excitations generate cyclic stresses affecting the reliability of welded joints of the support structure over the service life. Using strain measurements, these conditions can be monitored, and the resulting stress ranges, under consideration of measurement, mechanical and material uncertainties, can be reconstructed. These stress ranges can be used as an input for updating the prior probability density function (PDF) of the stress ranges predicted by the overall dynamics and a detailed design analysis. Applying Bayesian probability theory and decision theoretical implications, the predicted posterior probability density of the stress ranges is calculated based on the design information and uncertainties. This approach is exemplified, and it is shown how the predicted stress ranges and the design stress ranges are distributed. The prior and the predicted posterior stress ranges are used for a reliability calculation for potentially entering a pre-posterior decision analysis
The levelized cost of energy (LCoE) is an important measure to quantify the macro-economic efficiency of an offshore wind farm and to enable a quantitative comparison with other types of energy production. The costs of the structural integrity management - which is required to ensure an adequate lifetime reliability of the turbine support structures - are part of the operational expenditures of an offshore wind farm. An optimization of the structural integrity management may reduce the operational expenditures and consequently the LCoE. However, the effect of the structural integrity management on the LCoE is hardly known. To investigate this effect, this paper presents a sensitivity analysis of the LCoE of a generic offshore wind farm. The probabilistic models of the parameters influencing the LCoE are based on a literature study including an explicit model for the structural integrity management.
The analysis reveals that LCoE may potentially be reduced if an optimization of the structural integrity management enables a service life extension.