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Maintenance costs in offshore wind farms are one of the main reasons why it is still not competitive with its onshore counterpart. To lower the price of energy, the authors want to improve the modeling of offshore wind farms in order to help improving the applied maintenance strategies. In this paper, we investigate the repair of wind turbine components as an alternating renewal process. The time it takes to repair (renew) a component in a turbine, directly influences the downtime of this turbine, or even larger parts of the wind farm. This downtime leads to production losses, which in turn raise the cost of energy. Previous investigations by two of the present authors showed that a variation in repair times has a significant influence of the production losses. In Maintenance costs in offshore wind farms are one of the main reasons why it is still not competitive with its onshore counterpart. To lower the price of energy, the authors want to improve the modeling of offshore wind farms in order to help improving the applied maintenance strategies. In this paper, we investigate the repair of wind turbine components as an alternating renewal process. The time it takes to repair (renew) a component in a turbine, directly influences the downtime of this turbine, or even larger parts of the wind farm. This downtime leads to production losses, which in turn raise the cost of energy. Previous investigations by two of the present authors showed that a variation in repair times has a significant influence of the production losses. In this paper, an alternate renewal process is investigated as tool to calculate the influence of the repair time duration on the production losses. We show that if we assume an exponential distribution of repair times, the distribution of the downtimes can be calculated analytically. The results are demonstrated with a case study, based on available failure rates and repair times. For other distributions, the calculation has to be done numerically, after fitting the parameters of the distribution to the available data. Further work with other distributions and actual repair time distributions is planned. [ABSTRACT FROM AUTHOR]

The estimation of fatigue lifetime for an offshore wind turbine support structure requires a large number of time-domain simulations. It is an important question whether it is possible to reduce the number of load cases while retaining a high level of accuracy of the results. We present a novel method for simplified fatigue load assessments based on statistical regression models that estimate fatigue damage during power production. The main idea is to predict the total fatigue damage only and not also the individual damage values for each load case. We demonstrate the method for a jacket-type support structure. Reducing the number of simulated load cases from 21 to 3, the total fatigue damage estimate exhibited a maximum error of about 6% compared with the complete assessment. As a consequence, a significant amount of simulation time can be saved, in the order of a factor of seven. This quick fatigue assessment is especially interesting in the application of structural optimization, with a large number of iterations. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Stochastic representations of turbulent wind and irregular waves are used in time domain simulations of offshore wind turbines. The variability due to finite sampling of this input loading is an important source of simulation error. For the OC4 reference jacket structure with a 5 MW wind turbine, an error of 12-34% for ultimate loads and 6-12% for fatigue loads can occur with a probability of 1%, for simulations with a total simulation length of 60 min and various load cases. In terms of fatigue life, in the worst case, the lifetime of a joint was thereby overestimated by 29%. The size of this error can be critical, i.e., ultimate or fatigue limits can be exceeded, with probability depending on the choice of number of random seeds and simulation length. The analysis is based on a large simulation study with about 30,000 time domain simulations. Probability density functions of response variables are estimated and analyzed in terms of confidence intervals; i.e., how probable it is to obtain results significantly different from the expected value when using a finite number of simulations. This simulation error can be reduced to the same extent, either using several short simulations with different stochastic representations of the wind field or one long simulation with corresponding total length of the wind field. When using several short-term simulations, it is important that ultimate and fatigue loads are calculated based on the complete, properly combined set of results, in order to prevent a systematic bias in the estimated loads. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: Jacket substructures for offshore wind turbines show strong potentials in water depths from 25 up to 70m. A review of state-of-practice and enhanced state-of-the-art modeling of offshore wind turbine jackets is conducted regarding detailed joint properties. The state-of-the-art approach takes advantage of an accurate description of the local joint behavior by use of superelements, enabling more accurate load simulations. Studies conducted in the past highlighted both strong benefits as well as shortcomings of this approach, whereas the drawbacks were mainly related to the size of superelements and the application of local wave loading. This work develops a smart sizing for detailed joint models taking into account the loading and location of the jacket joints. A concept of local wave loading is presented as well. Advice on recommendable parameters is given and enables an optimized superelement application for jacket substructures. As an example the potential for fatigue load reduction is shown using the NREL offshore 5-MW baseline wind turbine and the OC4 reference jacket. The predicted fatigue lifetime was increased by about 15%. [Copyright &y& Elsevier]

Abstract: A multivariate Markov chain model is presented for generating sea state time series based on observed time series. The sea state is represented by the wave height, wind speed, wave period, wind direction and wave direction. Two ways of capturing the seasonal variation in the sea state parameters resulted in two distinct models. Their quality was assessed by comparing their statistical properties to what was obtained from observed time series. In one of the models (Model 1) transition probabilities were estimated separately for each month, while in the other (Model 2) a monthly transformation of the data were performed. Two different sea state data sets were considered in the validation, and it was found that both models compared favorably to the empirical data. It was concluded that Model 1 worked best for the longest data set considered, but was challenged by the shorter time series, where Model 2 worked best. Model 2 uses the observed data more efficiently, but relies on stationarity after removing the monthly variability. This seems to be a reasonable approximation for the data considered. The effect of changing the wave height resolution in the modeled time series was also investigated. [Copyright &y& Elsevier]

Abstract: An alternative support structure for offshore wind turbines is presented that removes the need for an expensive transition piece and allows for significant savings in steel weight. The concept is based on replacing both the traditional wind turbine tower and the usual support structure with a single lattice tower that extends from the sea bottom to the rotornacelle- assembly. An overview is given of studies performed and results obtained for this design so far, of its advantages and disadvantages, and of future plans for improved automatic optimization of the design. Although it is diffcult to show the economic viability of the full-height lattice tower concept, due to the general problem of reliably quantifying fabrication and installation costs, the major reduction in steel weight makes this an attractive concept that should be given further consideration, especially for future offshore projects in deep waters. [Copyright &y& Elsevier]

Abstract: This paper investigates two different approaches for individual pitch control for wind turbines. The first one is a gain scheduled decentralised control design and the second one is a robust H∞ loop shaping control design. Both controllers work well in the region above rated wind speed, exhibiting a response that is mostly independent of wind speed. The investigation is conducted based on the NREL 5MW benchmark wind turbine. Turbine modeling and control is conducted in FAST and Simulink. [Copyright &y& Elsevier]

ABSTRACT A simple method, based in the frequency domain, was developed for calculating the dynamic response of a stall-regulated wind turbine. Emphasis is placed on two aspects of the method, which are necessary in order to obtain a reasonable linearization of behavior when the blades are stalled. First, the tangential (in-plane) component of turbulence is included, in addition to the axial component. Second, the linearized relationship between lift coefficient and angle-of-attack is adjusted to account for the effects of dynamic stall: separate linearizations are used for excitation and damping of vibration. A thorough comparison is made between linear and non-linear dynamic-stall methods, with the conclusion that the accuracy of the linear method depends upon the frequency and amplitude of oscillation. The linear dynamic-stall method is accurate at blade vibrational frequencies, but it can be inaccurate at frequencies in the vicinity of 1P or below, when the angle-of-attack oscillates with an amplitude of 3° or more. Load spectra of a Nordtank 500 turbine, calculated using the frequency-domain method, are compared with measurements. The frequency-domain method provides estimates of load spectra and aerodynamic damping (stability) that are useful for preliminary design and optimization, but the method lacks sufficient accuracy and generality to be used for certification. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

We discuss aspects of biological relevance to the modelling of bio-computation in a multiset rewriting system context: turnover, robustness against perturbations, and the dataflow programming paradigm. The systems under consideration are maximally parallel and asynchronous parallel membrane systems, the latter corresponding to computation in which the notion of time is operationally meaningless. A natural geometrical setting which seems promising for the study of computational processes in general multiset rewriting systems is presented. Configuration space corresponds to a subset of the lattice ${\bf N}^d_0$, d ∈ N, and state transitions correspond to vector addition. The similarities and differences with Vector Addition Systems and Petri nets are discussed. Symbolic dynamics are introduced on special partitions of configuration space and we indicate different notions of complexity for membrane systems based on this and related concepts such as graph complexity and minimal automata. Some examples of synchronized, pipelined dataflow computations are given and decompositions into functional subunits are briefly commented on. [ABSTRACT FROM AUTHOR]