High Specification Offshore Blades. Work Package: 1C – Blade Materials.

Blades are regarded as the only component unique to wind turbine blades. They represent only 10 – 15% of the total system cost so the perception is that a reduction in the cost of energy through blade cost improvements is constrained. However, the use of novel materials technologies is predicted to reduce design loading by 10 – 20%, which may indirectly lead to substantial cost savings. The aim of this report is therefore to identify materials technologies offering potential for improved blade performance and their potential for (patentable) intellectual property exploitation

Active sensor fault tolerant output feedback tracking control for wind turbine systems via T-S model

This paper presents a new approach to active sensor fault tolerant tracking control (FTTC) for offshore wind turbine (OWT) described via Takagi–Sugeno (T–S) multiple models. The FTTC strategy is designed in such way that aims to maintain nominal wind turbine controller without any change in both fault and fault-free cases. This is achieved by inserting T–S proportional state estimators augmented with proportional and integral feedback (PPI) fault estimators to be capable to estimate different generators and rotor speed sensors fault for compensation purposes. Due to the dependency of the FTTC strategy on the fault estimation the designed observer has the capability to estimate a wide range of time varying fault signals. Moreover, the robustness of the observer against the difference between the anemometer wind speed measurement and the immeasurable effective wind speed signal has been taken into account. The corrected measurements fed to a T–S fuzzy dynamic output feedback controller (TSDOFC) designed to track the desired trajectory. The stability proof with H∞ performance and D-stability constraints is formulated as a Linear Matrix Inequality (LMI) problem. The strategy is illustrated using a non-linear benchmark system model of a wind turbine offered within a competition led by the companies Mathworks and KK-Electronic

Performance prediction of wind turbines utilizing passive smart blades: approaches and evaluation

The induced deformation, because of the presence of elastic coupling in the structure of passive smart blades, is the key parameter that affects the wind turbine aerodynamic performance, namely rotor mechanical power and blade loading. Therefore, in order to determine the aerodynamic performance of these turbines, a structural analyser is also required to bring the effect of the induced deformation into account. When predicting the rotor mechanical power, additional complexity arises when the blades are bend-twist-coupled. In this case, an iterative coupled-aero-structure analysis must be carried out at each given wind speed. Further difficulties in simulation of these turbines are posed by the fact that the current analytical models for analysis of structures made of anisotropic composite materials are not accurate enough. This differentiates the numerical simulation of wind turbines utilizing passive smart blades from the simulation of wind turbines with conventional blades. Different strategies have been proposed and followed by investigators in simulation of wind turbines utilizing passive smart blades. These methods can be categorized by the approach adopted in treating the torsional-induced deformation. In these studies, the induced twist has been predicted, planned or a combination of both. The present paper describes, evaluates and compares these approaches

Nonlinear Dual-Mode Control of Variable-Speed Wind Turbines with Doubly Fed Induction Generators

This paper presents a feedback/feedforward nonlinear controller for variable-speed wind turbines with doubly fed induction generators. By appropriately adjusting the rotor voltages and the blade pitch angle, the controller simultaneously enables: (a) control of the active power in both the maximum power tracking and power regulation modes, (b) seamless switching between the two modes, and (c) control of the reactive power so that a desirable power factor is maintained. Unlike many existing designs, the controller is developed based on original, nonlinear, electromechanically-coupled models of wind turbines, without attempting approximate linearization. Its development consists of three steps: (i) employ feedback linearization to exactly cancel some of the nonlinearities and perform arbitrary pole placement, (ii) design a speed controller that makes the rotor angular velocity track a desired reference whenever possible, and (iii) introduce a Lyapunov-like function and present a gradient-based approach for minimizing this function. The effectiveness of the controller is demonstrated through simulation of a wind turbine operating under several scenarios.Comment: 14 pages, 9 figures, accepted for publication in IEEE Transactions on Control Systems Technolog

Reinforcement learning-based structural control of floating wind turbines

The structural control of floating wind turbines using active tuned mass damper is investigated in this article. To our knowledge, this is for the first time that reinforcement learning-based control approach is employed to this type of application. Specifically, an adaptive dynamic programming (ADP) algorithm is used to derive the optimal control law based on the nonlinear structural dynamics, and the large-scale machine learning platform Tensorflow is employed for the design and implementation of the neural network (NN) structure. Three fully connected NNs, i.e., a plant network, a critic network, and an action network, are included in the proposed NN structure. Their training requires the gradient information flowing through the whole network, which is tackled by automatic differentiation, a popular technique for deriving the gradients of complex networks automatically. While to our knowledge, the network structures in the existing literature are rather simple and the training of the hidden layer is usually ignored. This allows their gradients to be derived analytically, which is infeasible with complex network structures. Thus, automatic differentiation greatly improves the employed ADP algorithm's ability in solving complex problems. The simulation results of structural control of floating wind turbines show that ADP controller performs very well in both normal and extreme conditions, with the standard deviation of the platform pitch displacement being reduced by around 40%. A clear advantage of ADP controllers over the H∞ controller is observed, especially in extreme conditions. Moreover, our design considers the tradeoff between the control performance and power consumption

Does foreign environmental policy influence domestic innovation? Evidence from the wind industry

This paper examines the relative influence of domestic and foreign renewable energy policies on innovation activity in wind power using patent data from OECD countries from 1994 to 2005. We distinguish between the impact of demand-pull policies (e.g., guaranteed tariffs, investment and production tax credits), as reflected by wind power capacities installed annually, and technology-push policies (government support to R&D). We show that inventors respond to both domestic and foreign new capacities by increasing their innovation effort. However, the effect on innovation of the marginal wind turbine installed at home is 28 times stronger than that of the foreign marginal wind turbine. Unlike demand-pull policies, public R&D expenditures only affect domestic inventors. A simple calculation suggests that the marginal million dollars spent on R&D support generates 0.82 new inventions, whereas the same amount spent on the deployment of wind turbines induces, at best, 0.06 new inventions (0.03 locally and 0.03 abroad)

A Markovian jump system approach for the estimation and adaptive diagnosis of decreased power generation in wind farms

In this study, a Markovian jump model of the power generation system of a wind turbine is proposed and the authors present a closed-loop model-based observer to estimate the faults related to energy losses. The observer is designed through an H∞-based optimisation problem that optimally fixes the trade-off between the observer fault sensitivity and robustness. The fault estimates are then used in data-based decision mechanisms for achieving fault detection and isolation. The performance of the strategy is then ameliorated in a wind farm (WF) level scheme that uses a bank of the aforementioned observers and decision mechanisms. Finally, the proposed approach is tested using a well-known benchmark in the context of WF fault diagnosis

Future work on harmonics : some expert opinions part I : wind and solar power

A workshop on power system harmonics was organized in Stockholm in January 2014. On the agenda was among others a discussion on what are the main issues on harmonics at the moment and in the near future. The results of this discussion are summarized in this paper and some of the issues are discussed in more detail in this paper and in its companion paper. This paper discusses emission from wind and solar power as well as advantages and disadvantages of active and passive filters