Room:
Diesel Hall
Topic:
B. Wind, wakes, turbulence and wind farms
Form of presentation:
Oral
Duration:
120 Minutes
Chaired by: J. Meyers, J. Peinke
13:30
Multi-Objective Random Search Algorithm for Simultaneously Optimizing Wind Farm Layout and Number of Turbines
Dr. Ju Feng | Technical University of Denmark | Denmark
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Authors:
Dr. Ju Feng | Technical University of Denmark | Denmark
Wen Zhong Shen | Denmark
Chang Xu | Denmark
A new algorithm for multi-objective wind farm layout optimization is presented. It treats the turbine locations as continuous variables and can optimize the number of turbines and their locations simultaneously. Two objectives are considered. One is to maximize the power production, calculated by considering the wake effects using the Jensen wake model and the local wind distribution. The other is to minimize the total electrical cable length, assumed as the total length of the minimal spanning tree that connects all turbines and calculated by Prim’s algorithm. Constraints on wind farm boundary and wind turbine proximity are also considered. An ideal test case shows the proposed algorithm largely outperforms a famous multi-objective genetic algorithm (NSGA-II). In a real test case based on the Horn Rev 1 wind farm, the algorithm also obtains useful Pareto frontiers and provides a wide range of Pareto optimal layouts with different numbers of turbines for wind farm developers.
13:50
Wind shear estimation and wake detection by rotor loads - First wind tunnel verification
Johannes Schreiber | Technische Universität München | Germany
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Authors:
Johannes Schreiber | Technische Universität München | Germany
Dr. Stefano Cacciola | Germany
Filippo Campagnolo | Germany
Vlaho Petrovic | Germany
Delphine Mourembles | Germany
Carlo L. Bottasso | Germany
The paper describes a simple method for detecting presence and location of a wake affecting a downstream wind turbine operating in a wind power plant. First, the local wind speed and shear experienced by the wind turbine are estimated by the use of rotor loads and other standard wind turbine response data. Then, a simple wake deficit model is used to determine the lateral position of the wake with respect to the affected rotor. The method is verified in a boundary layer wind tunnel using two instrumented scaled wind turbine models, demonstrating its effectiveness.
14:10
Wind tunnel testing of a closed-loop wake deflection controller for wind farm power maximization
Dr. Filippo Campagnolo | Technische Universität München | Germany
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Authors:
Dr. Filippo Campagnolo | Technische Universität München | Germany
Carlo Luigi Bottasso | Germany
Vlaho Petrovic | Germany
Alessandro Croce | Germany
Johannes Schreiber | Germany
Emmanouil Marios Nanos | Germany
Goal of this paper is to present results from wind tunnel tests aimed at evaluating a closed-loop wind farm controller seeking for wind farm power maximization by wake defection. The experiments are conducted in a large boundary layer wind tunnel, using three servo-actuated and highly sensorized wind turbine scaled models. The impact of wake defection, achieved by active yawing the upstream wind turbines, is first presented. In the following, the capability of the proposed wind farm controller in properly driving the upstream wind turbines into the optimal yaw misalignment setting is discussed.
14:30
A Control-Oriented Dynamic Flow Model: ‘WFSim’
Sjoerd Boersma | Delft University of Technology | Netherlands
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Authors:
Sjoerd Boersma | Delft University of Technology | Netherlands
Pieter Gebraad | Netherlands
Mehdi Vali | Netherlands
Bart Doekemeijer | Netherlands
Jan-Willem van Wingerden | Netherlands
In this paper, we present and extend the dynamic medium fidelity control-oriented Wind Farm Simulator (WFSim) model. WFSim resolves flow fields in wind farms in a horizontal, two dimensional plane. It is based on the spatially and temporally discretised two dimensional Navier-Stokes equations and the continuity equation and solves for a predefined grid and wind farm topology. The force on the flow field generated by turbines is modelled using actuator disk theory. Sparsity in system matrices is exploited in WFSim, which enables a relatively fast flow field computation. The extensions to WFSim we present in this paper are the inclusion of a wake redirection model, a turbulence model and a linearisation of the nonlinear WFSim model equations. The first is important because it allows us to carry out wake redirection control and simulate situations with an inflow that is misaligned with the rotor plane. The wake redirection model is validated against a theoretical wake centreline known from literature. The second extension makes WFSim more realistic because it accounts for wake recovery. The amount of recovery is validated using a high fidelity simulation model Simulator fOr Wind Farm Applications (SOWFA) for a two turbine test case. Finally, a linearisation is important since it allows the application of more standard analysis, observer and control techniques.
14:50
A study on the active induction control of upstream wind turbines for total power increases
Hyungyu Kim | Kangwon National University | Korea, Republic of
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Authors:
Hyungyu Kim | Kangwon National University | Korea, Republic of
Insu Paek | Korea, Republic of
Carlo Luigi Bottasso | Korea, Republic of
Kwansoo Kim | Korea, Republic of
Filippo Campagnolo | Korea, Republic of
In this study, the effect of active induction control of upstream wind turbines is investigated. Two scaled wind turbines having a rotor diameter of 1m with a spacing of four times of the rotor diameter were used to experimentally validate the concept. Also, an in-house c code was used to simulate the same two wind turbines and see if the experimental observations can be obtained. From the experiment, approximately 0.65% increase of total power could be observed. Although the simulation results were not exactly the same as the experimental results but the shape was similar and the maximum power increase of 0.27% was predicted. Also from further simulation for NREL 5MW wind turbines instead of scaled wind turbines and also with a suitable ambient turbulence intensity, it was found that the power increase could become more than 1%.
15:10
Lidar configurations for wind turbine control
Dr. Mahmood Mirzaei | Technical University of Denmark | Denmark
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Authors:
Dr. Mahmood Mirzaei | Technical University of Denmark | Denmark
Jakob Mann | Denmark
Lidar sensors have proved to be very beneficial in the wind energy industry. They can be used for yaw correction, feed-forward pitch control and load verification. However, the current lidars are expensive. One way to reduce the price is to use lidars with few measurement points. Finding the best configuration of an inexpensive lidar in terms of number of measurement points, the measurement distance and the opening angle is the subject of this study. In order to solve the problem, a lidar model is developed and used to measure wind speed in a turbulence box. The effective wind speed measured by the lidar is compared against the effective wind speed on a wind turbine rotor both theoretically and through simulations. The study provides some results to choose the best configuration of the lidar with few measurement points.