Wind Farm Power Output Research Articles

Optimized dispatch of wind farms with power control capability for power system restoration

As the power control technology of wind farms develops, the output power of wind farms can be constant, which makes it possible for wind farms to participate in power system restoration. However, due to the uncertainty of wind energy, the actual output power can’t reach a constant dispatch power in all time intervals, resulting in uncertain power sags which may induce the frequency of the system being restored to go outside the security limits. Therefore, it is necessary to optimize the dispatch of wind farms participating in power system restoration. Considering that the probability distribution function (PDF) of transient power sags is hard to obtain, a robust optimization model is proposed in this paper, which can maximize the output power of wind farms participating in power system restoration. Simulation results demonstrate that the security constraints of the restored system can be kept within security limits when wind farm dispatch is optimized by the proposed method.

Distributed Torque Control of Deloaded Wind DFIGs for Wind Farm Power Output Regulation

In this work, we propose a distributed control methodology that solves the problem of dispatching and regulating the power outputs of a group of deloaded wind double-fed induction generators (DFIGs) to attain fast, dynamic, and efficient wind farm power output regulation, with fair load-sharing among the DFIGs. In this context, fair load-sharing means that the ratio defined by the mechanical power over the maximum power from the wind, i.e., the utilization level, of all DFIGs, is the same in the steady state. Dynamic distributed dispatch and control of the power outputs of DFIGs refers to their ability to self-dispatch and regulate their power outputs under dynamical conditions and through peer-to-peer information exchange. Initially, we propose a leader-follower consensus protocol that DFIGs can adopt into their control system to attain: 1) asymptotic consensus on their utilization levels (i.e., fair load-sharing), and 2) total power output regulation. Then, we perform compositional stability analysis and prove that the protocol asymptotically converges under sufficient conditions. Finally, we design a distributed control-Lyapunov-function-based torque controller for the rotor-side converter that realizes the protocol in practice. The performance of the distributed control methodology is evaluated through numerical simulations on the modified IEEE 24-bus RT system.

Coupled wind farm parameterization with a mesoscale model for simulations of an onshore wind farm

The mesoscale Weather Research and Forecasting (WRF) model coupled with wind farm parameterization is newly developed to simulate the wake flow and power production of a real onshore wind farm. First, wind farm flow field simulations are conducted with 1000m, 500m and 200m horizontal resolutions, and the simulation results capture the wind farm observed data well. In addition, wind farm flow characteristics, power output, and influence on the atmosphere boundary layer (ABL) are resolved at a horizontal resolution of 200m. The wake interactions, wind speed, and power output deficit in the wind farm are analyzed. The power comparison results prove that the proposed method can be applied to simulate the power output of a real onshore wind farm with high accuracy in real time. The influence of the wind farm on the ABL is also discussed. The results show that wind farm effects on the ABL occur mainly within the turbine rotor-spanned heights and the downstream regions behind the wind farm within 10km, within which the speed deficit ratio can exceed 10%. For the region that is 18km downstream of the wind farm, the average speed deficit ratio is only about 2%. This study is the first attempt to reproduce the wake flow and power output of a real onshore wind farm by the WRF model at such high resolution.

A coordinative optimization method of active power and fatigue distribution in onshore wind farms

Summary To optimize the fatigue distribution and the active power output of an onshore wind farm, we develop a new centralized approach for optimizing active power references for each wind turbine. The fatigue of a turbine is modeled by a fatigue coefficient integrated with wind characteristics. In the active power dispatching optimization model, the objective function is designed to minimize the standard deviation of the fatigue coefficient for every turbine. Moreover, the optimization is constrained by active power limitations of the turbines and the wind farm. To solve this problem in real time, we propose an improved genetic algorithm that is embedded with partial constraints of the optimization model. Detailed simulation results demonstrate that the fatigue level among turbines becomes balanced, and active power demands for the farm are satisfied. The proposed approach is a feasible way to use the active power curtailment to reduce the maintenance frequency of wind farms.

Considering air density effect on modelling wind farm power curve using site measurements

Manufacturers develop power curves for their wind turbines. Customers use these wind turbine power curves for wind farm planning and estimating nearly total production of planned plant. When wind farm is installed and connected to the grid, these power curves are not useful. In literacy, researchers proposed wind turbine power curve measurement methods to obtain an accurate power curve for turbine on site. But it is not easy to develop power curves for clusters of wind turbines. Developing a single power curve for a wind farm slightly simplifies this problem. Accurate wind farm power curve is a very useful tool for converting wind speed forecasts to power. Also plant owner can use this tool to detect anomalous operations. In this study we developed and tested wind farm power curves by using real site measurements. Two different methods are used to develop power curves. They are polynomial curve fitting and mean bins method. Wind speed and power output relation is investigated. A method is proposed to add effect of air density on power curve. Developed power curve has two inputs. They are hourly mean wind speed and air density values. This approach uses variable air density in calculation of wind farm power output. Results of this study showed that performance of mean bins method is better than polynomial curve fitting. Also proposed air density effect adding method improves performances of obtained power curves.

Statistical meandering wake model and its application to yaw-angle optimisation of wind farms

The wake produced by a wind turbine is dynamically meandering and of rather narrow nature. Only when looking at large time averages, the wake appears to be static and rather broad, and is then well described by simple engineering models like the Jensen wake model (JWM). We generalise the latter deterministic models to a statistical meandering wake model (SMWM), where a random directional deflection is assigned to a narrow wake in such a way that on average it resembles a broad Jensen wake. In a second step, the model is further generalised to wind-farm level, where the deflections of the multiple wakes are treated as independently and identically distributed random variables. When carefully calibrated to the Nysted wind farm, the ensemble average of the statistical model produces the same wind-direction dependence of the power efficiency as obtained from the standard Jensen model. Upon using the JWM to perform a yaw-angle optimisation of wind-farm power output, we find an optimisation gain of 6.7% for the Nysted wind farm when compared to zero yaw angles and averaged over all wind directions. When applying the obtained JWM-based optimised yaw angles to the SMWM, the ensemble-averaged gain is calculated to be 7.5%. This outcome indicates the possible operational robustness of an optimised yaw control for real-life wind farms.

A new simplified model for assessment of power variation of DFIG-based wind farm participating in frequency control system

Due to the ever-increasing use of wind farms (WFs), an investigation of their impact on the power system stability and control is essential. Especially, assessing the active power variation of WF is one of the important issues, since it can affect the power system frequency. Unlike traditional power plants, a WF consists of many units (wind turbines) with different operating conditions; therefore, studying the behavior of each unit is necessary and this kind of study undoubtedly involves a myriad of calculations. This paper aims to propose a simple and effective equivalent model for a DFIG-based WF participating in the frequency control system. The model is intended to accurately show the behavior of WF as well as individual wind turbines. It is analytically shown that under nominal frequency conditions, a first-order system can accurately evaluate the WF output power. Also, the paper deals with further considerations that should be taken during frequency disturbances to preserve the accuracy. In order to verify the accuracy and effectiveness of the proposed model, the performance of the proposed model is compared to the detailed and the conventional models.

Short Term Prediction Method for Output Power of Wind Farm Based on Fusion Model

Wind power has the characteristics of randomness and intermittent, the safe and stable operation of power system will be influenced after a large scale of wind power integrated to the system. Against this background, it is extremely important for the power grid operation to forecast the power output of wind farm. A fusion prediction model based on wind speed and wind power is proposed in this paper in order to improve the precision of the short term output wind power. Firstly, a combined prediction model of wind power is constructed by autoregressive time series and generalized regression neural network to forecast the wind power directly. Then, the same combined prediction model is used to forecast the wind speed and the wind power is computed indirectly according to the relationship between wind speed and power. Finally, the fusion prediction model can be obtained by combining the two previous model. As a result, it can improve the prediction accuracy of output wind power for large scale wind farm effectively.

Wind farm multi-objective wake redirection for optimizing power production and loads

Clustering wind turbines as a wind farm to share the infrastructure is an effective strategy to reduce the cost of energy. However, this results in aerodynamic wake interaction among wind turbines. Yawing the upstream wind turbines can mitigate the losses in wind farm power output. Yaw-misalignment also affects the loads, as partial wake overlap can increase fatigue of downstream turbines. This paper studies multi-objective optimization of wind farm wake using yaw-misalignment to increase power production and reduce loads due to partial wake overlap. This is achieved using a computational framework consisting of an aerodynamic model for wind farm wake, a blade-element-momentum model to compute the power and the loads, and a gradient-based optimizer. The results show that yaw-misalignment is capable of increasing the power production of the wind farm, while reducing the loading due to partial wake overlap. A multi-objective optimization is able to further decrease the loads at the expense of a small amount of power production.

Probabilistic Voltage Stability Analysis Based on Unscented Transformation and Maximum Entropy Principle

Considering the uncertainty of load and the random variation of wind farm output power in power system, a probabilistic voltage stability analysis method is proposed based on unscented transformation technique. According to the statistical characteristics of random variables in power system, the statistical characteristics of voltage stability margins, such as mean, standard deviation and moments, can be calculated by using a small number of samples and the conventional method. The maximum entropy method is applied to determine the probability distribution of voltage stability margin. In compared with Monte Carlo method, the effectiveness of the proposed method is verified on 39-bus and IEEE 57-bus system. The results show that the proposed method can accurately compute the statistical characteristics and the probability distribution of the voltage stability margin, and the computational efficiency is improved.

Reactive power optimisation of distribution network with dispersed wind farm

Environmental pollution and energy shortage have resulted in a recent strong demand for distribution networks to accept renewable clean energy. As an important part of distributed generations, dispersed wind power with its clean and flexible characteristics has been an important focus of domestic and foreign entities. In this paper, the voltage deviation model and the maximum wind power real-time penetration model were established as the two objective functions, and the reactive power output of wind farms was considered to regulate the voltage. The harmonic search algorithm was used to solve the model, simulation test with IEEE33 node system model was carried out, and the results show that the established optimisation model as well as its solution strategy can make full use of the reactive power output of wind farms to achieve the maximum wind power consumption.

Coordinated Operation Strategy of Wind Farms for Frequency Control by Exploring Wake Interaction

This paper proposes a coordinated wind farm (WF) operation strategy that exploits the wake interaction within a WF. In contrast to the conventional WF operation strategy where each wind turbine (WT) is optimized individually, three operation strategies are suggested: 1) maximization of the WF's power while maintaining WF's rotational kinetic energy; 2) maximization of the WF's rotational kinetic energy while maintaining WF's output power; and 3) a de-loaded strategy whereby the WF's rotational kinetic energy is maximized for a fixed de-loading margin. The three operation strategies are formulated as nonlinear optimization problems and solved in a central WF controller. The optimal rotor speeds and pitch angles are used as reference values in the individual WTs. The optimization results for the three respective operation strategies show that: 1) up to 3% increase in the WF's output power; 2) up to 23% increase in the WF's rotational kinetic energy; and 3) up to 28% increase in the WF's rotational kinetic energy and 8% reserve power while operating the WF in a 5% de-loaded mode with respect to the conventional operation strategy. Time-domain simulations show that the proposed operation strategy noticeably improves the WF's performance in frequency control.

Output power smoothing of grid‐connected permanent‐magnet synchronous generator driven directly by variable speed wind turbine: a review

The output power of wind farms is fluctuating as a result of the wind speed variation. These power fluctuations disturb the quality of voltage and frequency of the grid. The fluctuated power can be smoothed via many methods such as controlling the pitch angle of blades, the rotor inertia, and using the energy storage systems (ESSs). These ESSs are mostly installed in the renewable energy for load levelling with cost limitations. Owing to the high cost of ESSs, it is required to utilise and enhance different power control techniques. This study introduces different and recent proposed methods and enhancements to smoothen the output power of permanent-magnet synchronous generator driven directly (gearless) by a variable-speed wind turbine. Fuzzy logic control, sliding mode control, and evolutionary algorithms are used to enhance the control performance of pitch angle, machine-side converter, and DC–DC converter of ESS.

Wind power fluctuation mitigation based low‐frequency oscillation

Owing to the stochastic and intermittent of output power of wind farms, the large-scale grid-connected wind power could have a remarkable impact on the power system operation. In this study, wind power fluctuation (WPF) mitigation is achieved from the perspective of power system low-frequency oscillation (LFO). Firstly, in order to meet fluctuation mitigation requirement, model predictive control algorithm is applied to smooth WPF. Secondly, the Hilbert–Huang transform method is used to obtain the influences of wind power before and after smoothing on system LFO. In addition, wind power is decomposed into high, medium and low bands by empirical mode decomposition, and then the impacts of different bands wind power on system LFO are studied. Finally, the influences of wind power with different fluctuation rates on system LFO are analysed based on the WSCC 3-machine 9-bus power system, which provides a theoretical reference for smoothing WPF.

Modeling and Simulation for Bifurcations of SSR in Large Wind Farms

Bifurcations of subsynchronous resonance (SSR) is applied to the induction generator (IG) based wind farms connected to series compensated lines. The developed first system of the IEEE second benchmark model of subsynchronous resonance is considered. The system studied can be mathematically modeled as a set of first order nonlinear ordinary differential equations with a compensation factor as a bifurcation parameter. Therefore, bifurcation theory can be applied to the nonlinear dynamical systems. The impress of both torsional interaction and induction generator effect are considered. Bifurcations of SSR are studied for a wide range of series compensation levels in the cases of various sizes of wind farms and various wind farm power outputs. The results show that Hopf bifurcations may occur in large wind farms based on double-cage IGs at high level of series compensation. When the size of wind farm increases, the Hopf bifurcation point initially shifts to the left at a less value of compensation then shifts to the right at a larger value of compensation with a supercritical Hopf bifurcation remains in all cases. This resulted in only quantitative changes in Hopf bifurcation for the case of variation in wind farm size. On the other hand, when the power output of a large wind farm increases the Hopf bifurcation point shifts a little to the left at a slightly less value of compensation. On the contrary, the type of Hopf bifurcation changes from subcritical to supercritical. Therefore, the impact of the variation in the wind farm size on bifurcation is only of a quantitative change, while the impact of variation in the power output is mainly a qualitative change.

곡선회귀분석을 이용한 풍력발전 출력 예측에 관한 연구

Recently, the size of wind farms is becoming larger, and the integration of high wind generation resources into power gird is becoming more important. Due to intermittency of wind generating resources, it is an essential to predict power outputs. In this paper, we introduce the basic concept of curvilinear regression, which is one of the method of wind power prediction. The empirical data, wind farm power output in Jeju Island, is considered to verify the proposed prediction model.

Modelling and solutions of coordinated economic dispatch with wind–hydro–thermal complex power source structure

This study presents an efficient optimisation strategy for solving coordinated economic dispatch problem with wind-hydro-thermal complex power source structure. The wind-hydro-thermal coordinated dispatch aims to minimise the total fuel costs of coal-fired thermal power units while satisfying all kinds of operating constraints. To better handle the random variables in the constraints introduced by wind power and load demand during analysis, a probabilistic analytical model is employed to describe the uncertainty of wind farm power output first; moreover, then an improved convolution method is applied to calculate the total stochastic power consisting of load demand and power output of wind farm. The two-stage stochastic linear programming method and stochastic chance constraints are employed to further form a new deterministic objective function with penalty items taken into account. An enhanced particle swarm optimisation method is applied in the solution of the proposed model. Finally, the simulations are performed on a 6-bus test system and a real-sized China power grid test system to investigate the effectiveness and validity of the proposed optimisation strategy.

Uncertainty quantification of infinite aligned wind farm performance using non‐intrusive polynomial chaos and a distributed roughness model

AbstractUncertainty of wind farm parameters can have a significant effect on wind farm power output. Knowledge of the uncertainty‐produced stochastic distribution of the entire wind farm power output and the corresponding uncertainty propagation mechanisms is very important for evaluating the uncertainty effects on the wind farm performance during wind farm planning stage and providing insights on improving the performance of the existing wind farms. In this work, the propagation of uncertainties from surface roughness and induction factor in infinite aligned wind farms modeled by a modified distributed roughness model is investigated using non‐intrusive polynomial chaos. Stochastic analysis of surface roughness indicates that 30% uncertainty can propagate such that there is up a 8% uncertainty in the power output of the wind farm by affecting the uncertainty in the position of the individual wind turbines in the vertical boundary layer profile and uncertainty in vertical momentum fluxes which replenish energy in the wake in large wind farms. Induction factor uncertainty of the wind turbines can also have a significant effect on power output. Not only does its uncertainty substantially affect the vertical boundary layer profile, but the uncertainty in turbine wake growth which affects how neighboring turbine wakes interact. We found that optimal power output in terms of reduction of uncertainty closely correlates with the Betz limit and is dependent on the mean induction factor. Copyright © 2016 John Wiley & Sons, Ltd.

Yaw-Misalignment and its Impact on Wind Turbine Loads and Wind Farm Power Output

To make wind energy cost competitive with traditional resources, wind turbines are commonly placed in groups. Aerodynamic interaction between the turbines causes sub-optimal energy production. A control strategy to mitigate these losses is by redirecting the wake by yaw misalignment. This paper aims to assess the influence of load variations of the rotor due to partial wake overlap and presents a combined optimization of the power and loads using wake redirection. For this purpose, we design a computational framework which computes the wind farm power production and the wind turbine rotor loads based on the yaw settings. The simulation results show that partial wake overlap can significantly increase asymmetric loading of the rotor disk and that yaw misalignment is beneficial in situations where the wake can be sufficiently directed away from the downstream turbine.

Perturbations to the Spatial and Temporal Characteristics of the Diurnally-Varying Atmospheric Boundary Layer Due to an Extensive Wind Farm

The effect of extensive terrestrial wind farms on the spatio-temporal structure of the diurnally-evolving atmospheric boundary layer is explored. High-resolution large-eddy simulations of a realistic diurnal cycle with an embedded wind farm are performed. Simulations are forced by a constant geostrophic velocity with time-varying surface boundary conditions derived from a selected period of the CASES-99 field campaign. Through analysis of the bulk statistics of the flow as a function of height and time, it is shown that extensive wind farms shift the inertial oscillations and the associated nocturnal low-level jet vertically upwards by approximately 200 m; cause a three times stronger stratification between the surface and the rotor-disk region, and as a consequence, delay the formation and growth of the convective boundary layer (CBL) by approximately 2 h. These perturbations are shown to have a direct impact on the potential power output of an extensive wind farm with the displacement of the low-level jet causing lower power output during the night as compared to the day. The low-power regime at night is shown to persist for almost 2 h beyond the morning transition due to the reduced growth of the CBL. It is shown that the wind farm induces a deeper entrainment region with greater entrainment fluxes. Finally, it is found that the diurnally-averaged effective roughness length for wind farms is much lower than the reference value computed theoretically for neutral conditions.