Influence Of Wake Effect Research Articles

Wind farm control using distributed economic MPC scheme under the influence of wake effect

As wind farms (WFs) expand in scale, there is a growing need for active power control to track the reference power benchmark issued by the grid dispatch center and also the imperative to reduce the fatigue load on key components of each wind turbine (WT). The presence of the wake effect causes a decrease in power generation for downstream WTs and an increase in the fatigue load. Consequently, the suppression of the wake effect has emerged as a critical control objective for WFs. For tackling the challenge, this article designs a hierarchical WF control framework. The upper-level controller employs a sequential convex programming (SCP) approach to maximize the WF's captured wind energy function and determine the optimal induction factors for the WTs. The lower-layer controller uses a distributed economic model predictive control (DEMPC) scheme to control the WT locally to achieve reference power tracking while reducing the fatigue load on each WT. Finally, the effectiveness of the designed algorithm was verified by conducting the simulation on a wind farm containing nine WTs.

An asynchronous distributed optimal wake control scheme for suppressing fatigue load and increasing power extraction in wind farms

The fatigue damage and power generation of wind farms (WFs) is related to their service lifetime and economic benefits. In this paper, an asynchronous distributed optimal wake control (OWC) scheme is proposed to suppress fatigue load and increase power extraction in doubly-fed induction generator (DFIG)-based wind farm (WF). To improve control flexibility, the generator torque and pitch angle of a wind turbine (WT) is simultaneously controlled. Then, considering the influence of wake effect, the wind speed sensitivity is used to combine with the states of WTs for formulating the model predictive control (MPC)-based optimal control objectives. To deal with the higher computational complexity of the aerodynamic interactions efficiently, an asynchronous distributed alternating direction method of multipliers (AD-ADMM) is designed for the control system. A layout of a 3 × 5 wake WF is considered in the case studies to validate the outstanding performance of the proposed scheme.

Optimal selection of time windows for preventive maintenance of offshore wind farms subject to wake losses

AbstractThe maintenance of wind farms is one of the major factors affecting their profitability. During preventive maintenance, the shutdown of wind turbines causes downtime energy losses. The selection of when and which turbines to maintain can significantly impact the overall downtime energy loss. This paper leverages a wind farm power generation model to calculate downtime energy losses during preventive maintenance for an offshore wind farm. Wake effects are considered to accurately evaluate power output under specific wind conditions. In addition to wind speed and direction, the influence of wake effects is an important factor in selecting time windows for maintenance. To minimize the overall downtime energy loss of an offshore wind farm caused by preventive maintenance, a mixed‐integer nonlinear optimization problem is formulated and solved by the genetic algorithm, which can select the optimal maintenance time windows of each turbine. Weather conditions are imposed as constraints to ensure the safety of maintenance personnel and transportation. Using the climatic data of Cape Cod, Massachusetts, the schedule of preventive maintenance is optimized for a simulated utility‐scale offshore wind farm. The optimized schedule not only reduces the annual downtime energy loss by selecting the maintenance dates when wind speed is low but also decreases the overall influence of wake effects within the farm. The portion of downtime energy loss reduced due to consideration of wake effects each year is up to approximately 0.2% of the annual wind farm energy generation across the case studies—with other stated opportunities for further profitability improvements.

An Investigation of the Influence of Close-Proximity Traffic on the Aerodynamic Drag Experienced by Tractor-Trailer Combinations

<div class="section abstract"><div class="htmlview paragraph">Recent research to investigate the aerodynamic-drag reduction associated with truck platooning systems has begun to reveal that surrounding traffic has a measurable impact on the aerodynamic performance of heavy trucks. A 1/15-scale wind-tunnel study was undertaken to measure changes to the aerodynamic drag experienced by heavy trucks in the presence of upstream traffic. The results, which are based on traffic conditions with up to 5 surrounding vehicles in a 2-lane configuration and consisting of 3 vehicle shapes (compact sedans, SUVs, and a medium-duty truck), show drag reductions of 1% to 16% for the heavy truck model, with the largest reductions of the same order as those experienced in a truck-platooning scenario. The data also reveal that the performance of drag-reduction technologies applied to the heavy-truck model (trailer side-skirts and a boat-tail) demonstrate different performance when applied to an isolated vehicle than to conditions with surrounding traffic. The results suggest that vehicle shape optimization strategies may differ if the influence of wake effects from surrounding traffic is included in product development cycles. Additionally, truck-platooning benefits should be taken in the context of typical traffic scenarios for which trucks are already experiencing a background-platooning effect and therefore may not be expected to attain the benefits relative to isolate-vehicle conditions.</div></div>

A Method for Calculating Wind PowerPenetration Limit Considering Wake Effect and Wind Speed Correlation

With the development of wind power technology, accurate analysis of wind power penetration limit is conducive to large-scale wind power safely connected to the power grid. At present, the related research does not consider the influence of wake effect. Therefore, this paper proposes a wind power penetration limit analysis method considering the wake effect and wind speed correlation. Firstly, this paper uses a stochastic simulation technique based on the Latin hypercube sampling (LHS) to simulate the wind speed of multiple wind farms with correlation, and establishes a wind power active output model considering the wake effect, thus the calculation model of wind power penetration limit is established based on the chance constrained programming (CCP) theory and solved by the particle swarm optimization algorithm. Taking the IEEE-30 node system as an example, the feasibility and effectiveness of the above model and algorithm in evaluating wind power access capability are verified.

Estimate of aDregion ionospheric electron density profile from MF radio wave observations by the S-310-37 rocket

The S-310-37 rocket, launched at 11:20 (JST) on 16 January 2007, was equipped with a radio receiver to observe the medium-frequency (MF) radio wave propagation characteristics in the ionosphere. The radio receiver measured the intensity and the waveform of the radio wave at 873 kHz from the NHK Kumamoto broadcasting station. The polarized mode waves' intensity characteristics were obtained by analyzing the observed waveform. In this study, the S-310-37 rocket-observed polarized mode waves' propagation characteristics are analyzed in order to estimate the electron density profile in the ionospheric D region. These observations become better measurement approach because the electron density profile in the ionospheric D region is difficult to be observed by other equipment such as a Langmuir probe. A Langmuir probe can measure in the ionospheric D region; however, the absolute values may be off by the influence of wake effects around the sounding rocket. It is demonstrated that the propagation characteristics of the polarized mode waves can be successfully used to derive the electron density profile in the ionospheric D region.

Wake Effect and Power Production of Wind Turbine Arrays

This study experimentally investigated the influence of wake effect and production of mechanical power in wind tunnel of wind turbine arrays. Wind turbine arrays consist of 2 rows with 3 columns for spacing wind turbines in rows apart in the windward direction 1.77 rotor diameters and apart in the crosswind direction 8.85 rotor diameters. The wake characteristics such as profiles of time averaged velocity, turbulence intensity, centerline velocity deficit and wake radius for far wake regions in position 1, 2, and 3 were measured and analysed. The vertical and lateral profiles of velocity and turbulence intensity were studied. Concerning the results from measured data, empirical relations for the centerline velocity deficit, turbulence intensity and wake radius were proposed. Based on the experimental results, the power loss is due to the wake flow of upwind turbine approximately 20% when the downwind distance 8.85 rotor diameters. This is different with numerical result study that 11% at downwind distance is 8.85 rotor diameters. This difference results from the influence of ambient turbulence on the production of mechanical power of the wind turbine.

Effects of wind generation intermittency and volatility on power system transient stability

The transient stability analysis incorporating wind power intermittency and volatility is studied in this study. The wind turbines with doubly fed induction generator (DFIG) and direct-driven permanent magnet synchronous generator (PMSG) are considered, respectively, during analysis. In modelling of DFIG and PMSG, the default GE wind turbine model and the Western Electricity Coordinating Council generic wind turbine model are employed, respectively. Based on the Jensen model, which is applied to describe the wake effect in a wind farm located on flat terrain, an equivalent simplified model of a wind farm is established regarding wind farm layout. On the basis of the built wind farm model, the Monte Carlo simulation technique combined with two evaluation indices, namely angle-based margin index and critical clearing time (CCT) is applied on the IEEE 10-generator-39-bus test system and a real-sized China-Jiangxi power grid as a benchmark to exploit and explore the effects of wind power intermittency and volatility on power system transient stability. The frequency distributions of transient stability evaluation index, CCT, probability of system transient instability and the range of wind speeds causing system transient instability are simulated. In addition, the influence of wake effect on transient stability is discussed as well.

Influence of Wake Effects and Inflow Turbulence on Wind Turbine Loads

Wind turbines are emerging as an exciting and rapidly expanding form of renewable energy. However, there are numerous technological challenges that must be overcome before wind energy provides a significant amount of power in the United States. One of the primary challenges in wind turbine design and analysis is accurately accounting for the wake. This study represents an initial step towards including wake effects in wind turbine design and analysis codes. A free wake model is developed using a time marching vortex line method, and subsequently verified and validated against existing results. The model is then used to examine time step requirements in the presence of inflow turbulence. Finally, comparisons are made between the developed free wake model and typical aerodynamic modeling approaches such as Blade Element Momentum Theory and Dynamic Inflow. For the configurations considered, blade time step sizes of 10° in azimuthal angle are adequate for capturing the effect of inflow turbulence on the wake. Finally, the inability of Blade Element Moment Theory and Dynamic Inflow to predict blade loads with combined inflow turbulence and wake effects is demonstrated.