Power Dispatching Method for a De‐Loading Operated Wind Farm Participating in Power System Frequency Regulation Considering Wake Effect

Large-scale grid-connected renewable energy sources (RES) pose a serious threat to the frequency stability of the power system. Considering the active power flexible regulation ability for wind turbines (WTs), the gradual increase in the penetration level of wind power (WP) has led to growing interest in the capability of WP participating in the power system frequency regulation. Therefore, this paper reviews the current research status of WP participating in frequency regulation from WT level, wind farm (WF) level, and power system level, respectively. At the WT level, the existing WT types and the characteristics of various frequency regulation strategies are analyzed. At the WF level, the coordinated controls within the WFs are further discussed, which contain the active power distribution between WTs and rotor speed recovery coordinated control. At the system level, the coordinated frequency controls of WP with other generation resources and energy storage systems are presented. The advantages and disadvantages of each frequency participation strategy are also discussed and compared. Finally, the prospects of WP frequency regulation are expected with further research attention.

Wind turbine wakes for wind energy

Assessment of wind resources in two parts of Northeast Brazil with the use of numerical models

With the increase of wind power penetration in the electric grid, the frequency regulation method that simply reply on traditional power is gradually weakened. For this reason, the participation of wind power in system frequency regulation has become an inevitable trend in the operation of large-scale grid-connected power system. Focused on the essential difference of the frequency response speed between wind turbine and thermal power unit, a primary frequency regulation control strategy for large-scale wind power cooperative thermal power units is proposed to realize frequency regulation in the full wind speed range of doubly-fed wind turbines and improve the frequency response capability of large-scale wind power access to system. Firstly, the frequency regulation response strategy of wind turbine based on rotor kinetic energy control and power reserve control and the control strategy of rotor speed recovery are studied to improve the frequency regulation capability of wind power system. Secondly, the optimal distribution of frequency regulation power of the large-scale wind farms is realized according to the establishing of the power distribution strategy based on weight factor of each turbine in the wind farm in different operating scenarios Finally, the control framework of wind-thermal power coordination frequency regulation is constructed. The system power shortage is distributed to the wind farm and the thermal power unit in real time by the dispatch center according to the wind farms' and thermal power unit's operating states and the variation of system frequency, by which the wind-thermal power coordination frequency regulation of power system can be achieved. Simulation results of the 36-node test example demonstrate that the proposed strategy can effectively improve the frequency response capability and the frequency characteristics of the power system.

Recently, frequency regulation strategies have been widely adopted in the operation and control of doubly fed induction generator-based wind turbines (DFIG-WTs). Thus, wind power, which is becoming an increasingly important energy source, is expected to play a significant role in both power generation and frequency regulation in modern power systems. Under such circumstances, maintaining the reliability and frequency of power systems at a designated level may be more challenging due to inherent uncertainties in wind power generation. In this paper, the integrated assessment of the reliability and frequency deviation risks of power systems with a high penetration level of wind power is investigated. A multi-time scale analytical framework is proposed to calculate the integrated reliability and frequency deviation indices. The coupling between the reliability and frequency deviation is further addressed by developing a novel frequency-sensitive reliability model of the electric generator. Frequency deviations under supply/demand fluctuations and device failures are analyzed, and the power system frequency regulation process is modeled with the fuzzy adaptive virtual inertial response of DFIG-WTs and energy storage system (ESS). Furthermore, IEEE-RTS79 is used to verify the validity of the proposed model and solution method.

There is a big wind energy potential in supplying the power in an island and most of the islands are off-grid. Due to the limited area in island(s), there is need to find appropriate layout / location for wind turbines suited to the local wind conditions. In this paper, we have considered the wind resources data of an island in Trøndelag region of the Northern Norway, situated on the coastal line. The wind resources data of this island have been analysed for wake losses and turbulence on wind turbines for determining appropriate locations of wind turbines in this island. These analyses are very important for understanding the fatigue and mechanical stress on the wind turbines. In this work, semi empirical wake model has been used for wake losses analysis with wind speed and turbine spacings. The Jensen wake model used for the wake loss analysis due to its high degree of accuracy and the Frandsen model for characterizing the turbulent loading. The variations of the losses in the wind energy production of the down-wind turbine relative to the up-wind turbine and, the down-stream turbulence have been analysed for various turbine distances. The special emphasis has been taken for the case of wind turbine spacing, leading to the turbulence conditions for satisfying the IEC 61400-1 conditions to find the wind turbine layout in this island. The energy production of down-wind turbines has been decreased from 2 to 20% due to the lower wind speeds as they are located behind up-wind turbine, resulting in decreasing the overall energy production of the wind farm. Also, the higher wake losses have contributed to the effective turbulence, which has reduced the overall energy production from the wind farm. In this case study, the required distance for wind turbines have been changed to 6 rotor diameters for increasing the energy gain. From the results, it has been estimated that the marginal change in wake losses by moving the down-stream wind turbine by one rotor diameter distance has been in the range of 0.5 to 1% only and it is insignificant. In the full-length paper, the wake effects with wind speed variations and the wind turbine locations will be reported for reducing the wake losses on the down-stream wind turbine. The Frandsen model has been used for analysing turbulence loading on the down-stream wind turbine as per IEC 61400-1 criteria. In larger wind farms, the high turbulence from the up-stream wind turbines increases the fatigues on the turbines of the wind farm. In this work, we have used the effective turbulence criteria at a certain distance between up-stream and down-stream turbines for minimizing the fatigue load level. The sensitivity analysis on wake and turbulence analysis will be reported in the full-length paper. Results from this work will be useful for finding wind farm layouts in an island for utilizing effectively the wind energy resources and electrification using wind power plants.

When traditional wind farm participates in frequency regulation, the wake effect on the operating conditions of wind turbines is usually ignored, which makes the upstream wind turbines capture too much wind energy and the wind speed attenuation of downstream wind turbine is too large. So the wind farm fails to maximize the output power, and the contribution of the wind farm to participate in frequency regulation will reduce. In order to fully tap the potential of wind farms participating in system frequency regulation under actual conditions, this paper adopts the Jensen model to establish a wind farm power optimization model considering the superposition of wake effects under actual operating conditions. The interior point method is used to coordinate the axial induction factors of each wind turbine to optimize the output of the wind farm. Furthermore, since the fixed droop coefficient cannot well reflect the ability of wind turbines participating in frequency regulation under different wind speeds, a variable coefficient droop control strategy is proposed for wind farm to participate in the primary frequency regulation optimally. Simulation studies are carried out to demonstrate the effectiveness of the proposed strategy.

An optimal operation strategy of wind farm for frequency regulation reserve considering wake effects

With the increasing penetration level of wind power in the power system, the decoupling of wind turbine rotor speed and system frequency has led to the loss of the inertia of wind farms (WF), which can no longer be neglected. With the continuous development of energy storage (ES) technology, WF-ES coordinated inertial control has attracted attention as an effective means for wind turbines (WT) to participate in inertia response. How to build a WF-ES coordinated inertial control strategy and analyze system frequency characteristics has become a key research issue. In this paper, the frequency response model of a power system with WF-ES is established using the system frequency characteristic analysis method. The wind speed zones of the WF are taken into account, and different WF-ES control schemes are adopted under different wind speeds, aiming to ensure the active participation of WTs in the system frequency process across all wind speed conditions and effectively prevent frequency secondary drop. Finally, a power system frequency response simulation model is built in Matlab/Simulink to analyze the frequency characteristics of the power system with WF-ES coordinated inertial control and verify the feasibility of the proposed WF-ES coordinated inertial control strategy under various wind speeds.

District of Namaacha in Maputo Province of Mozambique presents a high wind potential, with an average wind speed of around 7.5 m/s and huge open fields that are favourable to the installation of wind farms. However, in order to make better use of the wind potential, it is necessary to evaluate the operating conditions of the turbines and guide the independent power producers (IPPs) on how to efficiently use wind power. The investigation of the wind farm operating conditions is justified by the fact that the implementation of wind power systems is quite expensive, and therefore, it is imperative to find alternatives to reduce power losses and improve energy production. Taking into account the power needs in Mozambique, this project applied hybrid optimisation of multiple energy resources (HOMER) to size the capacity of the wind farm and the number of turbines that guarantee an adequate supply of power. Moreover, considering the topographic conditions of the site and the operational parameters of the turbines, the system advisor model (SAM) was applied to evaluate the performance of the Vestas V82-1.65 horizontal axis turbines and the system’s power output as a result of the wake effect. For any wind farm, it is evident that wind turbines’ wake effects significantly reduce the performance of wind farms. The paper seeks to design and examine the proper layout for practical placements of wind generators. Firstly, a survey on the Namaacha’s electricity demand was carried out in order to obtain the district’s daily load profile required to size the wind farm’s capacity. Secondly, with the previous knowledge that the operation of wind farms is affected by wake losses, different wake effect models applied by SAM were examined and the Eddy–Viscosity model was selected to perform the analysis. Three distinct layouts result from SAM optimisation, and the best one is recommended for wind turbines installation for maximising wind to energy generation. Although it is understood that the wake effect occurs on any wind farm, it is observed that wake losses can be minimised through the proper design of the wind generators’ placement layout. Therefore, any wind farm project should, from its layout, examine the optimal wind farm arrangement, which will depend on the wind speed, wind direction, turbine hub height, and other topographical characteristics of the area. In that context, considering the topographic and climate features of Mozambique, the study brings novelty in the way wind farms should be placed in the district and wake losses minimised. The study is based on a real assumption that the project can be implemented in the district, and thus, considering the wind farm’s capacity, the district’s energy needs could be met. The optimal transversal and longitudinal distances between turbines recommended are 8Do and 10Do, respectively, arranged according to layout 1, with wake losses of about 1.7%, land utilisation of about 6.46 Km2, and power output estimated at 71.844 GWh per year.

Researching on interaction between wind farm and power system, it usually uses simple model to describe the wind farm. The wind turbines in a wind farm always suppose as a coherent generator group, every wind turbines have identical wind speed. As wind turbine locates in the different site in the wind farm, the wind speed at each wind turbines will not change simultaneously. Wake effect is another factor that should take into consideration. So, it needs to get wind speed equivalent model. The equivalent model of wind speed in the wind farm is based on output of power. Gust wind and ramp wind are discussed. Wind farm will change gust wind into step varying wind and make ramp wind into different type wind. The arrangement of wind turbines will also affect equivalent model of wind speed. The result show that the length of wind farm will smooth the power output. It explains why the power output fluctuation of wind farm is smaller than single wind turbine. The onshore wind farm located in Dongtai Jiangsu province is proposed as an example. The equivalent wind speed model and equivalent impedance connected to grid are calculated. The results illustrate the impact of wind speed model on wind farm output.

This paper presents an analysis of most commonly used DG technology for the loss minimization with a contribution towards improving the power efficiency and power quality of distribution system. Wind power as DG is considered and the hourly performance has been analyzed using a standard IEEE 28 bus radial distribution system. A new Load Impedance Matrix (LIM) method is implemented for load flow study. Uncertainty in wind speed distribution is generated on a six-hour gap using Kernel Density Estimation (KDE) and Monte Carlo Simulation (MCS). A wind farm is designed with the certain irregular arrangement of wind turbines. The downstream wind turbines in the wind farm experiences wake effect due to the disturbed wind flow caused by upstream wind turbines. Wake effect reduces the effective wind speed and hence the power generation from the wind. The wake generated wind speed depends on the distance between the turbines. The effect of wake on free wind speed for several horizontally varying distances is presented in this paper. A new wind farm layout is availed to minimize the wake effect as well as the optimized power output extraction from minimum wind farmland area. The hourly air density effect is also considered for the calculation of hourly wind power generation. The wind powered DG sizing and location are determined by Grey Wolf Optimization (GWO) technique. This gives the most minimum line losses in the test distribution network.

Wind power is also known as junk. This is because wind power fluctuations affect the security and stability operation. Wind power wind turbines created is mainly concerned with the speed of wind. Because of the wind direction uncertain, intermittent, and wake effects between each unit wind farm, wind turbines cannot make that kind of power according to the demand for energy as conventional generators. Due to the lack of experimental data, assess the volatility of wind power is still a lack of effective methods. This article studies the sample in a northeast wind farm power, and based on a sliding differential algorithm, distribution fitting and quantitative calculations describe the characteristics of wind power fluctuations. This article studies the sample in a northeast wind farm power, and based on a sliding difference algorithm, through the analysis showed that wind power fluctuations obey t location scale distribution. And it is affected by factors such as spatial and temporal distribution, there is a big difference between the output power fluctuation characteristics of wind farm output power and single wind turbine. This is due to the wind turbine suffered varying differences, and wake effects between field units, making the distribution of frequent power fluctuations; relative to a single unit, the fluctuation of the whole wind farm is more gentle, that is to say with the spatial distribution increased scale, wind power fluctuations presents certain "gentle effect."

Large scale wind power penetration has a significant impact on the reliability of the electric generation systems. A wind farm consists of a large number of wind turbine generators (WTGs). A major difficulty in modeling wind farms is that the WTG not have an independent capacity distribution due to the dependence of the individual turbine output on the same energy source, the wind. In this paper, a model of the wind farm output power considering multi-wake effects is established according to the probability distribution of the wind speed and the characteristic of the wind generator output power: based on the simple Jenson wake effect model, the wake effect with wind speed sheer model and the detail wake effect model with the detail shade areas of the upstream wind turbines are discussed respectively. Compared to the individual wake effect model, this model takes the wind farm as a whole and considers the multi-wakes effect on the same unit. As a result the loss of the velocity inside the wind farm is considered more exactly. Furthermore, considering the features of sequentially and self-correlation of wind speed, an auto-regressive and moving average (ARMA) model for wind speed is built up. Also the reliability model of wind farm is built when the output characteristics of wind power generation units, correlation of wind speeds among different wind farms, outage model of wind power generation units, wake effect of wind farm and air temperature are considered. Simulation results validate the effectiveness of the proposed models. These models can be used to research the reliability of power grid containing wind farms, wind farm capacity credit as well as the interconnection among wind farms

In order to clarify the wake effect behind wind turbines of a wind farm located on a complex terrain, Computational Fluid Dynamics (CFD) simulations were performed with the WindModeller software, which is a module for wind farm simulation developed by ANSYS. The wake is modelled using an actuator disc model approach which is based on the wind turbine thrust coefficient and wind speed. A WindModeller simulation was carried out for DBK wind farm located on Jeju Island, Korea. The nacelle wind speed data from 15 Hanjin 2MW turbines were collected through the Supervisory Control And Data Acquisition (SCADA) system. The wind data was measured from a 80m tall met mast near the wind farm, which was used as a reference. The WindModeller module simulated the wind speed and turbulence intensity within the terrain with a wind speed of 9.3 m/s and a wind direction of 314 degrees. The wakes from single and multiple turbines were predicted by the WindModeller simulation were compared with the actual wind data from the SCADA system. Then, the wake effect was analyzed with the distance between the wind turbines. As a result, the wake effect predicted by the WindModeller simulation was greater than the actual wake effect. The actual wind speed ratio decreased by 22% and 35% when the turbines were separated with the distances of 3.1 and 5.8 times rotor diameters, respectively. The wake effect behind multiple wind turbines is revealed in this paper.