Control Strategy For Wind Farm Research Articles

Control strategy for DC series-connected wind farm without energy curtailment

With lower construction costs and power losses, the DC wind farm (DCWF) based on series-connected DC wind turbines (DCWT) is a potential collection scheme for large-scale offshore wind power. However, energy curtailment caused by unequal wind speed exists in DCWTs and results in energy waste, weakening the advantages of DCWTs. The energy curtailment mechanism is analyzed for DCWF, where single active bridge (SAB) is used as DC/DC converter in DCWTS and a full-bridge modular multilevel converter (FB-MMC) as the receiving end converter. The linear relationship between input and output of single active bridge (SAB) is interpreted, and a novel coordinate control strategy for DCWF is proposed to solve the wind energy curtailment caused by unequal wind speed. In addition, an auxiliary control strategy for receiving end converter is proposed to reduce the loss on HVDC link. A complete DCWF is built in PSCAD/EMTDC software package, and the results show that the proposed control strategy makes DCWF can operate well without energy curtailment under unequal wind speeds.

Active power control strategy for wind farms based on power prediction errors distribution considering regional data.

One of the renewable energy resources, wind energy is widely used due to its wide distribution, large reserves, green and clean energy, and it is also an important part of large-scale grid integration. However, wind power has strong randomness, volatility, anti-peaking characteristics, and the problem of low wind power prediction accuracy, which brings serious challenges to the power system. Based on the difference of power prediction error and confidence interval between different new energy power stations, an optimal control strategy for active power of wind farms was proposed. Therefore, we focus on solving the problem of wind power forecasting and improving the accuracy of wind power prediction. Due to the prediction error of wind power generation, the power control cannot meet the control target. An optimal control strategy for active power of wind farms is proposed based on the difference in power prediction error and confidence interval between different new energy power stations. The strategy used historical data to evaluate the prediction error distribution and confidence interval of wind power. We use confidence interval constraints to create a wind power active optimization model that realize active power distribution and complementary prediction errors among wind farms with asymmetric error distribution. Combined with the actual data of a domestic (Cox’s Bazar, Bangladesh) wind power base, a simulation example is designed to verify the rationality and effectiveness of the proposed strategy.

Control Strategy for Offshore Wind Farms with DC Collection System Based on Series-Connected Diode Rectifier

The DR-HVDC (Diode rectifier-based HVDC) transmission topology was recently proposed for integration on large offshore wind farms due to its low investment cost and high reliability. To further reduce the investment, a DC collection topology based on the series-connected diode rectifiers (DR) is proposed, where no offshore platform is needed. However, units of series-connected topology (SCU) show coupling issues, such as overvoltage, energy curtailment, and fault isolation. First, the coupling mechanism is analyzed, and a suitable operation mode for SCUs is selected to ensure the safe operation of the DC system. Then, the linear relationship of active power and output DC current and DC voltage of SCUs is analyzed, and a novel coordinate control strategy for DC wind farms is proposed, where an onshore converter adapts a DC current controller and wind turbines adapt a mediate output voltage control strategy. The mediate output voltage control strategy includes a triple loop with power loop, mediate output voltage loop, and current loop. Also, the DC open line fault, DC grounding fault, and AC grounding fault of the onshore grid are investigated, and a protection strategy is proposed. A 160 MW wind farm with a DR-SCU DC collection system is built in PSCAD/EMTDC to verify the validity of the proposed control strategy under unequal wind speeds, DC fault, and onshore AC fault, and the results validate the performance of the proposed strategy.

Reactive Voltage Control Strategy for PMSG-Based Wind Farm Considering Reactive Power Adequacy and Terminal Voltage Balance

To improve the ability of the power system to accommodate high penetration wind power, wind turbines (WTs) need to realize the mode transformation from grid-following to grid-forming, thus actively participating in the voltage regulation of the power grid with a high proportion of wind power. In this work, a reactive voltage control strategy for wind farms considering reactive power adequacy and terminal voltage balance is proposed. Firstly, the expression of the maximum reactive power regulation capacity of WT, namely reactive power adequacy, is derived under the complete wind condition based on the mathematical model and operating characteristics of WT, to study the influence of wake effect on reactive power adequacy of a wind farm. Then, the point of common coupling (PCC) voltage and terminal voltage are expressed analytically based on the radiative topology equivalent model of a wind farm, to analyze the influence of electrical distance on active power loss of wind farm. Finally, the calculation method of the adaptive gain coefficient of WT is put forward, which comprehensively considers the input wind speed and the electrical distance, to regulate the PCC voltage and terminal voltage simultaneously. The comprehensive effectiveness of the proposed strategy is demonstrated on a permanent magnet synchronous generator (PMSG)-based wind farm integration simulation model. While supporting the PCC voltage, the proposed strategy maintains the balance of the terminal voltage in the wind farm, thereby improving the friendliness of wind power grid connection.

Optimal Power Coordinated Control Strategy for DFIG-Based Wind Farm to Increase Transmission Capacity of the LCC-HVDC System Considering Commutation Failure

The line commutated converter (LCC)-based high voltage direct current (HVDC) transmission system is an effective scheme for long-distance transmission of wind power. Commutation failure is a common failure of LCC-HVDC transmission system. During the commutation failure, the overvoltage of the sending alternating current (ac) grid will occur to disconnect the wind farm from the utility grid and limit the transmission capacity of the system. It is necessary to suppress the overvoltage of the sending ac grid under commutation failure to increase the transmission capacity of the LCC-HVDC system. In this article, a mathematical model of the transient overvoltage peak value of the sending ac grid under commutation failure is established. The mathematical model can quantitatively analyze the influence of the reactive power of the wind farm and the transmission capacity of the LCC-HVDC system on the overvoltage peak value of the sending ac grid. Based on the mathematical model, a power coordinated control strategy for wind farms is proposed to improve the reactive power support capability under grid overvoltage. The proposed control strategy can effectively suppress the overvoltage of the sending ac grid and increase the transmission capacity of the LCC-HVDC system. The accuracy of the mathematical model is verified by simulation, and the superiority of the power coordinated control strategy is verified by the control hardware-in-the-loop (CHIL) experiment.

On the load impact of dynamic wind farm wake mixing strategies

In recent studies, the effectiveness of different so-called wake mixing strategies has been assessed in terms of wind farm power maximization. These studies show that by dynamically varying the pitch angles of a wind turbine, wake mixing can be enhanced to increase the overall power production of a wind farm. However, such strategies also increase the loads experienced by the turbine, which may disqualify such methods as viable wind farm control strategies. In this paper, an extensive analysis of the load effects of two specific wake mixing strategies, Dynamic Induction Control (DIC) and the helix approach, is presented. The damage equivalent load of critical components such as the turbine blades and tower is assessed, and the risk of fatigue damage on the blade pitch bearings is determined. This paper therefore contributes to determining the implementability of such wake mixing strategies in wind farms of the future.

Investigating the impact of atmospheric conditions on wake-steering performance at a commercial wind plant

Wake steering is a wind farm control strategy in which upstream wind turbines are misaligned with the wind to deflect their wakes away from downstream turbines, thereby increasing net energy production. But research suggests that the effectiveness of wake steering strongly depends on atmospheric conditions such as stability. In this paper, we investigate results from a two-turbine wake-steering experiment at a commercial wind plant to assess the impact of stability and five other atmospheric variables on wake-steering performance. Specifically, for different atmospheric condition bins we compare the ability of the controller to achieve the intended yaw offsets, the power gain from wake steering, and the reduction in wake losses. Further, we analyze wake-steering performance as a function of wind speed to eliminate the confounding impact of different wind speed distributions in different atmospheric conditions. Overall, we find that wind direction standard deviation is the best predictor of wake-steering performance, followed by turbulence intensity and turbulent kinetic energy. The results suggest the importance of adapting wake-steering control strategies to different atmospheric conditions.

Wind-Farm Power Tracking Via Preview-Based Robust Reinforcement Learning

This article aims to address the wind-farm power tracking problem, which requires the farm's total power generation to track time-varying power references and, therefore, allows the wind farm to participate in ancillary services such as frequency regulation. A novel preview-based robust deep reinforcement learning (PR-DRL) method is proposed to handle such tasks which are subject to uncertain environmental conditions and strong aerodynamic interactions among wind turbines. To our knowledge, this is for the first time that a data-driven model-free solution is developed for wind-farm power tracking. Particularly, reference signals are treated as preview information and embedded in the system as specially designed augmented states. The control problem is then transformed into a zero-sum game to quantify the influence of unknown wind conditions and future reference signals. Built upon the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_\infty$</tex-math></inline-formula> control theory, the proposed PR-DRL method can successfully approximate the resulting zero-sum game's solution and achieve wind-farm power tracking. Time-series measurements and long short-term memory networks are employed in our DRL structure to handle the non-Markovian property induced by the time-delayed feature of aerodynamic interactions. Tests based on a dynamic wind-farm simulator demonstrate the effectiveness of the proposed PR-DRL wind-farm control strategy.

Research on Fault Ride Through Control Strategy of Wind Farm via MMC-HVDC Networking System

Large-scale long-distance grid connection of wind farms has problems such as high line losses and small transmission capacity. The use of modular multilevel flexible direct current transmission (MMC-HVDC) for power transmission is an effective solution. And the recovery of system safety and stability under fault conditions is a hot spot for research. For the problem of DC bus voltage rise caused by symmetrical faults on the grid side, the AC voltage step-down method of the wind farm side converter station (WFMMC) is used for coordinated control with the self-regulating energy-consuming circuit. The capacity required for the self-regulating dissipation resistor is reduced while ensuring that the wind farm networked MMC-HVDC system can traverse the fault stably and smoothly; And the controller for suppressing negative sequence current is designed to effectively mitigate the three-phase current imbalance caused by asymmetric faults occurring on the grid side. The active power is transferred to the grid side while protecting the switching devices from damage. Finally, the correctness and effectiveness of the proposed scheme are verified in the PSCAD/EMTDC simulation software.

Three‐stage robust voltage/var optimal control of wind farms at multiple time scales

In wind farms, the uncertainty of wind power and the incoordination of multiple time scales increase the difficulty of voltage/var control (VVC), and result in the reactive power output of VVC devices becoming unreasonable. This will decrease the power quality and even cause the voltage collapse of wind farms at large voltage deviations. For these problems, hierarchical control of VVC devices is a promising solution, as VVC devices can adjust the reactive power output in different control strategies. Therefore, this paper proposes a three-stage robust voltage/var optimal control strategy for wind farms. The robust optimization model is introduced to solve the VVC problem caused by the uncertainty of wind power in this strategy. Besides, compared with traditional VVC strategies, the proposed strategy can coordinate different control stages and VVC devices at multiple time scales by combining centralized and local VVC strategies, which achieves voltage/var optimal control objectives. Simulation results demonstrate the good performance of the proposed strategy in mitigating system voltage violation rate and power loss of the wind farm.

A two-layer control strategy of the wind farm participating in grid frequency regulation

This paper proposes a two-layer control strategy of wind farm participating in grid frequency regulation for problems caused by the direct switching of FR power distribution and wind turbine control strategy. At the wind farm layer, FR scenarios are divided. And a turbine grouping strategy is proposed according to the running status at the current and next moments, and the current system FR demand, i.e., increase or decrease power. According to the FR capability of wind turbines, the turbines are arranged to participate in FR in sequence. Consequently, the power support for the corresponding frequency fluctuation of the wind turbine is achieved, and the insufficient FR capacity caused by equal distribution is avoided. At the turbine layer, a proportional coefficient model is created based on the optimized combination FR mode of participating in FR. As a result, smooth switching of different FR modes is realized without modifying the original turbine structure. It makes upgrades simple and easy. A simulation model including four turbines and two domains is created in Matlab/Simulink, verifying the validity of the proposed strategy.

An Active Voltage Coordinate Control Strategy of DFIG-Based Wind Farm with Hybrid Energy Storage System

In a power system with wind farms, the point of common coupling (PCC) usually suffers from voltage instability under large wind speed variations and the load impact. Using the internal converter of a doubly fed induction generator (DFIG)-based wind turbine to provide voltage support auxiliary service is an effective scheme to suppress the voltage fluctuation at PCC. To satisfy the reactive power demand of the connected grid, an active voltage coordinate control strategy with the hybrid energy storage system of the wind farm is proposed. The dynamic reactive power balance model is established to show the interaction between the reactive power limitation of the wind farm and the reactive power compensation demand of the grid. This indicates the initial conditions of the active voltage coordinate control strategy. According to the critical operating point and the operation state of the DFIG, the active and reactive power coordinate control strategy composed of active ω-β coordinate control and active β control is proposed to enhance the reactive power support capability and stabilize the grid voltage. To compensate the active power shortage, an auxiliary control strategy based on the hybrid energy storage system is introduced. The simulation results show that the proposed strategy can suppress the voltage fluctuation effectively and make full use of primary energy.

Impact of the wake deficit model on wind farm yield: A study of yaw-based control optimization

The exploitation of offshore wind resources is considered to have considerable potential in providing carbon-free energy. To increase the economic viability of wind farms, improvement in power generation is sought by mitigating the wake losses. While the industrial standards still favour turbine-level power maximization, the concept of collaborative yaw-based plant-level control has gained significant attention in recent years. The present work investigates the potential of such a wind farm control strategy employing different wake deficit models, for a range of atmospheric conditions and plant layouts. The utilized wake velocity deficit models are the top-hat Jensen model, the Gaussian-shaped Bastankhah model and its novel extension, termed Gauss–Curl Hybrid model, which accounts for secondary steering effects. The yaw control optimization is conducted on a row of eight NREL 5-MW turbines using the FLORIS modelling utility and the SLSQP optimization algorithm. Generally speaking, the Jensen model shows a lack of robustness and is not recommended for yaw control studies. In contrast, the two Gaussian-shaped models are well handled by the optimization algorithm and produce consistent results. More specifically, the Bastankhah model prefers yaw offsets of nearly equal magnitude throughout the whole wind farm except for the most downstream machine that remains aligned with the freestream. On the other hand, the GCH model suggests a large offset at the most upstream turbine, which is gradually reduced at consecutive machines. For the reference wind farm considered, the total power improvement was 3.59% and 14.66% for the Bastankhah and GCH models, respectively.

Results from a wake-steering experiment at a commercial wind plant: investigating the wind speed dependence of wake-steering performance

Abstract. Wake steering is a wind farm control strategy in which upstream wind turbines are misaligned with the wind to redirect their wakes away from downstream turbines, thereby increasing the net wind plant power production and reducing fatigue loads generated by wake turbulence. In this paper, we present results from a wake-steering experiment at a commercial wind plant involving two wind turbines spaced 3.7 rotor diameters apart. During the 3-month experiment period, we estimate that wake steering reduced wake losses by 5.6 % for the wind direction sector investigated. After applying a long-term correction based on the site wind rose, the reduction in wake losses increases to 9.3 %. As a function of wind speed, we find large energy improvements near cut-in wind speed, where wake steering can prevent the downstream wind turbine from shutting down. Yet for wind speeds between 6–8 m/s, we observe little change in performance with wake steering. However, wake steering was found to improve energy production significantly for below-rated wind speeds from 8–12 m/s. By measuring the relationship between yaw misalignment and power production using a nacelle lidar, we attribute much of the improvement in wake-steering performance at higher wind speeds to a significant reduction in the power loss of the upstream turbine as wind speed increases. Additionally, we find higher wind direction variability at lower wind speeds, which contributes to poor performance in the 6–8 m/s wind speed bin because of slow yaw controller dynamics. Further, we compare the measured performance of wake steering to predictions using the FLORIS (FLOw Redirection and Induction in Steady State) wind farm control tool coupled with a wind direction variability model. Although the achieved yaw offsets at the upstream wind turbine fall short of the intended yaw offsets, we find that they are predicted well by the wind direction variability model. When incorporating the expected yaw offsets, estimates of the energy improvement from wake steering using FLORIS closely match the experimental results.

Active power control strategy of wind farm considering fatigue load of wind turbines

For the purpose of maximize the utilization of wind energy and reduce the generation cost of wind farms, an active power control strategy of wind farm considering the fatigue load intensity of wind turbines was proposed. Turbulence intensity, average wind speed and active power command were used to evaluate the comprehensive fatigue load strength of the wind turbine. Then an improved particle swarm optimization algorithm was applied to optimize the active power distribution of each wind turbine, which maximize wind energy capture and keep the fatigue load intensity of each wind turbine within a certain allowable range. The effectiveness is proved by the analysis of an example. The results show that the control strategy is helpful to reduce the fatigue load intensity and reduce the operation and maintenance of the WF and the cost of power generation, which can improve the economy of the power system.

Optimization Control Strategy for Large Doubly-Fed Induction Generator Wind Farm Based on Grouped Wind Turbine

This paper proposes a grouped, reactive power optimization control strategy to maximize the active power output of a doubly-fed induction generator (DFIG) based on a large wind farm (WF). Optimization problems are formulated based on established grouped loss models and the reactive power limits of the wind turbines (WTs). The WTs in the WF are grouped to relieve computational burden. The particle swarm optimization (PSO) algorithm is applied to optimize the distribution of reactive power among groups, and a proportional control strategy is used to distribute the reactive power requirements in each group. Furthermore, the proposed control strategy optimizes the reactive power distribution between the stator and the grid side converter (GSC) in each WT. The proposed control strategy greatly reduces the number of variables for optimization, and increases the calculation speed of the algorithm. Thus, the control strategy can not only increase the active power output of the WF but also enable the WF to track the reactive power dispatching instruction of the power grid. A simulation of the DFIG WF is given to verify the effectiveness of the proposed control strategy at different wind speeds and reactive power references.

MPC Based Coordinated Active and Reactive Power Control Strategy of DFIG Wind Farm with Distributed ESSs

The ESS is considered as an effective tool for enhancing the flexibility and controllability of a wind farm, and the optimal control scheme of a wind farm with distributed ESSs is vital to the stable operation of wind power generation. In this paper, a coordinated active and reactive power control strategy based on model predictive control (MPC) is proposed for doubly fed induction generator (DFIG)-based wind farm (WF) with distributed energy storage systems (ESSs). The proposed control scheme coordinates the active and reactive power output among DFIG wind turbines (WTs), grid-side converters (GSCs), and distributed ESSs inside the WF, and the aim is to decrease fatigue loads of WTs, make the WT terminal voltage inside the extent practicable, and take the WF economic operation into consideration. Moreover, the best reactive power references of DFIG stator and GSC are produced independently based on their dynamics. At last, the control scheme generates optimal power references for all ESS to make the SOC of each ESS converge to their average state. With the distributed ESSs, the WF controller regulates the WTs inside WF more flexibly. A WF composed of 10 DFIG WTs was utilized to verify the control performance of the proposed coordinated active and reactive power control strategy.

Formulation of a wind farm control strategy considering lifetime of DC‐link capacitor bank of type IV wind turbines

The cost of energy should be minimised to increase market penetration of wind energy conversion systems. The existing wind farm control strategies are not helpful since they speed up the damage in upstream wind turbines. Therefore, a control strategy is proposed to maximise the energy yield while equalising lifetime of one of the most fragile sub-system of the wind turbines. The DC-link capacitor bank of the back-to-back converters is considered to this end. The proposed control strategy can be directly applied in systems based on type 4 wind turbines with full power converters. This exposition reveals the formulation of the control strategy by analysing the strengths and weaknesses of the existing strategies based on the maximum power output. The lifetime-based control strategy is extended to formulate a multi-stage reactive power dispatch method with the help of a total energy-based strategy. The effectiveness of all control strategies is validated using the model-based simulations.

Experimental investigation of wind turbine wake and load dynamics during yaw maneuvers

Abstract. This article investigates the far wake response of a yawing upstream wind turbine and its impact on the global load variation in a downstream wind turbine. In order to represent misalignment and realignment scenarios, the upstream wind turbine was subjected to positive and negative yaw maneuvers. Yaw maneuvers could be used to voluntarily misalign wind turbines when wake steering control is targeted. The aim of this wind farm control strategy is to optimize the overall production of the wind farm and possibly its lifetime, by mitigating wake interactions. While wake flow and wind turbine load modifications during yaw maneuvers are usually described by quasi-static approaches, the present study aims at quantifying the main transient characteristics of these phenomena. Wind tunnel experiments were conducted in three different configurations, varying both scaling and flow conditions, in which the yaw maneuver was reproduced in a homogeneous turbulent flow at two different scales and in a more realistic flow such as a modeled atmospheric boundary layer. The effects of yaw control on the wake deviation were investigated by the use of stereo particle imaging velocimetry while the load variation on a downstream wind turbine was measured through an unsteady aerodynamic load balance. While overall results show a nondependence of the wake and load dynamics on the flow conditions and Reynolds scales, they highlight an influence of the yaw maneuver direction on their temporal dynamics.

Control Strategy and Fault Protection for Series-Parallel DC Wind Farm

Control Strategy and Fault Protection for Series-Parallel DC Wind Farm