Coordinated Frequency Control Method for Multiple Wind Turbines to Avoid Secondary Frequency Drop

Virtual Inertia Control (VIC) provided by Wind Turbines (WTs) can contribute to frequency support in electrical power networks. For this reason, in addition to conventional systems such as power plants and battery storage systems, new and existing wind farms are of interest to VIC. WTs with Doubly-Fed Induction Generators (DFIGs) have VIC limitations when operating at low rotor frequency, which leads to higher temperature stress on semiconductors and thus constraints on lifetime and power output. This work presents a novel control method that effectively limits the rotor current and adjusts the reactive power supplied by the rotor-side inverter during frequency support. The WTs’ speed recovery following a VIC event is also taken into consideration. Temperature simulations for power semiconductors are presented and discussed. Flexible current limiting and reactive power control for the rotor-side inverter are presented and analyzed.

This paper investigates virtual inertia control of doubly fed induction generator (DFIG)-based wind turbines to provide dynamic frequency support in the event of abrupt power change. The model and control scheme of the DFIG is analysed. The relationships among the virtual inertia, the rotor speed and the network frequency variation are then investigated. The hidden kinetic energy that can be released to contribute to the grid inertia by means of shifting the operating point from the maximum power tracking curve to a virtual inertia control curve is investigated. The virtual inertia control strategy based on shifting power tracking curves of the DFIG is proposed and the calculation method for determining these virtual inertia control curves is presented. A three-machine system with 20 percent of wind penetration is used to validate the proposed control strategy. Simulation results show that by the proposed control strategy, DFIG based wind farms have the capability of providing dynamic frequency support to frequency deviation, and thus improving the dynamic frequency performance of the grid with high wind power penetration. (6 pages)

Floater motions introduce unsteadiness in the aerodynamics of floating offshore wind turbines. The aerodynamics of a wind turbine after three perturbations are studied: a blade pitch step, a rotor speed step for which dynamic inflow is expected, and a surge velocity step. The free vortex wake method and an analytical helical vortex model based on the Joukowsky rotor model are used to study the dynamic behavior of the induced velocity at the blades. As expected, the dynamic inflow effect is clear for the blade pitch and rotor speed changes, but for a surge velocity step, the models show that very little dynamic inflow effect takes place because the velocity induced by the vortex helix is not significantly modified: the tip vortex helix circulation change is partially compensated by the geometry change of the helix. For the rate of change, the velocities induced on the rotor by the vortex helix for the pitch and rotor speed changes show a rapid adjustment at the blade tip, with a slower change throughout the rest of the blade and at the center of the rotor. The convection velocity of the tip vortices is shown to be the main variable of the temporal evolution of the dynamic inflow effect.

Participation of the wind turbine generators (WTGs) in the frequency regulation service is an appealing issue in order to consider the safe increasing of the wind power generation. The droop and virtual inertia control are the most popular approaches that facilitate the WTGs to provide frequency regulation. However, the intermittent nature of the wind complicates the implementation of these methods and has impacts on the wind turbine stability and may cause violation of the allowed power reserve and minimum turbine rotor speed. Therefore, in this paper, a control approach based on the dynamic de-loading technique is proposed, where the wind turbine operating curve is dynamically adjusted in the response of the frequency deviation throughout controlling the turbine tip-speed ratio which helps the turbine provide steady-state power sharing within the reserved power as well as the transient response within its stability criteria. In addition, the inertial response based on a dynamic gain is suggested. The inertial weighting gain has been formulated where it is continuously regulated in the response of rotor speed and reflects the amount of available kinetic energy in the rotating mass. The effectiveness of the proposed control approaches is verified throughout the comparisons of the results with the fixed inertial gain control and the droop control. The simulation results confirm that the combined control of the proposed tip-speed ratio and dynamic inertia control improve the overall system dynamic behavior in terms of frequency response and turbine stability.

As the wind power penetration increases, the frequency stability of the power system is deteriorating. Thus, it is expected that the wind power plants (WPPs) will be required to produce the inertial response during the short-term large-scale frequency disturbances. To study the effects of the inertial response of the WPP, the dynamic equivalent model (DEM) of the WPP should be able to emulate the inertial response of the actual WPP. Otherwise, the simulated system frequency would be different from the actual one. Therefore, the inertial response identification algorithm (IRIA) is proposed in this paper. The IRIA is able to identify the values of the droop gain and the inertia constants of the WPP according to the actual system frequency and the active power output of the actual WPP. The simulation results demonstrate that the DEM of the WPP and the actual WPP have similar responses of the active power output and the rotor speed under two frequency disturbances. In addition, the FNs of the simulated and actual system frequencies are very close. As a results, the effectiveness of the IRIA is successfully proved.

Accordingto recent grid codes, large-scale wind turbines (WTs) are required to provide fast frequency response (FFR). The existing stepwise inertial control methods suggest immediate incremental power injection by WTs, followed by the abrupt over-production termination to avoid over-deceleration of the rotor speed. These methods have a drawback that they impose severe secondary frequency drops (SFD), or they consider an unrealistic constant wind speed during their inertial control support. This paper proposes a novel Gaussian distribution-based inertial control (GDBIC) scheme that can improve the frequency nadir without rotor speed over-deceleration. Upon detecting a power imbalance, WT increases the output power with an incremental power and declines it following Gaussian distribution trajectory controlled by a standard deviation parameter, ensuring by this convergence of the rotor speed to a stable equilibrium. The proposed scheme is also capable of responding to a second cascade event. The performance of the GDBIC is tested on the wind-integrated IEEE 9-bus system and the IEEE 39-bus system in DIgSILENT PowerFactory. It is also compared with other methods reported in literature. Furthermore, experimental tests are used to verify the performance of the proposed scheme, using two different hardware-in-the-loop testing facilities. The blade fatigue is studied using Fatigue, Aerodynamics, Structures, and Turbulence (FAST) Code. The simulation and experimental results showed that the release of the kinetic energy in rotors using the proposed GDBIC scheme allows significant improvement of the frequency nadir, with no SFD, as well as contribute to reliable operation during abrupt wind changes.

As wind energy adoption is growing, ensuring the efficient operation and maintenance of wind turbines becomes essential for maximizing energy production and minimizing costs and downtime. Many AI applications in wind energy, such as in condition monitoring and power forecasting, may benefit from using operational data not only from individual wind turbines but from multiple turbines and multiple wind farms. Collaborative distributed AI which preserves data privacy holds a strong potential for these applications. Federated learning has emerged as a privacy-preserving distributed machine learning approach in this context. We explore federated learning in wind turbine condition monitoring, specifically for fault detection using normal behaviour models. We investigate various federated learning strategies, including collaboration across different wind farms and turbine models, as well as collaboration restricted to the same wind farm and turbine model. Our case study results indicate that federated learning across multiple wind turbines consistently outperforms models trained on a single turbine, especially when training data is scarce. Moreover, the amount of historical data necessary to train an effective model can be significantly reduced by employing a collaborative federated learning strategy. Finally, our findings show that extending the collaboration to multiple wind farms may result in inferior performance compared to restricting learning within a farm, specifically when faced with statistical heterogeneity and imbalanced datasets.

Experimental evaluation of a tree-shaped quad-rotor wind turbine on power output controllability and survival shutdown capability

To integrate renewable energy into microgrids with a favorable inertia property, a virtual inertia control application is needed. Considering the inertia emulation capabilities, insufficient emulation of inertia power due to the lower and short-term power of storage systems could significantly cause system instability and failure. To enhance such capability, this paper applies a virtual inertia control topology to the superconducting magnetic energy storage (SMES) technology. The SMES-based virtual inertia control system is implemented in a microgrid with renewables to emulate sufficient inertia power and maintain good system frequency stability. The efficacy and control performance of the proposed control method are compared with those of the traditional virtual inertia control system. Simulation results show that the shortage of system inertia due to renewable penetration is properly compensated by the proposed control method, improving system frequency stability and maintaining the robustness of system operations.

With the conventional power supply being replaced by a large number of wind power and the investment of ultra‐high‐voltage transmission channels, the operating characteristics of the power system have undergone profound changes, and the characteristics of power electronics have become increasingly evident. The dynamic characteristics of DFIG (double‐fed induction generator) with virtual inertia control are in a coupling relationship with the dynamic characteristics of the power system, which leads to significant changes in the frequency oscillation characteristics of the wind turbine. The intrinsic mechanism and external performance of the sub and super‐synchronous oscillating systems are essentially different from those of conventional wind turbines. Based on the analysis of oscillation mechanism and stability of traditional wind turbines, this study reviews the literature and summarises the existing key technical problems. Secondly, the eigenvalue analysis and simulation are used to demonstrate the influence of virtual inertia on the sub and super‐synchronous oscillations of wind turbines.

Reconstructable dynamic simulation models of modern variable-speed wind turbines (WTs), which are integrable into any simulation software, are crucial to the scientists investigating the contribution of WTs to counteracting the current power system stability issues. The structural similarity between a doubly fed induction-generator-based (DFIG-based) WT model and a full-scale-convertor-based (FSC-based) WT model using induction generator offers the possibility of integrating them into a combined modular model with little effort and the same used parameter set. This article presents a combined root mean square (RMS) WT model, which contains a DFIG-based WT and a FSC-based WT using induction generator. The model is designed based on fundamental machine and converter equations and can be applied for classical network stability analyses. Furthermore, analogous well-performing initialization procedures for both DFIG-based and FSC-based WT models are also introduced. As an example, to demonstrate the performance of the WT model in frequency stability studies, the model is extended with a droop-based fast frequency response (FFR) controller and is implemented in a MATLAB-based RMS simulation tool. The results of the case studies confirmed a solid functionality of initialization procedures. Furthermore, they illustrate feasible and comparable general behavior of both WT models as well as their plausible responses in the event of a frequency drop in a 220 kV test system.

Recently, with the large-scale integration of renewable energy sources into microgrid (μGs) power electronics, distributed energy systems have gained popularity. However, low inertia reduces system frequency stability and anti-disturbance capabilities, exposing power quality to intermittency and uncertainty in photovoltaics or wind turbines. To ensure system stability, the virtual inertia control (VIC) is presented. This paper proposes two solutions to overcome the low inertia problem and the surplus in capacities resulting from renewable energy sources. The first solution employs superconducting magnetic energy storage (SMES), which can be deemed as an efficient solution for damping the frequency oscillations. Therefore, in this work, SMES that is managed by a simple proportional-integral-derivative controller (PID) controller is utilized to overcome the low inertia. In the second solution, the hydrogen storage system is employed to maintain the stability of the microgrid by storing surplus power generated by renewable energy sources (RESs). Power-to-Power is a method of storing excess renewable energy as chemical energy in the form of hydrogen. Hydrogen can be utilized locally or delivered to a consumption node. The proposed μG operation demonstrates that the integration of the photovoltaics (PVs), wind turbines (WTs), diesel engine generator (DEG), electrolyzer, micro gas turbine (μGT), and SMES is adequate to fulfill the load requirements under transient operating circumstances such as a low and high PV output power as well as to adapt to sudden changes in the load demand. The effectiveness of the proposed schemes is confirmed using real irradiance data (Benban City, Egypt) using a MATLAB/SIMULINK environment.

Security assessment method for inertia and frequency stability of high proportional renewable energy system

With the increasing penetration of renewable energy generators in power grid, many inertia emulation control strategies have been raised to solve the problem of reduced power system inertia. A co-simulation research platform is built based on RTDS and GH Bladed, detailed comparisons are made in terms of inertia response performance, weak grid operation stability, secondary frequency drop and wind tower load analysis. Research results point out that different control schemes are similar in inertia response while virtual synchronous generator control (VSG) and inertial synchronization control (ISynC) can improve weak grid operation stability, VSG strategy is also effective in reducing frequency secondary drop and wind tower fatigue load, the combination of VSG and ISynC can get the best control results.

In this project, performance of bearing lubricant for wind turbine were analyzed. The experimental equipment includes fans, anemometers, generators, rectifiers and voltage stabilizers. carbon steel sheet is used as the wind turbine skeleton which was matched with the position of the lock hole of the bearing fixing seat, and is fixed and well-constructed. Material of blades was assembled using aluminum alloy and the fan was driven by a fixed air source in experiment. Power generation of wind turbine as well as vibration data of bearing of wind turbine were investigated. The vibration frequency spectrum of bearing was regularly measured under normal circumstances. Lubrication performance and power generation were investigated by comparison with two different lubrications. The experimental results can be obtained by checking the rotation speed and power generation efficiency of different greases. Though there was no obvious change in rotation speed and power generation, the RMS diagram of vibration spectrum shows a decreased trend. A simple test model using a fan motor was set up for vibration test. The rotation speed was increased in a specific formula of grease that compared with a general grease, which can also be read from the frequency spectrum in vibration test.