Comparative study between HDP and PSS on DFIG damping control

Approximate dynamic programming based supplementary reactive power control for DFIG wind farm to enhance power system stability

A single machine-infinite-bus (SMIB) system including the interline power flow controllers (IPFCs) and the power system stabilizer (PSS) controller is addressed. The linearized system model is considered for investigating the interactions among IPFC and PSS controllers. To improve the stability of whole system again different disturbances, a lead-lag controller is considered to produce supplementary signal. The proposed supplementary controller is implemented to improve the damping of the power system low frequency oscillations (LFOs). Imperialist optimization algorithm (ICA) and shuffled frog leaping algorithm (SFLA) are implemented to search for optimal supplementary controllers and PSS parameters. Moreover, singular value decomposition (SVD) method is utilized to select the most effective damping control signal of IPFC lead-lag controllers. To evaluate the system performance, different operating conditions are considered. Reponses of system in five modes including uncoordinated and coordinated modes of IPFC and PSS using ICA and SFLA are studied and compared. Considering the results, response of system without controller shows the highest overshoot and the longest settling time for rotor angel at the different operating conditions. In this mode of system, rotor speed has the highest overshoot. Rotor angel in the system with only PSS includes lower overshoot and oscillation than system without controller. When PSS is only implemented, rotor speed deviation has the longest settling time. Rotor speed deviation in the uncoordinated mode of IPFC and PSS shows lower overshoot than system with only PSS and without controller. It is noticeable that in this mode, rotor angel has higher overshoot than system with only PSS. The superiority of the suggested ICA-based coordinated controllers is obvious compared with SFLA-based coordinated controllers and other system modes. Responses of coordinated PSS and IPFC SFLA-based supplementary controllers include higher peak amplitude and longer settling time compared with coordinated IPFC and PSS ICA-based controllers. This comparison shows that overshoots, undershoots and the settling times are reduced considerably in coordinated mode of IPFC based controller and PSS using ICA. Analysis of the system performance shows that the proposed method has excellent response to different faults in power system.

With large wind energy integration into power systems, wind farms begin to influence power systems in a much more significant manner. As wind energy systems utilize different generator technologies from the one utilized in the conventional power plants, the steady-state, transient and small-signal dynamics, as well as, power system stability will thus be significantly affected. The impact of wind energy systems on the power system dynamics and stability is thus of practical importance. As there is a significant increase in installation of wind turbines equipped with doubly-fed induction generator (DFIG) in recent years, a dynamic model of the DFIG wind turbine is firstly developed in this thesis. The model is validated against field measurement data, and the validation gives confidence about the accuracy and applicability of the developed model. DFIG wind farms consist of tens to hundreds of identical DFIG wind turbines increasing the complexity of the wind farm model and simulation time. A novel aggregation technique is developed in this thesis that incorporates a multiplication factor, namely mechanical torque compensation factor (MTCF), to the mechanical torque of the full aggregated wind farm model. The MTCF is initially constructed to approximate a Gaussian function by using fuzzy logic method. By optimizing the MTCF on a trial and error basis, less than 10 percent discrepancy is then achieved between the proposed aggregated model and the complete model. The proposed aggregation technique is then applied to a 120 MVA offshore wind farm comprising of 72 DFIG wind turbines and shows higher accuracy in approximating the wind farm dynamics as it appears at the point of common coupling (PCC) as compared to the full aggregated model. The proposed aggregated model computes faster than the complete wind farm model by 90.3 percent during normal operations and 87 percent during grid disturbances. To overcome the adverse effects due to the fluctuating nature of wind, two wind power smoothing methods are proposed using a fuzzy logic pitch angle controller for a smooth performance with a minimum drop in output power. One method performs partial smoothing with only 4.74 percent drop in the output power while the other method offers complete smoothing with a 8.28 percent drop in output power. The impact of wind energy integration on power system transient stability (PSTS) is studied quantitatively with the transient energy margin (TEM), which is calculated through the evaluation of the transient energy function (TEF). This study is carried out in two ways in the thesis. One is to analyse the impact of transient fault on the DFIG wind turbine as compared to SGs for different factors, like the fault clearing time, the grid coupling, the inertia constant and the voltage sag. The study reveals that transient stability of the DFIG wind turbine is hardly affected by the grid coupling, the inertia constant and the generator terminal voltage sag variations indicating its consistent transient performance within a wide range of these factors. The fault clearing time should be almost 11 percent faster for the system with the DFIG than the synchronous generator (SG). The other is to investigate the impact of the DFIG wind farm on the PSTS with the variation of different factors, which are the voltage sag, the fault clearing time, the load and the wind power penetration level. The study reveals that power systems integrated with DFIG wind farms are sensitive to transient events with high voltage sag, high fault clearing time, low load operation and high wind power penetration level. Machines at different locations individually possess distinct fault response and suffer from a large-scale power imbalance. As a result, reliable operation of DFIG wind farm integrated power systems demands upgraded equipment, such as advanced switchgear, fast breakers/isolators, efficient power reserve systems and advanced reactive power compensating device, etc.

Under the disruption of communication system, the wide area controller may fail to stabilize power oscillations. As a result, the power grids may be jeopardized due to the undamped oscillations. To improve the grid resiliency, a new design method of the two-level robust coordinated stabilizing control of power oscillation damper (POD) of wind turbine with doubly-fed induction generator (DFIG), and power system stabilizer (PSS) is presented in this paper. The two-level control of POD and PSS consists of centralized and local levels. As the main controllers, the centralized POD and PSS are applied to damp out power oscillations. When the communication failure occurs, the local POD and PSS act as the backup controllers to stabilize power oscillations instead of the centralized POD and PSS. The geometric measures of controllability and observability are adopted to determine the suitable input signals of POD and PSS. The structure of POD and PSS is represented by a practical 2nd-order lead/lag compensator. The control parameters of POD and PSS of each control level are separately optimized under various operating conditions so that the damping effect and robustness can be guaranteed. Simulation study is conducted to show the stabilizing effect of the proposed controller on the enhancement of grid resiliency against severe short circuits, line outages, various power flow levels, wind speeds, variable communication latency, and communication failure.

In this study, the problem of simultaneous and coordinated tuning method for thyristor-controlled series capacitor (TCSC) power oscillation damping controllers and conventional power system stabilizer (PSS) controllers in multi-machine power systems is considered. For a multi-machine power system, the tuning of the PSS and TCSC controllers is generally formulated as an objective function with constraints consisting of the damping ratio and damping factor. Using the linearized system model and the parameter-constrained nonlinear optimization algorithm, interactions among TCSC controller and PSS controllers are minimized. It is done by simultaneously optimizing, the parameters of the damping controllers using sequential quadratic programming technique. Simulation results of a two area multi-machine power system validate the effectiveness of the approach and its capacity in tuning multiple controllers in power systems simultaneously.

In this paper, the Authors present the designing of power system stabilizer (PSS) and static var compensator (SVC) based on chaos, particle swarm optimization (PSO) and shuffled frog leaping (SFL) Algorithms has been presented to improve the power system stability. Single machine infinite bus (SMIB) system with SVC located at the terminal of generator has been considered to evaluate the proposed SVC and PSS controllers. The coefficients of PSS and SVC controller have been optimized by Chaos, PSO and SFL algorithms. Fi-nally the system with proposed controllers is simulated for the special disturbance in input power of genera-tor, and then the dynamic responses of generator have been presented. The simulation results show that the system composed with recommended controller has outstanding operation in fast damping of oscillations of power system and describes an application of Chaos, PSO and SFL algorithms to the problem of designing a Lead-Lag controller used in PSS and SVC in power system.

With rapid proliferation of wind generation in current generation mix, the issue of low frequency oscillations (LFOs) may get escalated in the modern power grids. The eigenvalue and dynamic sensitivity analysis have been employed to examine the effect of wind integration on system damping. Further, a wide area based robust damping improvement control is suggested. It involves the coordinated control of power system stabilizers (PSSs) of synchronous generators (SGs) and power oscillation dampers (PODs) of doubly fed induction generators (DFIGs). The robust control is attained by employing a new fitness function based on eigenvalue and damping ratio and optimized by Whale Optimization Algorithm (WOA). The wide area POD inputs are selected using modal observability criterion, obtained using phasor measurement units (PMUs) located optimally in the system. The results are verified on IEEE benchmark 68 bus NY-NE (New York- New England) test system. The simulation results highlights the robustness of proposed control to changing system conditions and shows its effectiveness in augmenting system damping and thus small signal stability with high level of wind penetration.

In order to improve the ability of a power system with doubly-fed induction generator (DFIG) to suppress low-frequency oscillations, this paper put forward a damping control strategy based on model predictive control (MPC). It is raised that stochastic subspace identification (SSI) is used to identity a power system with DFIG. Compared with other control strategies, configuring MPC can achieve the purpose of system optimization, which is to enhance the stability of a power system with DFIG. This paper uses the 4-machine 2-area system to compare results of MPC and traditional power system stabilizer (PSS) control in terms of damping characteristics, stability and applicability.

Providing additional damping for system electromechanical oscillations through doubly fed induction generator (DFIG)‐based wind turbines is investigated in this study. In this regard, first an objective function is developed to tune the DFIG control gains, aim to maximise the wind farm (WF) contribution to system oscillation damping, but it is shown that it causes a decrease in the damping of DFIG stator mode. In other words, with the current DFIG control design, it is not possible to improve both the small signal stability of the power system and the dynamic stability of WF together. Afterwards, two high‐pass filters are suggested to be employed in the control design of DFIG. It is shown that with the modified control design, it is possible to improve the system oscillation without spoiling the dynamic stability of the WF itself. Eigenvalue analysis is performed to validate the effectiveness of the modified control design.

ABSTRACTHigh penetration level of wind power has significant impact on the dynamic performance of power system. Power system with existing high-voltage direct current (HVDC) link may influence the stability of power system at high penetration level of wind power. This article investigates the stability issues of power system with existing HVDC link for different penetration level of doubly fed induction generator (DFIG) and direct drive synchronous generator (DDSG) based wind farms. The small signal stability analysis shows that power system with HVDC link has improved the stability of the power system for increased penetration of DFIG- and DDSG-based wind farms.

Many wind turbine generations have been installed into power systems around the world, where in recent years doubly fed induction generator (DFIG) attracts a lot of attentions because of its efficiency and controllability. However, the DFIG is connected to the power system through inverters and originally does not have an ability to release the kinetic energy of the rotor or resorb the surplus power of the power system as the kinetic energy. Therefore, it has not been made clear how the DFIGs have an influence on small-signal stability in power systems. In this paper, we propose a control scheme of the DFIG and analyse its effect on the small-signal stability of the power system by eigenvalue calculations and time-domain simulations.

The growth rate of penetration of wind energy has addressed many challenges and impacts related to the power quality and power system stability because of its intermittent nature. Once a doubly fed induction generator (DFIG) is connected to a power system, it absorbs lagging reactive power during the grid operation causing instability issues to the grid voltages. In this research paper, a DFIG based wind turbine is being modeled considering the optimal power coefficient and reactive power control strategy. The optimal power coefficient correlates the power law exponent with the respect of velocity and elevation. The reactive power control strategy is modeled using back-to-back converter system. The paper also investigates the voltage improvement of a large distribution network connected with DFIG system. By using steady state analysis, the voltage magnitude profiles are determined during DFIG at point of common coupling. The proposed control shows that DFIG based wind-turbine integration to the large distribution network enhances the weak bus voltage.

The increasing level of wind power integration using doubly fed induction generators (DFIGs) has implications for local frequency support as a consequence of decoupling between DFIG rotor speed and grid frequency. To ensure reliable and stable power system operation with DFIG integration, supplementary inertial control strategies are required. Conventional inertial control algorithms which use the rate of change of frequency (RoCoF) and frequency deviation loops (droop loop) require great effort to determine appropriate gains suitable for all power grid and wind speeds. In this paper, the influence of supplementary inertial control loop parameters on the inertial response and power system frequency are analysed. An active control strategy is proposed for frequency regulation using variable gains in the frequency deviation loop for the inertial controller. The variable gain control approach is shown to actively respond to system changes to improve the performance. The controller is compared with the widely used PID method. The proposed method is shown to enhance the frequency nadir and guarantee steady DFIG operation.

In this paper an Optimization based linear control design method is used to achieve a coordinated design of Power System Stabilizer (PSS) and Thyristor Controlled Series Capacitor (TCSC) for power system damping improvement with pre specified control design requirements. The settling time is considered as main performance criteria in time domain specification and gain and phase margins for frequency domain specifications. The main objective of the coordination of controllers is to improve the global stability through damping of oscillations by improving the damping ratio of the system and minimizing the settling time of the system response. Thus coordination increases the reliability of the system and maintains the required damping even one or more controllers are out of service and hence reduces the need for additional controller. Optimization based linear control design is used to determine the optimal gain and time constant setting of lead-lag controller parameters for PSS and TCSC. The coordinated PSS and TCSC controller is tested in the Single Machine Infinite Bus Power System (SMIB). Simulation is carried out using Matlab2011b. From the time domain simulation results it is observed that oscillations are damped out, settling time is reduced and damping ratio is improved. From bode plot it is inferred that gain and phase margin of the system is further improved to satisfy the system requirements. In the overall analysis, optimization based linear control design implemented for the coordination of PSS and TCSC controller satisfies the practical requirements of the power system oscillation damping problem, also shift the eigen values to the left half of the s-plane as far as possible and hence enhances the overall system stability

The adverse effects resulting from the intermittent nature of wind energy on power generation and stability is well documented in the literature. More specifically, the impact of power oscillations on doubly fed induction generator (DFIG)-based wind turbines can have drastic effects and even lead to large area blackouts, if not addressed properly. This paper deals with the design and implementation of a probabilistic coordinated approach for power systems with synchronous generators (SGs), DFIGs, and facts devices. The parameters of the power system stabilizers (PSSs) of the SG, power oscillation dampers (POD) of the DFIGs and STATCOM controllers were optimally coordinated using a modified Imperialist Competitive Algorithm (MICA) combined with a probabilistic eigenvalue approach. The proposed approach was implemented to a modified 39-bus New England power system. Its effectiveness in guaranteeing power system's dynamic stability was assessed using time domain analysis, eigenvalue mapping, and robustness analysis under various wind conditions. DFIG's realistic modes of operation, including normal, synchronous, and sub-synchronous modes were considered in the performance analysis. The obtained results were further compared to those of deterministic and uncoordinated approaches. A comparison of the MCA algorithm to other optimization approaches such as particle swarm optimization (PSO), genetic algorithm (GA), and imperialist competitive algorithm (ICA) is also carried out. The simulation results and robustness analysis confirmed the superiority of the proposed probabilistic approach over various other approaches.