Impact Analysis and Robust Coordinated Control of Low Frequency Oscillations in Wind Integrated Power System

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.

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.

In the face of challenges posed by increasing wind power integration, penetrations, SG replacement with Wind Farm (WF), and significant disturbances and their impact on small signal and transient stability. This paper presents a novel solution employing coordinated control of Power System Stabilisers (PSS) and Power Oscillation Dampers (POD). The stochastic nature of wind power and nonlinear wind speed behaviour creates complexities and is exacerbated by severe disturbances. Traditional PSS and POD designs struggle with these non-linearities. An intelligent coordinated control strategy based on a Fuzzy Logic Controller (FLC) is proposed to address this issue. The FLC synchronises and coordinates PSS and POD, enhancing stability by dampening Low-Frequency Oscillations (LFOs) and mitigating undamped fluctuations even under extreme conditions. Sensitivity analysis identifies key LFOs affecting stability, enabling optimal control gain selection. RT-LAB experimental platform on the IEEE-9 bus system validates the approach, showcasing superior performance compared to individual methods. The results underscore the robustness and reliability of FLC coordination, ensuring enhanced system stability in practical applications.

The stochastic nature of wind speed and nonlinear wind power behavior complicates stability, particularly under severe disturbances, where traditional controller designs are insufficient and lead to transient stability. This paper proposes a Power System Stabilizers (PSS), Power Oscillation Dampers (POD), and Thyristor Controlled Series Capacitors (TCSC) control strategy to enhance stability. Further, this study analyzed the intermittent nature of wind speed and the replacement of Synchronous Generators (SG) with Wind Farm (WF). The results show that the system is unstable and stable weekly without and with the control of PSS, POD, and TCSC. A coordinated controller of TCSC with POD is proposed to enhance the stability effectively and mitigate undamped fluctuations even under extreme conditions. The proposed coordinated controller demonstrates superior performance, robustness and reliability compared to standalone controllers. It has been validated and shown to be effective using the IEEE-11 bus model on the MATLAB/SIMULINK platform across diverse scenarios. This research presents a cohesive framework for addressing stability issues in WF-integrated power systems by streamlining methodologies and results.

In this paper, heuristic dynamic programming (HDP) based supplementary control is compared with the power system stabilizer (PSS) based supplementary control for doubly-fed induction generators (DFIG), namely, the active power damping control. The traditional design of PSS control on DFIG damping is based on eigenvalue analysis. For such analysis, disturbances are considered sufficiently small to permit the nonlinear model representing the power system to be linearized and expressed in state space form. When the disturbance or the system configuration changes, this kind of design is easy to become entrapped in local minimal and the robust ability of the controller is not guaranteed. On the other side, the HDP based supplementary damping controller analyzed in this paper is “model-free” with on-line learning capability: once a system state is observed, an action will be subsequently produced based on the performance index function. The obtained results by such a HDP supplementary controller on a benchmark power system are compared with the traditional PSS controller, demonstrating the improved control performance and robustness.

Synchrophasor has evolved as an effective tool for detection of low frequency oscillation (LFO) inherent to a power system. This paper presents case studies to illustrate utilization of Synchrophasors for post-mortem analysis of oscillations to identify the root cause and evaluate the effectiveness of the remedial measures like Power System Stabilizer (PSS) and System Protection Schemes (SPS) for improving damping in the system. Authors suggest installation of Phasor Measurement Unit (PMU) at suitable locations for performance evaluation of other controllers installed in the system for power oscillation damping (POD).

Due to power system oscillations induced by complex interconnections, power system stability has been a major concern and will continue to be a major concern in power system operations. For improving power system stability, efforts have been directed toward damping power system oscillations. The small signal stability is the instability that has been influenced by complex interconnections. Small signal stability can be dampened with power system stabilisers (PSS). PSS, on the other hand, have certain disadvantages, such as significant variations in voltage profiles and the potential for leading power factor operations, which may reduce system stability in the face of severe disturbances. In wide multi machine power systems, using only traditional PSS can not be enough to dampen inter-area oscillations and the effect of voltage profile variation. Power electronic devices known as Flexible Alternating Current Transmission System (FACTS) devices, on the other hand, are good at damping inter-area oscillations and can handle voltage variations. As a result, based on computational intelligence techniques, this paper provides a thorough analysis and evaluation of PSS and FACTS power oscillation damping (POD) controllers in reducing low frequency oscillations. The importance of technical paper publications on PSS and FACTS-based controller design, optimum location, and parameter tuning is highlighted. Finally, the potential future research directions for novel PSS and FACTS devices is proposed as a reference for interested researchers.

Enhancing stability via coordinated control of generators, wind farms, and energy storage: Optimizing system parameters

Real time monitoring and control of low frequency oscillations is an important issue to be taken into consideration in modern interconnected power systems operation. A method to find the system small signal stability and coherent generators following a disturbance in real-time is proposed in this work The synchronously sampled data available from Phasor Measurement Units (PMUs) at a high sampling rate provides an opportunity to observe the system operation near to real-time. The first four cycles of post disturbance data comprising of bus voltage magnitudes and angles is measured from optimally placed PMUs. This data is fed to different Artificial Neural Networks to determine the damping index and coherent groups. The dimensionality reduction is performed using Principal Component Analysis. The suggested method is very fast and accurate in predicting the system damping and coherent groups in real-time for different operating conditions including topological variations and 3-phase faults. The efficiency of the proposed methodology is investigated on IEEE 39-bus test system.

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.

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.

This paper reports a new technique for achieving optimized design for power system stabilizers. In any large scale interconnected systems, disturbances of small magnitudes are very common and low frequency oscillations pose a major problem. Hence small signal stability analysis is very important for analyzing system stability and performance. Power System Stabilizers (PSS) are used in these large interconnected systems for damping out low-frequency oscillations by providing auxiliary control signals to the generator excitation input. In this paper, collective decision optimization (CDO) algorithm, a meta-heuristic approach based on the decision making approach of human beings, has been applied for the optimal design of PSS. PSS parameters are tuned for the objective function, involving eigenvalues and damping ratios of the lightly damped electromechanical modes over a wide range of operating conditions. Also, optimal locations for PSS placement have been derived. Comparative study of the results obtained using CDO with those of grey wolf optimizer (GWO), differential Evolution (DE), Whale Optimization Algorithm (WOA) and crow search algorithm (CSA) methods, established the robustness of the algorithm in designing PSS under different operating conditions.

The aim of this research work is to analyse sub-synchronous control interaction (SSCI) in doubly-fed induction generators (DFIGs) and to design a supplementary control technique for the mitigation of SSCI. A mathematical model of the DFIG is derived and linearized in order to perform an eigenvalue analysis. This analysis pinpoints the parameters of the system which are sensitive in making sub-synchronous modes unstable and hence are responsible for causing SSCI. A power oscillation damper (POD) is designed using a residue method to make the DFIG system immune to the SSCI. The POD control signal acts as a supplementary control, which is fed to the controller of the grid-side converter (GSC). The POD signal is applied to different summation junctions of the GSC controller in order to determine the best placement of the POD for effective mitigation of SSCI and for the increased damping of the system.

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.

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.