Conventional Power System Stabilizer Research Articles

Virtual Inertia Based Fuzzy Logic Controller for Improving Power System Stability

Electrical power system is one among the biggest and complex systems in the world. This system may always undergoes different types of disturbances that may cause to the loss of synchronism the system. To prevent this, Power system stabilizers (PSS) are being used in order to damp these oscillations and hence to maintain stability of the system. Leadlag compensation methods are used in the conventional type power system stabilizer (CPSS), where it have a fixed gain settings for particular operating condition. To cover the operating conditions of large range under different variables, fuzzy logic controllers are find to be the better one. In renewable energy sources (RES) the system inertia will be decreased due to the presence of power electronic inverters used to connect to the grid. This reduction in inertia will be improved by virtual inertia based control strategy. The design of virtual inertia based fuzzy controller power system stabilizer is been described in this paper. The main control objective of the intended work is to improve the stability and to increase the system dynamic response. The execution of the proposed controller shows enhanced results when analysed with the conventional type PSS. This work is done in SIMULINK atmosphere and the performance of the systems are investigated.

Simulation And Analysis of An Intelligent Power System Stabilizer Using Fuzzy Logic

The basic aim of the power system stabilizer is to damp the fluctuations that occur on the rotating axis of the synchronous generator that result from noise or disturbance on the power system. This is achieved by producing an appropriate damping torque for these fluctuations across the excitation circuit of the generator and for a wide range of operation conditions. The study describes the types of power system stabilizers and giving an mathematical model of the power system that consists of a synchronous machine connected to the infinite bus though transmission lines. This has been achieved by simulating the electric and mechanical equations of power systems and proposing a methodological approach to design a Fuzzy Logic Power System Stabilize (FPSS) relaying in the design on the (Matlab/Fuzzy logic toolbox).Speed deviation (Δω) and acceleration (∆ ) of the synchronous machine are chosen as the input signals to the fuzzy controller in order to achieve a good dynamic performance .The complete range for the variation of each of the two controller inputs is represented by a 7×7 decision table, i.e. 49 rules using proportional derivative like fuzzy logic. The power system (SMIB) was tested with the presence and absence of the excitation system, then (CPSS) was added, and then (FPSS).The simulation results of the proposed fuzzy logic on )SMIB( gave a better dynamic response, decreased the settling time and good performance of the stabilizer in damping the fluctuations that arise in the speed of rotation of the generator and its active power in various operating conditions when proposed (FPSS) is compared with conventional PSS. The simulation results proved the superior performance of the proposed (FPSS).

Damping Oscillation Techniques for Wind Farm DFIG Integrated into Inter-Connected Power System

According to the new international grid codes, ancillary services from renewable energy sources are essential, especially when these sources are harnessed as distributed generators. Power oscillation damping (POD) is a supplemented feature needed from wind power plants. This paper investigates different control techniques that can support wind farms based on a doubly fed induction generator (DFIG) with the proper POD. A damping control loop (DCL) is inserted into the control circuit of the back-to-back converter of DFIG to enhance system oscillation damping. The main function of DCL is similar to that of the conventional power system stabilizer. However, under congestion situations, external regulation devices such as STATCOM are required to support system performance and maintain wind farms tracking grid code requirements. A 2-area 4-machine system which consists of three thermal power plants and one wind power plant is examined. The dynamic performance of the system is investigated using power system stabilizer (PSS) as an embedded feature with the control circuit of the thermal power plants. A comparison between the PSS and STATCOM based on system dynamic performance is performed using MATLAB/Simulink. Additionally, the particle swarm optimization technique is used to enhance the performance of the proposed control techniques, taking the voltage stability margins into consideration.

A Novel Nature-Inspired Improved Grasshopper Optimization-Tuned Dual-Input Controller for Enhancing Stability of Interconnected Systems

Power system often experiences the problem of low-frequency electromechanical oscillations which leads the system to unstable condition. The problem can be corrected by implementing power system stabilizers (PSSs) in the excitation control system of alternator. This paper provides a novel and efficient approach to design an Improved Grasshopper Optimization Algorithm (IGOA)-based dual-input controller to damp the inter-area-mode power system oscillations. A three-fold optimization criterion has been formulated to calculate the optimum values of the controllers required for power system stability. The damping performance of the proposed controller is compared with conventional PSS and genetic algorithm-based controllers to validate the better performance of the proposed IGOA-based controller under various system loading conditions and disturbances.

Application of Neuro-Fuzzy Controller to Replace SMIB and Interconnected Multi-Machine Power System Stabilizers

In this research, an effective application and performance assessment of the Neuro-Fuzzy Controller (NFC) damping controller is designed to replace a single machine infinite bus (SMIB) power system stabilizer (PSS), and coordinated multi PSSs in large interconnected power systems are presented. The limitation of the conventional PSSs on SMIB and interconnected multi-machine test power systems are exposed and disclosed by the proposed NFC stabilizer. The NFC is a nonlinear robust controller which does not require a mathematical model of the test power system to be controlled, unlike the conventional PSSs’ damping controller. The Proposed NFC is designed to improve the stability of SMIB, an interconnected IEEE 3-machine, 9-bus power system, and an interconnected two-area 10-machine system of 39-bus New England IEEE test power system under multiple operating conditions. The proposed NFC damping controller performance is compared with the conventional PSS damping controller to confirm the capability of the proposed stabilizer and realize an improved system stability enhancement. The conventional PSSs’ design problem is transformed into an optimization problem where an eigenvalue-based objective function is developed and applied to design the SMIB-PSS and the interconnected multi-machine PSSs. The time-domain phasor simulation was done in the SIMULINK domain, and the simulation results show that the transient responses of the system rise time, settling time, peak time, and peak magnitude were all impressively improved by an acceptable amount for all the test system with the proposed NFC stabilizer. Thus, the NFC was able to effectively control the LFOs and produce an enhanced performance compared to the conventional PSS damping controller. Similarly, the result validates the effectiveness of the proposed NFC damping controller for LFO control, which demonstrates more robustness and efficiency than the classical PSS damping controller. Therefore, the application and performance of the NFC has appeared as a promising method and can be considered as a remarkable method for the optimal design damping stabilizer for small and large power systems.

Controller parameter tuning of a single machine infinite bus system with static synchronous compensator using antlion optimization algorithm for the power system stability improvement

AbstractThe improvement of power system stability by damping oscillations in the system states is presented in this paper. An antlion optimization (ALO) algorithm is adopted to tune the damping device controller parameters. The ALO algorithm performance is investigated on the benchmark functions, and the same has been compared with the traditional particle swarm optimization (PSO) technique. The statistical analysis on the fitness achieved with the considered algorithms has been demonstrated using best, worst, mean, and SD values on the benchmark functions over 30 individual runs. Here power system stabilizer (PSS) and static synchronous compensator are considered as oscillation damping devices in the test power network. The analysis has been carried out in a sample power system network, and the proposed technique is compared with the conventional PSS and PSO. The results obtained from the designed test system recommends the superior performance characteristics of ALO in applying to the practical power system.

Extreme learning machine for real-time damping of LFO in power system networks

This article proposes a real-time power system stabilizers (PSS) parameter optimization technique employing extreme learning machine (ELM) to enhance overall system stability by damping out the low-frequency oscillations. It models two electric networks, i.e., single machine infinite bus systems where the first network's synchronous machine is equipped with a PSS only, and the second network's synchronous machine is equipped with a unified power flow controller coordinated PSS. It uses diverse loading conditions to investigate the performance of the proposed ELM model-tuned PSS technique and compares it with conventional PSS and the referenced works in terms of the eigenvalues and minimum damping ratios. Additionally, the satisfactory values of the well-known statistical performance indices including the root mean squared error (RMSE), mean absolute percentage error, RMSE-observations-to-standard deviation ratio, coefficient of determination (R2), Willmott’s index of agreement, and Nash–Sutcliffe model efficiency coefficient provide confidence in the developed technique in predicting PSS parameters. Besides, comparisons of results from time-domain simulation demonstrate the ELM model tuned system's superiority over the conventional approach for both test cases. Furthermore, the ELM models require less than a cycle to predict PSS parameters for any loading condition that endorses the developed technique's real-time application.

Analysis of the Effects of PSS and Renewable Integration to an Inter-Area Power Network to Improve Small Signal Stability

Power system often suffers from low frequency oscillations (LFOs) which might result in instability in the long run, if allowed to sustain in the system for a long time. In order to mitigate these oscillations, power system stabilizers (PSS) are used through excitation control. Three recently developed meta-heuristic algorithms namely: Collective Decision Optimization (CDO), Grasshopper Optimization Algorithm (GOA) and Salp Swarm Algorithm (SSA) have been applied for the optimal tuning of PSS parameters for small signal stability analysis of a renewable integrated power network. This was done by designing a conventional speed-based lead-lag PSS in a multi-machine interconnected power system, whose parameters have been tuned using CDO, GOA and SSA in a way to shift all the eigenvalues associated to electromechanical modes to the left half of S plane. Comparison of the results obtained by the algorithms demonstrates the superiority of SSA over GOA and CDO to boost the overall system stability over a wide range of operating conditions. The PSS controller designed using SSA is observed to be more robust and efficient in damping out oscillations under different operating conditions.

Deep Reinforcement Learning-Based Approach for Proportional Resonance Power System Stabilizer to Prevent Ultra-Low-Frequency Oscillations

Recent studies have shown that due to the hammer effect of the governor, hydropower units are easily creating negative damping torque at the common mode frequency (below 0.1 Hz). Therefore, there is a risk of ultra low frequency oscillations (ULFO) in hydropower-dominated systems. ULFO is a small-signal frequency oscillation problem, which is quite different from low frequency oscillations (LFO). A conventional power system stabilizer (CPSS) has less effect on suppressing ULFO. To solve this problem, this paper proposes a high-order polynomial structure to replace the CPSS, and combine it with a proportional resonance controller to form a novel PR-PSS. In order to ensure the robustness of PR-PSS, based on the characteristic analysis results of the PR-PSS, a deep reinforcement learning (DRL) algorithm asynchronous advantage actor-critic (A3C) is introduced to train an agent. After training, the proposed agent can provide optimal parameter settings for PR-PSS under various operating conditions. Simulation results verify the effectiveness of the proposed method.

Excitation control method based on wide-area measurement system for improvement of transient stability in power systems

In this paper, we propose a novel excitation control method for synchronous generators (SGs) for improvement of transient stability in power systems. The proposed excitation system controls the excitation voltage based on a wide-area measurement system (WAMS). An energy function for the power system was adopted as a stability index, and we designed a control system to promote a decrease in the energy function after a disturbance. Numerical simulations were carried out for a multi-machine power system. The results show that the proposed WAMS-based stabilizer (WBS) improves the first swing stability and enhances the damping of the subsequent oscillation, whereas the conventional power system stabilizer (PSS) does not necessarily improve the first swing stability. It is also noteworthy that the WBS has few parameters that need to be tuned, unlike the PSS.

A nonlinear coordinated approach to enhance the transient stability of wind energy-based power systems

This paper proposes a novel framework that enables the simultaneous coordination of the controllers of doubly fed induction generators &#x0028 DFIGs &#x0029 and synchronous generators &#x0028 SGs &#x0029 . The proposed coordination approach is based on the zero dynamics method aims at enhancing the transient stability of multi-machine power systems under a wide range of operating conditions. The proposed approach was implemented to the IEEE 39-bus power systems. Transient stability margin measured in terms of critical clearing time along with eigenvalue analysis and time domain simulations were considered in the performance assessment. The obtained results were also compared to those achieved using a conventional power system stabilizer &#x002F power oscillation &#x0028 PSS &#x002F POD &#x0029 technique and the interconnection and damping assignment passivity-based controller &#x0028 IDA-PBC &#x0029 . The performance analysis confirmed the ability of the proposed approach to enhance damping and improve system &#x02BC s transient stability margin under a wide range of operating conditions.

Adaptive Tuning of Power System Stabilizer Using a Damping Control Strategy Considering Stochastic Time Delay

The operation of a modern electrical system presents complex operating conditions, and uncertainty factors increased by the presence of variable and flexible loads. This stochastic operating point variation can promote low-frequency oscillations, and like the conventional power system stabilizer (PSS) features static tuning, it does not provide sufficient damping. Today, an electrical system is monitored through online measurements from the wide-area measurement system (WAMS); moreover, it enables stochastic dynamics to be tracked as the remote signals of WAMS system, the time delay due to the communication channel. It is interesting to analyze the incorporation of the PSS of signals from the WAMS without the time delay effect that degrades the small-signal stability (SSS) and, in turn, allows adaptive tuning. Through two stages, at first, the subspace of the operating point is determined based on a distribution of consumption levels. Each operating point considered a random time delay. For each subspace, establish a bank of tuned PSSs. Second, through the optimal classification and the regression decision tree (CART), the classification rules for the subspace are determined, allowing classifying the measurements of WAMS. The proposed methodology is applied to the New England of 66-bus system and Ecuadorian electric system to demonstrate that the adaptive tuning of PSSs significantly improves SSS under different scenarios and is probabilistic robust, considering the time delay.

Grid-Forming Power Converters Tuned Through Artificial Intelligence to Damp Subsynchronous Interactions in Electrical Grids

The integration of non-synchronous generation units and energy storage through power electronics is introducing new challenges in power system dynamics. Specifically, the rotor angle stability has been identified as one of the major obstacle with regards to power electronics dominated power systems. To date, conventional power system stabilizer (PSS) devices are used for damping electromechanical oscillations, which are only tuned sporadically leading to significant deterioration in performance against the ever-changing operating conditions. In this paper, an intelligent power oscillation damper (iPOD) is proposed for grid-forming converters to attenuate electromechanical inter-area power oscillation. In particular, the iPOD is applied to a synchronous power controller (SPC) based grid-forming power converter to increases gain of the active power control loop at the oscillatory frequency. Predictions regarding the mode frequency, corresponding to the current operating points, are given by an artificial intelligence ensemble model called Random Forests. The performance of the proposed controller is verified using the two area system considering symmetrical fault for random operating points. In addition, a comparison with PSS installed in each generator reveals the individual contribution with respect to the inter-area mode damping.

An intelligence technique-based control model for power system stabiliser

In the power system, voltage instability is one of the important issues and it may cause voltage sag, voltage swell, change in load and generation of harmonics. To tackle all these problems, the transmission power system makes use of an intelligent control model to improve the stability of power system. In this paper, a new adaptive neuro fuzzy inference system (ANFIS) based power system stabiliser (PSS) for the enhancement of voltage stability in power systems is proposed. A hybrid learning algorithm, which combines the least squares method and the back propagation algorithm, is used to train the ANFIS. The performance of the power system by using fuzzy based PSS is about 60.1% when compared to that of the conventional PSS. To evaluate the effectiveness of the proposed technique the performance of the proposed technique was compared with the results obtained by using fuzzy PSS model and its performance was analysed. Simulation results described in the paper demonstrate that the adaptive neuro-fuzzy based PSS can give 33.43% of improvement in voltage stability when compared to that of fuzzy based PSS over a wide range of operating conditions.

BAT ALGORITHM IMPLEMENTATION TO OPTIMALLY DESIGN THE STABILIZER POWER SYSTEM ON THE SUPPA GENERATOR

One of the control devices that can be used to strengthen the performance of PLTU Suppa is the installation of Power System Stabilizer. The problem of using Power System Stabilizer (PSS) in generator excitation is how to determine the optimal PSS parameter. To overcome these problems, the authors use a method of intelligent bats to design PSS. Bat's algorithm will work based on the specified destination function, which is an Integral Time Absolute Error (ITAE). In this research, we will see the deviation response of velocity and the rotor angle of the suppa generator in case of interference. The results of the analysis show that the uncontrolled system produces oscillation overshoot speed of -0.02437 pu to 0.006517 pu, conventional PSS about -0.02186 pu to 0.004623 pu and with PSS Bat overshoot of -0.01507 pu up to 0.0006223 pu. A loop for rotor angle response shows good results with reduced oscillation and rapidly leading to steady-state conditions. From the analysis results can be concluded, the performance of suppa generator is increased with the installation of Power System Stabilizer with optimal PSS parameters, with parameters respectively Kpss = 32.2077, T1 = 0.0173, T2 = 0.0401, T3 = 0.9174, T4 = 1.2575.

Sssc Based Time Delay Compensator Design for Interconnected Power System

In this paper, researcher designed a delay-dependent wide-area damping controller based on Static Synchronous Series Compensator (SSSC) to enhance the power system stability by using remote signal obtained from Wide-Area Measurement System (WAMS). This remote signals introduces a time delay in the feedback signal, as a result, degrade the system damping performance and even causes instability of close loop power system. To find out various controller parameters, use of Genetic Algorithm (GA) is adopted. The performance of Multi-Machines system is evaluated with proposed controller including signal delay and Conventional PSS(CPSS) in MATLAB simulation. Various results show that SSSC based controller damp-out the inter-area oscillations under small disturbance more effectively as compare to LPSS.

Intelligent Power System Stabilizers using Fuzzy Logic Technique and Sliding Mode Control Strategy

Each electric power grid should be equipped with a power system stabilizer (PSS) to ensure the network stability during operation and distribution. The major function of a PSS is to provide an appropriate control signal to the synchronous generator system, making its rotational speed stabilization against disturbances. This paper investigates three control strategies to design such an efficient PSS for the power network, including a PID-based PSS, a fuzzy logic – based PSS (FLC), a fuzzy logic-integrated sliding mode control – based PSS (SMC). With the rapid development of fuzzy logic technique considered to be an intelligent and successful control tool, the PSS controllers applying this control strategy are able to obtain good control performances, satisfying high requirements of the smart grids. Through a number of numerical simulations implemented in MATLAB/Simulink package for a single synchronous generator connected to an infinite bus, this work verifies the feasibility and success of the studied control strategies in designing an efficient PSS controller. Two case studies with load change and without load change will also be carried out in this paper to demonstrate the broad stability range of the proposed PSS controllers. Simulation results reveal that the FLC and the SMC are much better than the conventional PID-based PSS controllers and these two intelligent regulators can be selected for successfully solving the stabilization problem of an electric power grid in practice.

Fixed order non-smooth robust H∞ wide area damping controller considering load uncertainties

This paper presents the design of a fixed order non-smooth robust H∞ wide area damping controller for the multi machine power system considering load uncertainties. Dynamic response of loads has a significant effect on system stability and directly determines the stability margin of the operating point. The effect of load uncertainties is considered by different percentage and size of induction motors as dynamic load which was considered by unstructured uncertainty. The proposed method is based on shaping of the open loop transfer function in the frequency domain. This proposed method is robust with respect to multi-model and load type (dynamic, static) and parametric time-delay uncertainties. Non-smooth optimization techniques are developed to H∞ synthesis problem under additional structural constraints on the controller. This approach avoids using Lyapunov variables and therefore leads to moderate size optimization programs even for very large systems.The performance of the controller has been tested on two-area four-machine test system model and New England 39 bus system under various operating scenarios and faults. The effectiveness of the developed robust centralized wide area controller, designed based on H∞ fixed order loop shaping synthesis, is compared with a conventional power system stabilizer.

Wide area inter‐area oscillation control system in a GB electric power system

A wide area control system (WACS) for the Great Britain (GB) power system is presented. This WACS is designed to enhance the GB system's small signal stability, i.e. improve the damping of the inter-area oscillatory mode between Scotland and England. This study mainly consists of two parts. In the first part, the conventional concept of high-voltage direct current (HVDC) and supplementary damping control modelling is presented. The model of HVDC and supplementary damping control are tested through the classic two-area model. In the second part, the operation of the proposed WACS is demonstrated using a full model of the GB power system. In addition to the demonstration of the major applications, some key factors that will influence the operation of the wide area inter-area oscillation damping control scheme will be tested and discussed. These factors include the time delay involved in wide area data transmission and the reactions between the additional HVDC damping controller and conventional power system stabilisers.

Robust Power System Stabilizer based on Static Output Feedback Approach to Enhance Power System Stability

This contribution shows how power system stabilizer adds supplementary signal along with the regular excitation signals to improve the stability of the power system. In literature, PSS has been designed using almost every technique available in control theory i.e from conventional to robust to intelligent control methods. Conventional PSS based on Lead-Lag compensation network is not that much reliable for different loading conditions, as it gives poor performance when the loading condition changes. On the other hand, robust control designs take care of varied operating conditions using the concept of uncertainty. It is well known that the static output feedback problem if feasible can be solved using a pair of coupled linear matrix inequalities. Also, it is shown in literature that the static output feedback problem can be used for direct lower order control design. Researchers have applied the SOF control techniques for direct design of PID controllers, if one exists. This paper involves extensive study and comparison of design techniques for PSS, implements various existing control methodologies for PSS design.