Robust Power System Stabilizer Research Articles

Robust multi-machine power system stabilizer design using bio-inspired optimization techniques and their comparison

This paper reports a comparative study among four bio-inspired meta-heuristic techniques i.e. Sooty-Tern Optimization (STO), Grey Wolf Optimization (GWO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) to tune the robust Power System Stabilizer (PSS) parameters of the multi-machine power system. These approaches are successfully tested on two bench-mark systems: sixteen-machine, sixty-eight-bus New England Extended Power Grid (NEEPG) and three-machine, nine-bus Western System Coordinating Council (WSCC). The efficacy of planned PSS via STO and GWO is validated by extensive non-linear simulations, eigenvalue analysis, and performance indices for numerous operating conditions under decisive perturbations, and outcomes are matched with those of GA and PSO techniques. In addition, the robustness is also tested for these algorithms. The results indicate that the PSS design using STO and GWO improves the small-signal stability and damping performance for mitigating inter-area and local area modes of low-frequency oscillations compared to GA and PSO.

Robust Optimization of Power System Stabilizer Parameters Based on Pole Placement Technique

To enhance the stability of power system, a power system stabilizer (PSS) is one of the control mechanisms installed in the power plants. A suitable PSS parameters set can help in reducing the power swing. In general, the design of PSS parameters is performed based on a nominal operating condition of the power system. In this paper, a multi‐objective optimization algorithm based on pole placement technique is proposed to find a robust PSS parameters set. The proposed strategy searches for the optimal PSS parameters under multiple operating conditions of the generator. Preliminary simulation results on a single machine infinite bus (SMIB) model show that the proposed PSS parameters design method can further improve the robustness of the overall power systems performance under different types of disturbance. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

A robust crow search algorithm-based power system stabilizer for the SMIB system

A robust crow search algorithm-based power system stabilizer for the SMIB system

Control constraint‐based optimal PID‐PSS design for a widespread operating power system using SAR algorithm

Nowaday's tuning of a power system stabilizer (PSS) over widespread operating conditions to safeguard the power system stability is a challenging task to power engineers. Therefore, there is a need to develop a robust and reliable PSS to produce clean and sustainable energy for power generation. In this research work, a control constraint-based optimal proportional, integral, and derivative (PID)-PSS using nature-inspired search optimization technique called search-and-rescue algorithm (SAR) is developed to suppress the low-frequency oscillations (LFOs) in a power system operating in a wide range of operational states. The wide variations in the system operating conditions are captured by the coefficients of interval polynomial and then simple inequality conditions are attained to assure the power system stability. Furthermore, a multi-objective function (MOF) is formulated to enhance the operation of the proposed PID-PSS for a widespread operating state and also to encounter practical working conditions. A human search-based optimization algorithm, that is, SAR, is implemented to acquire the PID-PSS gains. The design resilience of the proposed PID-PSS is investigated using two test cases of a one-machine infinite-bus (OMIB) power system operating at a widespread and also verified for static and dynamic mechanical disturbances. The simulation results show that the proposed optimal PID-PSS controller outperforms the most prominent controllers in the recent literature.

H-robust technique based ant optimal power system for solar energy power system stabilizer

The prime objective of the proposed work is to create a method for solar power stabilizer under deregulated environment. A robust thermal power system was designed and implemented in the present work. In this an advancement procedure enhanced Artificial Bee Colony (ABC) algorithm was investigated to settle the recurrence and tie-line power motions successfully. The robust solar power system stabilizer (RPSS) was planned to utilize the upgraded ABC for the planning of regulators for dynamical frameworks for electrical designing. The main objectives of this research are to reduce the oscillation and to increase the overall robust performance of the system. The proposed technique adopts the stability margin (ε) as the index of robustness and performance of the controlled system. As an outcome a correlation were made between the conventional force framework stabilizer (CFFS) and PSS with H∞ improvement as an additional source. An improvement was seen in the ABC in contrast with different methods that leads to produce an efficient result and to generate the desired response.

Design of Velocity PID-Fuzzy Power System Stabilizer Using Particle Swarm Optimization

Power system stabilizer (PSS) is used to damping power system local and interarea modes of oscillation. It will act as additional signal through the generator excitation system which produces a component of electrical torque in phase with speed variation. Fuzzy controller is nonlinear. It is more difficult to set the fuzzy controller gains compared to conventional PID controller. This research proposed velocity (PID-FPSS) its gains are tuned off-line by particle swarm optimization techniques (PSO). The objectives are to damp local-area mode of oscillations that occur following power system disturbances. The effectiveness of the proposed technique is illustrated by applying the velocity PID-FPSS to a single-machine infinite bus power system that is typically used in the literature to test the performance of power system stabilizers. The simulation studies has been tested in MATLAB SIMULINK package . A comparison between the proposed PID-FPSS and a well-tuned and designed robust power system stabilizer (RPSS) confirms the superiority of the PID-FPSS.

Design of a robust PID-PSS for an uncertain power system with simplified stability conditions

In a deregulated power system uncertainty exists and lack of sufficient damping can lead to Low Frequency Oscillations (LFO). The problem can be addressed using robust Power System Stabilizers (PSS). In this paper, an optimal procedure to design a robust PID-PSS using interval arithmetic for the Single Machine Infinite Bus (SMIB) power system is proposed. The interval modelling captures the wide variations of operating conditions in bounds of system coefficients. In the proposed design procedure, simple and new closed loop stability conditions for an SMIB interval system are developed and are used to design an optimum PID-PSS for improving the performance of an SMIB system. The optimum PID-PSS is attained by tuning the parameters using the FMINCON tool provided in MATLAB. The robustness of the proposed PID-PSS design is validated and compared to other notable methods in the literature when the system is subjected to different uncertainties. The simulation results and performance error values show the effectiveness of the proposed robust PID-PSS controller.

Robust multi-objective PSSs design via complex Kharitonov's theorem

This paper represents a step toward shooting an optimal robust three-parameter power system stabilizer (PSS) with the common form of (x1+x2s)/(1+x3s). The whole set of stabilizing PSSs is graphically characterized using d-decomposition with which the controller-parameter space is subdivided into root-invariant regions. Design is accomplished using the bench mark model of single machine-infinite bus system (SMIB). Rather than Hurwitz stability, d-decomposition is extended to consider d-stability where D refers to a pre-specified damping cone in the open left half of the complex s-plane to enhance time-domain specifications. Pole clustering in damping cone is inferred by enforcing Hurwitz stability of a complex polynomial accounting for the geometry of such cone. Parametric uncertainties of the model imposed by continuous variation in load patterns is captured by an interval polynomial. As a result, computing the set of all robust d-stabilizing PSSs calls for Hurwitz stability of a complex interval polynomial. The latter is tackled by a complex version of Kharitonov's theorem. A less-conservative and computationally effective approach based on only two extreme plants is concluded from the geometry of the stability region in the controller parameter plane. Simulation results affirm the robust stability and performance with the proposed PSSs over wide range of operating points.

Robust pole-placer power system stabilisers design via complex Kharitonov's theorem

In this paper, the synthesis of robust three-parameter power system stabilisers (PSSs) is presented. Graphical characterisation of the set of stabilising PSSs is carried out using D-decomposition. Dynamic model of single-machine infinite-bus system (SMIB) is considered to accomplish the design. D-decomposition is extended to consider D-stability where D refers to a pre-specified damping cone in the open left half of the complex plane to enhance time-domain specifications. Pole clustering in a damping cone is inferred by enforcing Hurwitz stability of a complex polynomial accounting for the geometry of such cone. Parametric uncertainties of the model are captured by an interval polynomial. Hence, performance enhancement calls for Hurwitz stability of a complex interval polynomial. The latter is tackled by the complex version of Kharitonov's theorem. A less-conservative and computationally effective approach is concluded from the geometry of the stability region. Simulation results affirm robust stability and performance over a wide range of operating points.

Enhancement of Small Signal Stability of SMIB System with Robust Power System Stabilizer

As power system experiences low frequency oscillations due to disturbances, these low frequency oscillations are related to the small signal stability of a power system. The phenomenon of stability of synchronous machine under small perturbations is explored by examining the case of an SMIB system. The analysis of SMIB gives physical insight into the problem of low frequency oscillations. The SMIB system is predominant in local mode low frequency oscillations. These oscillations may sustain and grow to cause system separation if no adequate damping is available. The damping is provided by adding Power System Stabilizer for Synchronous Machine. In addition, as power system is nonlinear in nature, application of robust control techniques is mandatory to face the challenge of dynamic conditions. Hence, this work aims to design robust Power System Stabilizer for Synchronous Machine in order to damp the rotor speed deviations.

Roust Power System Stabilizer Design Using Kharitonov’s Theorem: A Case Study

This paper proposes a robust power system stabilizer(PSS) for a steam synchronous generator in Barka II power station. The PSS should be capable of damping small-disturbance oscillations (inherently existing in power systems due to e.g. load changes, lines switching...etc.) within a certain settling time for different load conditions. Also, the proposed PSS must have the conventional structure and its parameters must not be violated. To achieve this goal, robust control provides many advantages. The suggested controller is tuned by the Kharitonov’s theorem and uses the standard structure employed in industry. The problem is cast into a nonlinear constrained optimization problem to achieve the desired settling time without violating the practical values of the controller parameters. Performance of the robust PSS is evaluated by several simulations in the presence of system uncertainty due to load changes.

Robust design of fuzzy‐based power system stabiliser considering uncertainties of loading conditions and transmission line parameters

Ensuring the efficiency and robustness of a power system stabiliser is indebted to provide a comprehensive scheme that considers significant uncertainties in variables and parameters of the model. This study proposes a robust type-II fuzzy logic-based power system stabiliser scheme that can handle the uncertainties in both loading condition and line parameters. Unlike loading condition, there are many lines in a typical power system and it is necessary to introduce an indicator that can mark lines with significant uncertainty in the parameters. Hence, a criterion based on Oscillatory Stability Index is presented in the study. On the other hand, random samples from line parameters and loading conditions are generated by the roulette-wheel using probability density functions (PDF) to form the elements of the weighting matrix. Two objective functions including weighted eigenvalue deviations and damping ratios are defined and then optimised to find the parameters of the proposed stabiliser in the uncertain environment. Simulations are carried out in different scenarios and in terms of both load condition and line parameters changes. Finally, the performance of the proposed stabiliser is assessed through comparisons with an optimised lead–lag power system stabiliser and a robust lead–lag power system stabiliser.

Design of robust modified power system stabilizer for dynamic stability improvement using Particle Swarm Optimization technique

Abstract This paper presents a novel method for designing robust Power System Stabilizer (PSS) using Particle Swarm Optimization (PSO) technique to improve the dynamic stability of the power system. Modified Heffron-Phillip’s model is developed by considering the generator side transformer voltage as the reference instead of considering the infinite bus voltage as the reference to reduce the complexity and computational time. Using this MHP model, a power system stabilizer called Modified Power System Stabilizer (MPSS) is developed and integrated with P-I-D controller using PSO (PSO-P-I-D-MPSS) on a Single Machine Infinite Bus System. PSO algorithm is used to determine the gain settings of the P-I-D-MPSS. The developed PSO-P-I-D-MPSS is simple to implement and will be a better alternative to the conventional or evolutionary based PSSs. The efficacy of the proposed PSO-P-I-D-MPSS is validated by the application of proposed stabilizer to a benchmark system for several operating conditions under various disturbances. The results clearly show that the proposed stabilizer improves the dynamic stability of the power system under wide range of operating conditions.

Optimal design of probabilistically robust PIλDμ controller to improve small signal stability of PV integrated power system

With the rapidly increasing penetration level of power generated by large scale photovoltaic (PV) units into the power systems, the effect of the variable output power of the PV unit on the stability of the system cannot be ignored. This paper presents a mathematical approach to study the effect of high infiltration of PV power plant on the small signal stability of a power network and design of optimal fractional order PID (PIλDμ) controller for improving the probabilistic small signal stability of the power systems, taking into consideration the uncertainty of system operating conditions. Due to the probabilistic characteristics of large scale PV power generation, deterministic analysis approaches are not able to fully reveal the impact of high-level PV penetration. At first, this work introduces the main module and mathematical modeling of the large scale PV generation jointly with the single-machine infinite-bus power system. In the following, the paper proposes an efficient method that tunes power system stabilizer (PSS) to have the robustness for damping electro-mechanical oscillations in power systems with incorporated random PV power. For this reason, a robust PSS based on hybridization of PIλDμ controller and Non-dominated Sorting Genetic Algorithm (NSGAII) is designed. This paper targets at finding the optimal gain scheduling of the PIλDμ through the use of the advanced heuristic optimization technique with two objective functions in PV-grid connected systems. The performance of the proposed NSGAII-based PIλDμ controller (NSGAII- PIλDμ) under different solar irradiation, temperature conditions and disturbances is tested. Simulation results illustrate that the model presented can be used in designing of essential controllers for large scale PV power plant.

Robust PI, gain scheduled and PSS controller design using LMI regions: Comparative studies

Abstract This paper considers development of a new design procedure for PI and Gain scheduled robust controller with PSS for turbogenerator using LMI regional regions. The obtained PI+PSS and GSC+PSS robust controllers with output and state derivative feedback for uncertain polytopic turbogenerator model ensure that all closed -loop eigenvalues lay in the prescribed LMI region. The proposed method is to guarantee the less conservativeness with respect to previous methods due to introducing a design procedure based on new auxiliary matrices. The effectiveness of this procedure is illustrated by the examples of two controllers for turbogenerator.

Parameter Optimization of PSS Using a Novel Simplex-Simulated Annealing Approach

A new simplex-simulated annealing (SSA) approach for optimal design of Power System Stabilizer (PSS) parameters in multi-machine power systems is proposed. This approach formulates the PSS design as a nonlinear programming problem using an eigenvalue-based objective function. For purposes of robust PSS design, several representative operating conditions are applied in construction of the objective function. One of advantages of the SSA approach is that, due to incorporation of the downhill simplex method into the Simulated Annealing (SA) method, it can significantly reduce the heavy computation burden of the SA method. Case studies on the 10-generator 39-bus New England test power system show that the effectiveness and efficiency of PSS optimal design have been tremendously improved by using the SSA approach.

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.

A robust power system stabilizer for enhancement of stability in power system using adaptive fuzzy sliding mode control

This paper presents design of power system stabilizer (PSS) based on conventional fuzzy-PID and type-1 fuzzy controller for stability improvements in single as well as multimachine power system connected to infinite bus under different loading conditions. Again, fuzzy and integral sliding mode controllers (FSMC and I-SMC) are being incorporated with PSS into the power system to improve the stability performance. But, the presence of chattering in this controller may lead to low frequency oscillations of smaller magnitudes that can sustain to disturb the power transfer capability and the stability of the system. Therefore, to enhance the performance and efficiency of the power system, a novel adaptive fuzzy sliding mode controller with a robust sliding surface is designed to overcome the possible chattering due to system uncertainties and dynamics. In the proposed adaptive fuzzy sliding mode controller (AFSMC), the stability is ensured through Lyapunov analysis and synthesis test. In addition to the graphical simulation analysis, a quantitative stability approach and real-time test using OPAL-RT OP5600 is also carried out in order to augment the stability study. Further, stability test using eigen modes, root locus and Bode plots are presented to assess the stability performance of the proposed controller. Both the qualitative and quantitative analysis ensures better and robust performance of proposed controllers in comparison to the conventional fuzzy-PID and type-1 fuzzy controller.

Cuckoo Search Optimization Algorithm for Designing of a Multimachine Power System Stabilizer

In this paper, new metaheuristic technique cuckoo search optimization (CSO) is explored for an optimal and robust power system stabilizer (PSS) designing for multimachine power systems and performance is evaluated by comparing with well-established techniques, i.e., genetic algorithm (GA), particle swarm optimization (PSO), and new harmony search optimization (HSO). An eigenvalue-based multiobjective function is implemented for simultaneous control of damping factor and damping ratio to damp out low-frequency local and interarea modes of oscillations. The PSS parameters are so intended that unstable and/or lightly damped mode eigenvalues are shifted to a specified D-shape zone in the left half of the s-plane. The selected metaheuristic techniques GA, PSO, HSO, and CSO are used to obtain PSS parameters for 10-machines, 39-bus New England Power System and the controllers designed are named as GAPSS, PSOPSS, HSOPSS, and CSOPSS, respectively. The performance of all designed PSSs controllers is evaluated by eigenvalues analysis, nonlinear simulations, and performance indices for various operating conditions under different scenarios of severe disturbances and their comparative analysis is observed. The robustness of all designed PSSs controllers is observed by testing them on unseen operating conditions and results are compared for the same. The performance of CSOPSS is found to be better than other controllers designed.

Fractional‐order lead‐lag compensator‐based multi‐band power system stabiliser design using a hybrid dynamic GA‐PSO algorithm

Power system stabilisers (PSSs) are supplementary controllers connected to the excitation system of synchronous generators to damp electromechanical oscillations. Multi-band PSSs are reported as advanced PSSs with the ability to damp out all oscillation modes present in the power systems. This study presents the design of a robust fractional-order multi-band power system stabiliser (Fo-MBPSS) using a meta-heuristic hybrid algorithm for dynamic stability improvement of multi-machine power systems. The large bandwidth, memory effect and flat phase contribution in the frequency response of fractional-order controllers are exploited to make the Fo-MBPSS perform well against a wide range of system uncertainties. The parameter tuning problem of Fo-MBPSS is transformed to an optimisation problem that is solved using a hybrid algorithm by combining a dynamic genetic algorithm (DGA) with a standard particle swarm optimisation (PSO) algorithm. The performance of the proposed DGA-PSO-Fo-MBPSS is evaluated through eigenvalue analysis, non-linear time-domain simulations and some performance indices, in two different multi-machine systems under different loading conditions and disturbances. The results are compared with PSO-based conventional MBPSS and PSO based Fo-MBPSS (PSO-Fo-MBPSS) to establish the fractional parameter effect on the improvement of the system dynamic response and the relevance of the proposed hybrid optimisation technique in achieving robustness.