Optimal Power System Stabilizer Research Articles

Online tuning of power system stabilizer employing genetic programming for stability enhancement

This paper aims to design optimal power system stabilizer (PSS) employing genetic programming (GP) to enhance system stability through damping the low-frequency oscillations out. GP is used to develop model equations for PSS parameters where the inputs are generator terminal voltage, active and reactive powers. The dynamic performance of the proposed technique is validated through the values of statistical performance measures. The mean squared error (MSE) and mean absolute percentage error (MAPE) are quite low whereas the coefficient of determination (R2) is reasonably high for the developed model. In addition, the eigenvalue and minimum damping ratio analysis, as well as time domain simulation, were carried out, which also demonstrate the efficacy of the proposed model.

Coordinated Supplementary Damping Control of DFIG and PSS to Suppress Inter-Area Oscillations With Optimally Controlled Plant Dynamics

This paper proposes a design method to coordinate dual-channel supplementary damping controllers (SDCs) of doubly-fed induction generators (DFIGs) and power system stabilizers (PSSs) for suppression of inter-area power oscillations. A dynamic performance index is introduced to measure the dynamics of the conventional synchronous generator and DFIG during the damping control process. Hence, the proposed method designing the PSS and SDC is formulated as an optimization problem with the objective function being the sum of weighted performance indexes and the constraints indicating the requirements on the damping of the inter-area modes. Solving the optimization problem can obtain the optimal SDC and PSS, which can meet the required damping results as well as optimize dynamics of the controlled plants. Moreover, by adjusting weights in the objective function, the damping control burden can be flexibly and feasibly allocated between active and reactive power channels of DFIGs or among the damping controllers. Simulations with the modified New England and New York interconnected system prove that the proposed optimization based tuning method can not only robustly coordinate the PSS and SDC to effectively damp inter-area oscillations but also improve the dynamics of controlled plants during the damping control process over different operating conditions.

Design of Simulation Product for Stability of Electric Power System Using Power System Stabilizer and Optimal Control

This paper will discuss the use of optimal control and Power System Stabilizer (PSS) in improving the oscillation of electric power system. Oscillations in the electric power system can occur due to the sudden release of the load (Switcing-Off). The oscillation of an unstable system for a long time causes the equipment to work in an interruption. To overcome this problem, a control device is required that can work effectively in repairing the oscillation. The power system is modeled from the Single Machine Infinite Bus Model (SMIB). The state space equation is used to mathematically model SMIB. SMIB system which is a plant will be formed togetherness state variables (State-Space), using riccati equation then determined the optimal gain as controller plant. Plant is also controlled by Power Stabilizer System using phase compensation method. Using Matlab Software based simulation will be observed response of rotor speed change and rotor angle change for each of the two controlling methods. Simulation results using the Simulink-MATLAB 6.1 software will compare the analysis of the plant state in Open loop state and use the controller. The simulation response shows that the optimal control and PSS can improve the stability of the power system in terms of acceleration to achieve settling-time and Over Shoot improvement. From the results of both methods are able to improve system performance.

A mathematical model of SOFC power plant for dynamic simulation of multi-machine power systems

Modern power networks are complex multi-component dynamic system with many operational levels made up of a wide range of renewable energy resources. The low frequency oscillations may undergo and sustain to cause system separation if adequate damping is not provided. This research work presents the mathematical model of Solid Oxide Fuel Cells (SOFC) within transmission network in order to dynamic stability analysis and control. The main contribution is to propose the new linearized Heffron-Philips model of the system under consideration the SOFC power plant to studying of low frequency oscillations. The eigenvalue-based objective function is used to search optimal multi-machine power system stabilizer (PSS) with the Particle Swarm Optimization (PSO) technique under various operating conditions. The effectiveness of the proposed model is tested on three-machine power system integrated with the single SOFC power plant. The time-domain simulation results are promising and illustrate the effectiveness of the proposed stabilizers. It can be damp the low frequency oscillations in the best possible procedure and significantly improves the stability performance of the case study system.

Optimal Design of Power System Stabilizer Using Remote Signal Considering the Transport Delay

Abstract This paper proposes a novel optimal Power System Stabilizer (PSS) design method to damp inter-area oscillations in power systems. As the input of PSS, remote signals which can be obtained by Phasor Measurement Units (PMUs) are used since remote signals represent global information of the power system. The method improves both small signal stability and transient stability, taking into consideration the fluctuation range of transport delay in the communication link between PMUs and PSSs, which may significantly affect the oscillation damping performance. In the design method, Mean Variance Mapping Optimization (MVMO) is employed to determine the PSS parameters. The proposed method is applied in IEEJ (The Institute of Electrical Engineers of Japan) WEST 10-machine system model. Then, network modeshape is used to select the most appropriate remote signal. As a result of optimal design, the PSSs with both local and remote signals can give better damping than the local PSS alone, even when maximum transport delay occurs, whereas PSS designed ignoring transport delay makes the system unstable in some cases of such delay.

Application of Smart Bats Algorithm for Optimal Design of Power Stabilizer System at Sengkang Power Plant

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 based algorithm to design PSS. Bat Algorithm is an algorithm that works based on bat behavior in search of food source. Correlation with this research is, food sources sought by bats represent as PSS parameters to be optimized. Bat's algorithm will work based on a specified destination function, namely Integral Time Absolute Error (ITAE). In this research will be seen the deviation of velocity and rotor angle of each generator, in case of disturbance in bakaru generator. The analysis results show that the uncontrolled system produces a large overshoot oscillation, and after the addition of PSS oscillation control equipment can be muted. So that the overshoot and settling time of each generator can be reduced and the generator can quickly go to steady state condition

Optimal Design of Power System Stabilizer In Bakaru Power Plant Using Bat Algorithm

The problem of using Power System Stabilizer (PSS) in generator excitation is how to determine optimal PSS parameter. To overcome these problems, the authors use a method of intelligent bats based algorithm to design PSS. Bat Algorithm is an algorithm that works based on bat behavior in search of food source. Correlation with this research is, food sources sought by bats represent as PSS parameters to be optimized. Bat's algorithm will work based on a specified destination function, namely Integral Time Absolute Error (ITAE). In this research will be seen the deviation of velocity and rotor angle of each generator, in case of disturbance in bakaru generator. The analysis results show that the uncontrolled system produces a large overshoot oscillation, and after the addition of PSS oscillation control equipment can be muted. So that the overshoot and settling time of each generator can be reduced and the generator can quickly go to steady state condition.

Using Bacterial Foraging Algorithm to Design Optimal Power System Stabilizer and Comparisons with Genetic Algorithm and Particle Swarm Optimization

Using Bacterial Foraging Algorithm to Design Optimal Power System Stabilizer and Comparisons with Genetic Algorithm and Particle Swarm Optimization

Coordinated parameter design of power system stabilizers and static synchronous compensator using gradual hybrid differential evaluation

In this study, the damping scale function is used as an objective function to coordinate power system stabilizers and a static synchronous compensator with damping stabilizer parameters under various power system operating conditions to address high-frequency oscillation problems. The gradual hybrid differential evaluation algorithm developed in this study employs the gradual search method on the hybrid differential evaluation to enhance the probability of finding an optimal solution. A 16-machine power system is used to estimate the feasibility of the proposed objective function and algorithm. In the test system, all machines have stabilizers installed, and a static synchronous compensator with a damping stabilizer is placed on bus 17. The input signals of the damping stabilizer and power system stabilizers include local and remote voltage or speed deviation signals, respectively. The proposed objective function and the objective function of the combined damping factor and damping ratio are used to search for optimal power system stabilizers, and a static synchronous compensator with damping stabilizer parameters with the gradual hybrid differential evaluation algorithm and previous gradual self-tuning hybrid differential evaluation algorithms are tested under various operating conditions. The results in the frequency and time-domains reciprocally demonstrate the reliability of the simulation results. Analysis of the results indicates that the damping scale and the gradual hybrid differential evaluation algorithm can effectively coordinate power system stabilizers and the static synchronous compensator with damping stabilizer parameters to increase the transient stability of a power system.

Modeling, simulation, and optimal design of power system stabilizers using ABC algorithm

This paper introduces a methodological system for modeling, simulation, and optimal tuning of the parameters of power system stabilizer (PSS) controllers in a multimachine power system so as to enhance transient stability. The model of a multimachine power system with PSS controllers is developed in MATLAB/Simulink for the simulation design. Simulink is a software instrument related to MATLAB, which is employed for modeling, simulating, and analyzing dynamical systems. The PSS controllers' design problem is expressed as an optimization problem; and the artificial bee colony (ABC) algorithm is utilized so as to examine the optimal PSS controller's parameters. The power system's transient stability performance is enhanced through diminishing a time domain-based objective function, where the oscillatory rotor speed deviation of the generator is obtained. The results of the nonlinear simulations substantiate the efficacy of the proposed modeling and tuning approach for power system stability enhancement. These outcomes likewise indicate that the proposed PSS controllers are operative in damping low frequency oscillations. In addition, comparing the ABC algorithm with the genetic algorithm method shows that better performance is achieved.

Optimal Power System Stabilizers design via Cuckoo Search algorithm

Abstract Cuckoo Search (CS) algorithm is introduced in this paper for optimal Power System Stabilizers (PSSs) design in a multimachine power system. The PSSs parameter tuning problem is formulated as an optimization problem which is solved by CS Algorithm. An eigenvalues based objective function involving the damping ratio, and the damping factor of the lightly damped electromechanical modes is considered for the PSSs design problem. The performance of the proposed CS based PSSs (CSPSS) has been compared with Genetic Algorithm (GA) based PSSs (GAPSS) and the Conventional PSSs (CPSS) under different operating conditions and disturbances. The results of the developed CSPSS are verified through time domain analysis, eigenvalues and performance indices. Also, the effectiveness of the proposed algorithm in providing good damping characteristics is confirmed.

General Relativity Search Algorithm: A Global Optimization Approach

In this paper, a novel metaheuristic optimization algorithm inspired by General Relativity Theory (GRT) is presented. In this method that we named General Relativity Search Algorithm (GRSA), a population of particles is considered in a space free from all external non-gravitational fields and propel toward a position with least action. Based on GRT, particles have conserved masses and move along geodesic trajectories in a curved space. Step length and step direction for updating the particles are separately computed using particles velocity and geodesics, respectively. Velocity of particles is obtained by their energy–momentums. According to physical action principle, a population of particles goes to the position with minimum action. By inspiring this physical principle, GRSA will lead variables of an optimization problem move toward the optimal point. Performance of the proposed optimization algorithm is investigated by using several standard test functions and optimal Power System Stabilizers (PSSs) design in a multi-machine power system as a real-world application. Numerical simulations results demonstrate the efficiency, robustness and convergence speed of GRSA in solving various problems.

Coordinated and uncoordinated design of LFO damping controllers with IPFC and PSS using ICA and SFLA

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.

A New Meta-heuristic Technique Based on Robust Power System Stabilizer with Wind Power Penetrations

In this paper a robust Power System Stabilizer (PSS) is proposed based on inverse additive perturbation in a power system with wind farms. The proposed controller designed by new Improve Bacteria Foraging Algorithm (IBFA) to achieve robustness of this strategy where the optimization process is formulated based on an enhancement of system robust stability margin. The designed optimal PSS is based on Fuzzy Logic Controller (FLC). The effectiveness of the proposed technique is tested over ten macine 39 buses New England power system. Obtained results demonstrate the superiority of proposed technique over conventional PSS.

Water Cycle Algorithm Based Power System Stabilizer Robust Design for Power Systems

Abstract Power System Stabilizers (PSSs) are used to enhance damping of power system oscillations. This paper presents a new fast algorithm to develop PSS. According to this regard, Water Cycle Algorithm (WCA) is used to detect optimum Power System Stabilizer parameters. For this purpose, the design problem of PSS is formulated as an optimization problem and WCA by forming three subsidiary objective functions is employed to search for optimal power system stabilizer’s parameters to minimize the maximum overshoot and settling time together. In order to show the efficiency of the proposed algorithm, a comparison between WCA and without PSS condition has been done, and the results of proposed algorithm show that it detects optimum parameters in reasonable computation time to increase the power system stability.

A multi objective vector evaluated improved honey bee mating optimization for optimal and robust design of power system stabilizers

This paper presents the Parallel Vector Evaluated Improved Honey Bee Mating Optimization (VEIHBMO) as a novel multi objective technique to obtain a set of optimal Power System Stabilizers (PSSs) parameters. It includes a feedback signal of a remote machine and local and remote input signal ratios for each machine in a multi-machine power system under various operating conditions. This goal is formulated as a multi objective optimization process with two competing and non-commensurable fitness functions. The objectives considered in this paper are the time domain based integral square time of square error (ISTSE) and eigenvalues based comprising the damping factor. The effectiveness of the proposed method is demonstrated on 4-machine two-area and 16-machine five-area power system under different loading conditions. The system performance is assessed through the time multiplied absolute value of the error (ITAE), eigenvalues and figure of demerit (FD) analysis performance indices. The simulation results show that the performance of the proposed stabilizer is comparable to that which could be obtained by the conventional design, but without the need for the estimation and computation of the external system parameters.

Low-frequency power system oscillation damping using HBA-based coordinated design of IPFC and PSS output feedback controllers

In this paper, a robust method for the simultaneous coordinated design of the interline power flow controller (IPFC) and power system stabilizer (PSS) based on output feedback controllers in a single-machine infinite-bus power system for the enhancement of power systems low-frequency oscillations damping is presented. The Honey Bee Algorithm, which has a strong ability to find the most optimistic results, is employed to search for optimal IPFC and PSS output feedback controller parameters. A singular value decomposition method is utilized to select the most effective damping control signal of the IPFC output feedback controller. To assess the effectiveness and robustness of the proposed method, simulation studies are carried out for three operating conditions. Analysis of the results shows that the combined design has an excellent capability for damping a power system’s low-frequency oscillations. Moreover, system performance analysis under different operating conditions and performance indices shows the effectiveness of the proposed method even when a severe fault is applied.

Modeling and seeker optimization based simulation for intelligent reactive power control of an isolated hybrid power system

Seeker optimization algorithm (SOA) is a novel heuristic population-based search algorithm based on the concept of simulating the act of human searching. In SOA, the acts of human searching capability and understanding are exploited for the purpose of optimization. In this algorithm, search direction is based on empirical gradient by evaluating the response to the position changes and the step length is based on uncertainty reasoning by using a simple fuzzy rule. In this paper, effectiveness of the SOA has been tested for optimized reactive power control of an isolated wind–diesel hybrid power system model. In the studied power system model, a diesel engine based synchronous generator (SG) and a wind turbine based induction generator (IG) are used for the purpose of power generation. IG offers many advantages over the SG but it requires reactive power support for its operation. So, there is a gap between reactive power demand and its supply. To minimize this gap between reactive power generation and its demand, a variable source of reactive power such as static VAR compensator (SVC) is used. The SG is equipped with IEEE type-I excitation system and dual input power system stabilizer (PSS) like IEEE-PSS3B. The performance analysis of a Takagi–Sugeno fuzzy logic (TSFL)-based controller for the studied isolated hybrid power system model is also carried out which tracks the degree of reactive power compensation for any sort of input perturbation in real-time. In time-domain simulation of the investigated power system model, the proposed SOA–TSFL yields on-line, off-nominal coordinated optimal SVC and PSS parameters resulting in on-line optimal reactive power control and terminal voltage response. The performance of the proposed controller, with the influence of signal transmission delay, has also been investigated.

A Novel Objective Function and Algorithm for Optimal PSS Parameter Design in a Multi-Machine Power System

This paper proposes a novel objective function and algorithm to obtain a set of optimal power system stabilizer (PSS) parameters that include a feedback signal of a remote machine and local and remote input signal ratios for each machine in a multi-machine power system under various operating conditions. A novel function called the damping scale is proposed and formulated as an objective function to increase system damping after the system undergoes a disturbance. Three existing objective functions of the damping factor, damping ratio, and a combination of the damping factor and damping ratio were analyzed and compared with the proposed objective function. A novel algorithm called gradual self-tuning hybrid differential evolution (GSTHDE) was developed for rapid and efficient searching of an optimal set of PSS parameters. GSTHDE uses the gradual search concept on STHDE to enhance the probability of searching for an optimal solution. Eigenvalue analysis and nonlinear time domain simulation results demonstrated the effectiveness of the proposed objective function and algorithm.

A Comparison between Conventional and Optimal Power System Stabilizers for a Single Machine to an Infinite Bus Power System

The excitation control of synchronous generator in a single machine to an infinite bus (SMIB) power system is very important to improve the stability modes of power system. In addition to the usual or conventional excitation control techniques and speed governors, other devices proved its effectiveness to enhance better system stability like power system stabilizers (PSS) and static VAR compensators (SVC). In this paper, the PSS is used as an additional device to improve the SMIB power system stability. Two out of different control strategies were used; a conventional control technique (PI controller) and a linear optimal controller (LOC). A comparison between both types of PSSs was stated. The contribution of this paper is the design and application of an optimal-PSS and a PI-PSS to a synchronous generator connected to an infinite bus power system. KeywordsSingle machine to an infinite bus, power system stabilizer, excitation control, PI controller, linear optimal controller.