Placement Of Power System Stabilizers Research Articles

A novel method for optimal placement and tuning of the power system stabilizer in the multi-machine system

This paper introduces a new method for optimal placement of power system stabilizers (PSS) and tuning them simultaneously in the multi-machine system. This method is based on an improved genetic algorithm (GA), and the power system model is very accurate. This method determines the best place to install the stabilizers, using the least number of PSS and tuning their parameters simultaneously to move the poles to the left of the imaginary axis and maximize the damping ratio of mechanical modes. In addition, the proposed algorithm can consider any of the critical conditions, which are obtained based on sensitivity analysis, and suggest a robust setting for stabilizers. After implementing the proposed algorithm in MATLAB, the modal analysis and time-domain simulations in IEEE 9Bus and IEEE 39Bus systems were compared with other algorithms. The results confirm that the proposed algorithm can effectively improve dynamic stability margin.

Improving the Stability of An Interconnected Power System Using Genetic Eigenvalue Technique

Improving the power stability of an interconnected Nigerian 330KV 48 bus power system was developed using Genetic Eigenvalue Technique to mitigate the challenges of proper placement of power system stabilizer due to its highly dynamic and nonlinear nature. In order to eliminate load losses, equipment malfunctioning, and other quality issues, unnecessary tripping and cascaded failures in system network, power system stabilizers are installed to improve system stability. The operational and process data of 330KV power system grid network, cable distance meter (CDM-75), Transmission line calculator (AWR version) were sampled at Transmission Company of Nigeria Osogbo, Osun State of Nigeria. The Genetic Eigenvalue technique was used to generate eigenvalues, damping ratios and participation factors for proper placement of PSS (Power System Stabilizers) to mitigate the effect of transmission line and power plant outage contingencies. The PSSs were placed using Genetic Eigenvalue Analysis technique performed better than PSS placed based on conventional Arnoldi eigenvalue technique. The simulation results for base case voltage profile and for the trajectories of the impact of contingencies were plotted on the MATLAB/SUMULINK environment. From the output plots, the percentage of voltage instability suppression time improvement of Genetic technique over Arnoldi is 51.86%. Oscillation suppression at generator 1, is 74%, and that of generator 3 is 79%, and finally at generator 5 is 76.98%. PSS placed on Nigerian 330KV 48 bus plant and transmission line of an interconnected power system case study power system based on genetic analysis suppressed voltage oscillation faster compared to the time it took the PSS based on the conventional Arnoldi eigenvalue analysis technique. Keywords: Power Stability- Genetic Eigenvalue, ArnoldiEigenvalue, PSS. DOI: 10.7176/JETP/11-1-03 Publication date: January 31 st 2021

A Critical Assessment of Oscillatory Modes in Multi-Microgrids Comprising of Synchronous and Inverter-Based Distributed Generation

This paper provides a critical assessment of oscillatory modes for a droop-controlled multi-microgrid (MMG) consisting of inverter-based and synchronous-based distributed generation (DG). Local and inter-microgrid oscillatory modes similar to conventional interconnected power systems are observed. However, an additional new and more “dominant” oscillatory mode caused by interactions between close-by coherent synchronous-based and inverter-based DGs in the MMG is identified. Sensitivity analysis is employed to assess the impact of various MMG configurations and parameters such as: interconnecting line length, droop gain, exciter gain, and governor gain on MMG oscillatory modes. Parametric studies are conducted to highlight the impact of oscillatory modes on MMG transient and dynamic performances. Consequently, power system stabilizers (PSSs) are developed for both inverter-based and synchronous-based DGs to improve the transient and dynamic performances of the MMG. Residues are calculated and therefore utilized to determine the effect of PSS placement on the MMG oscillatory modes. Finally, small-signal stability analysis results and the performances of the PSSs are validated through time domain simulations on MATLAB/Simulink.

Small Signal Stability Analysis of Wind Turbine Penetration in Sulselrabar Interconnection System

This paper present and explain the analysis of power flow and small-signal stability of the electrical system in the islands of South Sulawesi, East and West (Sulselrabar) located in Indonesia. The research focused on the Eigen values analysis that used to investigate small-signal stability performance of the main electricity grid when the fault conditions with and without control equipment as well as the inclusion of wind turbines large scale on the system. Power Systems Analysis Toolbox (PSAT), which integrated in MATLAB is used to develop a network topology in Sulselrabar. This study allowed us to determine the optimal location of the placement of Power System Stabilizer (PSS) to dampen the oscillation. The simulation result shows the placement of PSS on two generators can add system stability and help the system to resume operation at the balance point. Time domain simulation methods are used to see the frequency response of the rotor speed.

Small-Signal-Stability Enhancement using a Power-System Stabilizer based on the Cuckoo-Search Algorithm against Contingency N-1 in the Sulselrabar 150-kV System

Small-signal stability is one of the main factors limiting power transmission in conventional power systems. This concern is primarily handled by adding damper windings of a synchronous generator and power-system stabilizer (PSS). However, due to the impact of the N-1 contingency, damper windings and a conventional PSS are insufficient to overcome this problem. Proper placement and design of the PSS are crucial for improving stability. One approach to optimizing the placement and tuning of the PSS is to use an artificial-intelligence method. Here, the cuckoo-search algorithm (CSA) is proposed to optimize the PSS tuning and placement. Based on simulation, it is found that a PSS based on the CSA can enhance the system's small-signal stability. The critical, local, and inter-area modes of the investigated system improve significantly. The oscillatory condition is more highly damped, as indicated by a smaller overshoot and faster settling time. It is also found that the CSA can be used to tune the PSS parameter under an N-1 contingency. From the analytical results of the N-1 contingency condition, optimal tuning of the PSS parameters was obtained, resulting in PSS-placement options for generators 1 to 7 and 12 to 15, producing a minimum damping of 0.611.

Optimal Placement and Tuning Approach for Design of Power System Stabilizers and Wide Area Damping Controllers Considering Transport Delay

Abstract In this paper, a novel optimal placement and parameter tuning approach for Power System Stabilizer (PSS) is proposed to damp both local and inter-area modes in mesh like power system. The design target is two-level PSS consisting of ΔP type local PSS and Δθ type Wide Area Damping Controller (WADC). For the PSS placement, modeshape with eigenvector sensitivity and coherency analysis are used to determine the appropriate placement of both local PSS and WADC. For the PSS parameter tuning, metaheuristics based approach via Mean Variance Mapping Optimization (MVMO) is employed in order to consider the time domain analysis. The proposed objective function designs at first the local PSS only to improve damping coefficient and damping ratio of eigenvalue. After that, it designs the WADC overlapping with already designed local PSS by time domain analysis, taking into account the transport delay in the remote signal between Phasor Measurement Unit (PMU) and PSS. The proposed method is applied in IEEE New England 39-Bus (NE 39-bus) system model. Then, modeshape and coherent grouping analysis give us understandable system aspect, the local PSS and the WADC optimized by using MVMO considering the transport delay improve both local and inter-area modes whereas a method ignoring the transport delay make system poorly damped.

Tuning of power system stabilizer for small signal stability improvement of interconnected power system

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.

Optimal Tuning and Placement of Power System Stabilizers Based Eigenvalue

<p>In this paper, an eigenvalue assignment based Particle Swarm Optimization and Participation Factor for Optimal tuning and placement of power system stabilizers is proposed. The proposed approach presents a two-step methodology to find optimal location and parameters of PSS. The Participation Factor method is computed using the modal analysis toolbox from DIgSILENT, and used to determine the power system stabilizers optimal location. A Particle Swarm Optimization algorithm is written in MATLAB to search the power system stabilizers optimal parameters. Two eigenvalue-based objective functions to ensure a maximum damping of the inter-area modes as well as of the local modes by assigning them in a robust stability area are considered. The performance of the proposed approach is tested and examined on the four-machine two-area power system. Linear modal analysis and non-linear time domain simulations show the robustness of the proposed approach.</p>

An Integrated Method for Optimal Placement and Tuning of a Power System Stabilizer Based on Full Controllability Index and Generator Participation

In this paper, an integrated architecture for optimal placement and tuning of power system stabilizers (PSSs) in multimachine systems is proposed in order to improve system stability, damp oscillations, and increase damping of the power system oscillatory modes. The proposed approach provides full-rank optimal conditions for the PSS placement, which provide complete controllability of the system. In addition, this method allows optimal tuning of PSS parameters based on real and imaginary coefficients for damping. Test cases are performed to evaluate the proposed concept, and it has been found that the proposed architecture fully captures system dynamics and provides an efficient way for PSS placement and tuning. The architecture is also verified using a real-time digital simulator on a real experimental test bed and found that the method provides improvement in system stability and reduces low-frequency oscillations in local and inter-area modes of oscillations.

An integrated approach for optimal placement and tuning of power system stabilizer in multi-machine systems

In this paper, a hybrid approach for tuning and placement of power system stabilizers (PSS) in multi-machine power systems is provided with the aim of reducing low-frequency oscillations (LFO) and improving power system dynamic stability with wide range of changes in system parameters and operating point of the system. PSS parameters are adjusted using Particle Swarm Optimization algorithm (PSO), and using Takagi–Sugeno (TS) fuzzy, optimal location for the PSS is determined. The employed fuzzy system has two inputs, the real part and the damping coefficient of network eigenvalues. The results of test on a grid four machine-two area sample, show optimal performance of the proposed method in improving system stability and reducing low-frequency oscillations of local and inter-area modes.

An efficient particle swarm optimization technique with chaotic sequence for optimal tuning and placement of PSS in power systems

This paper presents a novel and efficient method for the optimal tuning and placement of power system stabilizer (PSS). The proposed modified particle swarm optimization (MPSO) integrates the particle swarm optimization with passive congregation (PSOPC) and the chaotic sequence. Passive congregation helps each swarm member in receiving a multitude of information from other members and thus decreases the possibility of a failed attempt at detection or a meaningless search. In addition, the chaotic sequence concept is introduced to improve the global searching capability and prevent the premature convergence due to local minima. The proposed optimization procedure handles the problem-specific constraints, in this case it is related to low frequency oscillations in power systems and PSS, using a penalty function. Based on this, tuning and placement of PSS over a wide range of system configurations is formulated as a multi-objective function where the main objective is the aggregation of the three objectives related to the damping ratio and damping factor, and the number of PSS. The robustness of the proposed PSS tuning technique is verified on a multi-machine power system under different operating conditions. The performance of the proposed MPSO is also compared to the PSOPS and PSO, genetic algorithm through eigenvalue analysis, nonlinear time-domain simulation and statistical tests. Finally, the proposed method is applied to find out the best candidate machines to be equipped with PSSs. The obtained results showed that the new method can find the best placements and the optimum PSSs parameters simultaneously with an excellent global damping performance.