scholarly journals Enhancement of small signal stability of a DFIG-based wind power system using fuzzy logic control

1970 ◽  
Vol 8 (3) ◽  
pp. 48-63
Author(s):  
T. K. Renuka ◽  
P. Reji ◽  
Sasidharan Sreedharan
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Short Circuit ◽  
Test System ◽  
Operating Conditions ◽  
Small Signal ◽  
Small Signal Stability ◽  
Fuzzy Logic Controllers ◽  
Signal Stability ◽  
Logic Controllers

This paper proposes fuzzy logic controllers for enhancing the small signal stability of DFIG-based wind integrated power system. The test system used is single machine infinite bus system integrated with conventional proportional-integral controllers. The fuzzy logic controllers provide optimum proportional and integral gains under various operating conditions namely wind speed and grid strength. The effects of strong and weak grid strengths have been taken into account with short circuit level of 40 MVA and 16 MVA, respectively. The obtained result justifies that the damping ratio and there by the small signal stability of such a system have been enhanced considerably by the action of fuzzy logic controllers. The generalization can be enlarged to multi-machine systems in various dynamic conditions.Keywords : Doubly Fed Induction Generator, small signal stability, state space model, eigenvalue analysis, fuzzy logic based tuning circuits

scholarly journals Modelling and Simulation for Small Signal Stability of Multi-machine Power System under Various Disturbance Conditions

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Ohnmar Swe
Keyword(s):  
Power System ◽  
Time Domain ◽  
Test System ◽  
Small Signal ◽  
Time Domain Simulation ◽  
Small Signal Stability ◽  
Signal Stability ◽  
Rotor Angle ◽  
Network Fault ◽  
Signal Dynamic

This paper presents the small signal stability of multi-machine power system over the 58-Bus, 26-Machine, Yangon Distribution Network and is validated with MATLAB software under various disturbance conditions. Time-domain solution analysis is employed to determine the small signal dynamic behavior of test system. Transtability model is used to perform time-domain simulation in SIMULINK. The simulation is carried out for normal condition, reference voltage of regulator (Vref) disturbance, mechanical torque (Tm)disturbance and network (fault) disturbance and the conditions of change in center of inertia for rotor angle (delta COI),  slip for center of inertia (slip COI), field current and mechanical torque are observed. According to the simulation results, perturbation of Vref shows only instability on the system. But ramping of Tm and network disturbance can cause large disturbance on the system and unstable conditions can be observed.

scholarly journals Probabilistic small-signal stability analysis of power system with solar farm integration

2019 ◽  
pp. 1276-1289 ◽  
Author(s):  
SAMUNDRA GURUNG ◽  
SUMATE NAETILADDANON ◽  
ANAWACH SANGSWANG
Keyword(s):  
Power System ◽  
Density Function ◽  
Forecast Error ◽  
Low Frequency ◽  
Test System ◽  
System Stability ◽  
Small Signal ◽  
Small Signal Stability ◽  
Oscillatory Dynamics ◽  
Signal Stability

Currently, large-scale solar farms are being rapidly integrated in electrical grids all over the world. However, the photovoltaic (PV) output power is highly intermittent in nature and can also be correlated with other solar farms located at different places. Moreover, the increasing PV penetration also results in large solar forecast error and its impact on power system stability should be estimated. The effects of these quantities on small-signal stability are difficult to quantify using deterministic techniques but can be conveniently estimated using probabilistic methods. For this purpose, the authors have developed a method of probabilistic analysis based on combined cumulant and Gram– Charlier expansion technique. The output from the proposed method provides the probability density function and cumulative density function of the real part of the critical eigenvalue, from which information concerning the stability of low-frequency oscillatory dynamics can be inferred. The proposed method gives accurate results in less computation time compared to conventional techniques. The test system is a large modified IEEE 16-machine, 68-bus system, which is a benchmark system to study low-frequency oscillatory dynamics in power systems. The results show that the PV power fluctuation has the potential to cause oscillatory instability. Furthermore, the system is more prone to small-signal instability when the PV farms are correlated as well as when large PV forecast error exists.

Small Signal Stability Analysis of Grid Connected Photovoltaic

2017 ◽  
Vol 6 (3) ◽  
pp. 553 ◽  
Author(s):  
Shalom Lim Zhu Aun ◽  
Marayati Bte Marsadek ◽  
Agileswari K. Ramasamy
Keyword(s):  
Stability Analysis ◽  
Power System ◽  
Damping Ratio ◽  
Test System ◽  
Small Signal ◽  
Small Signal Stability ◽  
Solar Pv ◽  
Signal Stability ◽  
Pv Penetration ◽  
Small Signal Stability Analysis

This paper primarily focuses on the small signal stability analysis of a power system integrated with solar photovoltaics (PV). The test system used in this study is the IEEE 39-bus. The small signal stability of the test system are investigated in terms of eigenvalue analysis, damped frequency, damping ratio and participation factor. In this study, various conditions are analyzed which include the increase in solar PV penetration into the system and load variation. The results obtained indicate that there is no significant impact of solar PV penetration on the small signal stability of large scaled power system.

A Study on Small Signal Stability of the Large-Scale Wind Farm with DFIGs

2013 ◽  
Vol 765-767 ◽  
pp. 2579-2585
Author(s):  
Min Jing Yang ◽  
Yan Li ◽  
Jin Yu Wen ◽  
Chun Fang Liu ◽  
Min Jie Zhu ◽  
...  
Keyword(s):  
Power System ◽  
Large Scale ◽  
Wind Farm ◽  
System Analysis ◽  
Wind Farms ◽  
Test System ◽  
Small Signal ◽  
Small Signal Stability ◽  
Signal Stability ◽  
Induction Generators

The high penetration of doubly-fed induction generators (DFIGs) entails a change in dynamics and operational characteristics of the power system, thus this paper investigates the small signal stability of the large-scale wind farm with DFIGs. The GE 1.5MW DFIG is modeled in power system analysis software package (PSASP), and a large-scale wind farm with DFIGs is established. Then, the two-area test system with four generators is applied to assess the effect of the large wind farm on power system inter-area oscillatory mode in which the penetration and the installation site of the wind farm are considered. Finally, the simulation results indicate that abundant penetration of DFIG-based wind power will improve the inter-area oscillatory, and the integration of wind farms with DFIGs in the receiving area makes the inter-area mode highly damped.

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

2017 ◽  
Vol 16 (1/2) ◽  
pp. 3-28 ◽  
Author(s):  
Prasenjit Dey ◽  
Aniruddha Bhattacharya ◽  
Priyanath Das
Keyword(s):  
Power System ◽  
Low Frequency ◽  
Operating Conditions ◽  
System Stability ◽  
Interconnected Systems ◽  
Small Signal ◽  
Small Signal Stability ◽  
Power System Stabilizers ◽  
Signal Stability ◽  
Low Frequency Oscillations

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.

scholarly journals Performance Comparison of Adaptive Estimation Techniques for Power System Small-Signal Stability Assessment

2010 ◽  
Vol 7 (2) ◽  
pp. 10
Author(s):  
E. A. Feilat
Keyword(s):  
Power System ◽  
Least Squares ◽  
Operating Conditions ◽  
Recursive Least Squares ◽  
Small Signal ◽  
Loading Conditions ◽  
Small Signal Stability ◽  
Signal Stability ◽  
Wide Range ◽  
Damping Torque

This paper demonstrates the assessment of the small-signal stability of a single-machine infinite- bus power system under widely varying loading conditions using the concept of synchronizing and damping torques coefficients. The coefficients are calculated from the time responses of the rotor angle, speed, and torque of the synchronous generator. Three adaptive computation algorithms including Kalman filtering, Adaline, and recursive least squares have been compared to estimate the synchronizing and damping torque coefficients. The steady-state performance of the three adaptive techniques is compared with the conventional static least squares technique by conducting computer simulations at different loading conditions. The algorithms are compared to each other in terms of speed of convergence and accuracy. The recursive least squares estimation offers several advantages including significant reduction in computing time and computational complexity. The tendency of an unsupplemented static exciter to degrade the system damping for medium and heavy loading is verified. Consequently, a power system stabilizer whose parameters are adjusted to compensate for variations in the system loading is designed using phase compensation method. The effectiveness of the stabilizer in enhancing the dynamic stability over wide range of operating conditions is verified through the calculation of the synchronizing and damping torque coefficients using recursive least square technique.

scholarly journals Small Signal Stability Analysis of Multi-Area Power System

2020 ◽  
Vol 9 (4) ◽  
pp. 1850-1855
Keyword(s):  
Fuzzy Logic ◽  
Steady State ◽  
Stability Analysis ◽  
Power System ◽  
System Stability ◽  
Small Signal ◽  
Small Signal Stability ◽  
Interconnected Power System ◽  
Signal Stability ◽  
Small Signal Stability Analysis

This paper focuses on methodologies for calculation and examination of oscillatory security of interconnected power system network against constant disturbances. For instance, voltage soundness, transient dependability and oscillatory behaviors are also the measure of power system stability, which must be evaluated. For that proposed strategies based on proportional integral and fuzzy logic controlling techniques are implemented. The integral controller-based technique provides the zero steady-state error and with adequate damping, time to reach steady state can be reduced, on the cost of oscillation in frequency and tie-line power. On the contrary, fuzzy logic has demonstrated that strategies of computational intelligence can alleviate the quick appraisal of oscillatory solidness with less time to reach steady state. Furthermore, Eigenvalues are constructed for small signal stability analysis, utilizing a parallel variation of Arnoldi technique, reducing the time essential for calculation of vast Multi-Area power frameworks. For exhibit purposes, models have been composed utilizing MATLAB/SIMULINK and with the assistance of the fuzzy logic.

Small signal stability analysis of power systems integrated with wind power using sensitivity-based index

2019 ◽  
pp. 0309524X1986842 ◽  
Author(s):  
Arghya Mitra
Keyword(s):  
Power System ◽  
Wind Power ◽  
Wind Farm ◽  
Operating Conditions ◽  
Sensitivity Index ◽  
Small Signal ◽  
Small Signal Stability ◽  
System Matrix ◽  
Signal Stability ◽  
Bus System

To know the inherent property of the power system connected with a wind farm along with its associated controllers, a small signal stability study is required. For this, a linearized system model has to be developed. The small signal model of the system with wind farm along with its controllers is discussed here. The eigenvalues of system matrix are computed from the linearized model of the power system. The absolute value of the real part of eigenvalues indicates distance from instability. The sensitivity of this minimum real part of eigenvalues with respect to small changes of wind power injection is used as an index to assess the small signal stability under various operating conditions. The optimum value of the wind power can also be determined with the help of the proposed eigenvalue sensitivity index. The systems used for the study are WSCC 3-machine 9-bus system and IEEE 16-machine 68-bus system.

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