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 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.

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

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3416-3423
Keyword(s):  
Power System ◽  
Low Frequency ◽  
Synchronous Machine ◽  
Power System Stabilizer ◽  
Local Mode ◽  
Small Signal ◽  
Small Signal Stability ◽  
Signal Stability ◽  
Low Frequency Oscillations ◽  
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.

scholarly journals Improved DE Algorithm for Power System Stabilizer for Damping Low Frequency Osci llations

2019 ◽  
Vol 9 (2S2) ◽  
pp. 606-611
Keyword(s):  
Power System ◽  
Low Frequency ◽  
Operating Conditions ◽  
Power System Stabilizer ◽  
Small Signal ◽  
Small Signal Stability ◽  
Interconnected Power System ◽  
Signal Stability ◽  
De Algorithm ◽  
System Stabilizer

In the large interconnected power system, maintaining the Small signal stability of the system is of more concern, for the stable, secure and reliable operation. This paper proposes an Improved Differential Evolution (DE) Algorithm based Optimal Power system stabilizer (PSS) for damping the low frequency oscillations. Enhancing the damping of system is formulated as the optimization problem. DE/Best Mutation Operator is adopted for producing the mutation vector, to augment the convergence rate of DE algorithm. The effectiveness of the proposed approach has been tested in Single Machine Infinite Bus (SMIB) system under different operating conditions. The time response evaluations has justified the superiority of the proposed approach for damping the oscillations and thereby improving the Small signal stability of the system.

Small Signal Stability Analysis Based on Multi-Band Parallel Technology in Henan Power Grid

2013 ◽  
Vol 441 ◽  
pp. 258-262
Author(s):  
Lin Lin Yu ◽  
Yu Fei Rao ◽  
Shi Qian Wang
Keyword(s):  
Stability Analysis ◽  
Power System ◽  
Power Grid ◽  
System Stability ◽  
Small Signal ◽  
Small Signal Stability ◽  
Work Efficiency ◽  
Signal Stability ◽  
Small Signal Stability Analysis ◽  
Multi Band

With the rapid growth in the size of Henan grid, in the context of UHV networking, Henan power grid operation is facing a more complex mechanism and operating characteristics. Risks affecting the security and stability will be more subtle. There are more and more problems in frequency oscillation. The power system has much more generators and dimension after interconnection. Small signal stability analyzing eigenvalue complex and longer, which greatly reduces the work efficiency. This paper which based on Henan power system stability diagnostic platform developed technology based on multi-band parallel algorithm for small signal stability analysis. The analysis of the small signal stability eigenvalue calculation is assigned to a different platform computing nodes simultaneously. Then this method is applied to Henan grid in the year of 2012. The results show that the small signal stability algorithm which based on the multi-band can ensure the correctness of calculations. Simultaneously, calculation time is greatly reduced and the work efficiency is improved. The practice has a strong role in the promotion.

scholarly journals Assessing the Impact of DFIG Synthetic Inertia Provision on Power System Small-Signal Stability

Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3440 ◽  
Author(s):  
Edgar Lucas ◽  
David Campos-Gaona ◽  
Olimpo Anaya-Lara
Keyword(s):  
Power System ◽  
Large Scale ◽  
Damping Ratio ◽  
System Stability ◽  
Electrical Network ◽  
Small Signal ◽  
Small Signal Stability ◽  
Signal Stability ◽  
Electromechanical Modes ◽  
The Impact

Synthetic inertia provision through the control of doubly-fed induction generator (DFIG) wind turbines is an effective means of providing frequency support to the wider electrical network. There are numerous control topologies to achieve this, many of which work by making modifications to the DFIG power controller and introducing additional loops to relate active power to electrical frequency. How these many controller designs compare to one-another in terms of their contribution to frequency response is a much studied topic, but perhaps less studied is their effect on the small-signal stability of the system. The concept of small-signal stability in the context of a power system is the ability to maintain synchronism when subjected to small disturbances, such as those associated with a change in load or a loss of generation. Amendments made to the control system of a large-scale wind farm will inevitably have an effect on the system as a whole, and by making a DFIG wind turbine behave more like a synchronous generator, which synthetic inertia provision does, may incur consequences relating to electromechanical oscillations between generating units. This work compares the implications of two prominent synthetic inertia controllers of varying complexity and their effect on small-signal stability. Eigenvalue analysis is conducted to highlight the key information relating to electromechanical modes between generators for the two control strategies, with a focus on how these affect the damping ratios. It is shown that as the synthetic inertia controller becomes both more complex and more effective, the damping ratio of the electromechanical modes is reduced, signifying a decreased system stability.

Fast Analysis of Power System Stability by Artificial Neural Network

2013 ◽  
Vol 732-733 ◽  
pp. 848-851
Author(s):  
Chao Chun Li ◽  
Pei Hwa Huang
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Power System ◽  
Oscillation Mode ◽  
System Stability ◽  
Small Signal ◽  
Small Signal Stability ◽  
System Matrix ◽  
Signal Stability ◽  
Artificial Neural

Power system small signal stability concerns the ability of the power system to maintain stability subject to small disturbances. The analysis of small signal stability often has to deal with high-order system matrix due to the large number of generating units so that it is not easy to calculate and analyze the original system matrix and the whole set of eigenvalues. In this paper a new approach is proposed to take advantage of the specific feature of the parallel structure of artificial neural network for calculating the most critical eigenvalue or all eigenvalues of the unstable oscillation mode. The developed algorithm is tested on a sample power system to validate the feasibility of the proposed method for the calculation of the critical eigenvalue.

scholarly journals Improvement of Small Signal Stability of SMIB System with Optimized Power System Stabilizer

2020 ◽  
Vol 9 (7) ◽  
pp. 709-716
Keyword(s):  
Power System ◽  
Low Frequency ◽  
Power System Stabilizer ◽  
Small Signal ◽  
Small Signal Stability ◽  
Swarm Optimization ◽  
Signal Stability ◽  
System Stabilizer ◽  
Stability Issues ◽  
Damping Torque

As electrical power system is a complex system, there are more chances of stability issues may arise. One of the stability issues is Low Frequency Oscillations (LFOs) which makes the system unstable. As these oscillations are having low frequency i.e. large time constant with slowly increasing magnitude, they are referred to small signal stability. The main reason of these oscillations is due to lack of sufficient damping torque. Automatic Voltage Regulator (AVR) action in generator is providing sufficient synchronizing torque for system stability. This is possible with high gain and low time constant AVR which results in reduction of damping torque. Power System Stabilizer (PSS) is used together with AVR for providing necessary damping torque to minimize the LFOs. For effective damping, the PSS performance is improved by optimizing its parameters. In this paper, Single Machine Infinite Bus (SMIB) system is considered for studying the effect of LFOs. The SMIB system is simulated for a step disturbance in reference voltage and the results are carried out for different optimizing techniques Particle Swarm Optimization (PSO), Cat Swarm Optimization (CSO), Teaching and Learning based Optimization (TLBO)

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.

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