Design of power system stabilizers to damp low frequency inter-area oscillations with limited information

2019 ◽  
Author(s):  
J. Renedo ◽  
L. Sigrist ◽  
L. Rouco
Keyword(s):  
Power System ◽  
Low Frequency ◽  
Limited Information ◽  
Power System Stabilizers

Optimal Coordination of PSS and SSSC Controllers in Power System Using Ant Colony Optimization Algorithm

2021 ◽  
Author(s):  
Mehrdad Ahmadi Kamarposhti ◽  
Ilhami Colak ◽  
Celestine Iwendi ◽  
Shahab S. Band ◽  
Ebuka Ibeke
Keyword(s):  
Power Plant ◽  
Power System ◽  
Ant Colony Algorithm ◽  
Phase Error ◽  
Low Frequency ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Power System Stabilizers ◽  
Three Phase ◽  
Optimal Coordination

Volatility leads to disruption in synchronism between generators of a continuous system. The frequency of the volatility is usually between a few tenths of Hz to several Hz. This volatility is sometimes divided into two types, local and interregional. Local volatility is the low-frequency volatility of a power plant unit or units of a power plant relative to the grid whereas interregional volatility is the volatility of the units of one area relative to the units of another area. The worst kind of low-frequency volatility occurs when the power system in a region has a short three-phase connection to the earth, creating a complete instability of the grid and operating protective systems. One of the ways to improve the dynamic stability and steady-state of the power system is to use power system stabilizers and FACTS devices in the system. In this paper, the stabilization of the power system stabilizers (PSSs) and SSSC is done using the ant colony algorithm. Studies on a four-machine system with the three-phase error were performed in two scenarios and finally compared with the PSO method. The simulation results show that the proposed method produced more accurate performance.

A Novel Nature-Inspired Improved Grasshopper Optimization-Tuned Dual-Input Controller for Enhancing Stability of Interconnected Systems

2020 ◽  
pp. 2150134
Author(s):  
Shivakumar Rangasamy ◽  
Yamuna Kuppusami
Keyword(s):  
Power System ◽  
Low Frequency ◽  
Optimization Criterion ◽  
System Stability ◽  
Unstable Condition ◽  
Power System Stabilizers ◽  
Electromechanical Oscillations ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization ◽  
Power System Oscillations

Power system often experiences the problem of low-frequency electromechanical oscillations which leads the system to unstable condition. The problem can be corrected by implementing power system stabilizers (PSSs) in the excitation control system of alternator. This paper provides a novel and efficient approach to design an Improved Grasshopper Optimization Algorithm (IGOA)-based dual-input controller to damp the inter-area-mode power system oscillations. A three-fold optimization criterion has been formulated to calculate the optimum values of the controllers required for power system stability. The damping performance of the proposed controller is compared with conventional PSS and genetic algorithm-based controllers to validate the better performance of the proposed IGOA-based controller under various system loading conditions and disturbances.

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.

Designing of power system stabilizer based on neural-like P systems

2019 ◽  
Vol 234 (2) ◽  
pp. 199-210 ◽  
Author(s):  
Meng Li ◽  
Yong Chen
Keyword(s):  
Power System ◽  
Damping Ratio ◽  
Low Frequency ◽  
P Systems ◽  
Power System Stabilizer ◽  
Low Frequency Oscillation ◽  
Power System Stabilizers ◽  
Operation Rules ◽  
Optimal Power ◽  
System Stabilizer

Power system stabilizers play an important role in reducing the low-frequency oscillation. In this article, the problem of robustly selecting the parameters of the power system stabilizers is studied. A new neural-like P systems optimization algorithm is proposed in order to optimize the power system stabilizer parameters. First, the structure of the neural-like P systems is established. Then, the operation rules, including forgetting rule, spiking rule, evolving rule, and transferring rule, are designed. Furthermore, a new objective function is constructed on the eigenvalues and damping ratio. Finally, the proposed algorithm is tested on the 16-machine and 68-bus system. The simulation results show the effectiveness and robustness of the proposed methods to select the optimal power system stabilizer parameters for damping out the low f oscillation.

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