Application of Multi-Objective Genetic Algorithm for Optimal Design of SSSC Based Robust Damping Controllers to Improve Small Signal Stability

2006 ◽  
Author(s):  
M. Ladjavardi ◽  
M.A.S. Masoum
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Small Signal ◽  
Small Signal Stability ◽  
Multi Objective ◽  
Signal Stability ◽  
Multi Objective Genetic Algorithm ◽  
Damping Controllers

scholarly journals Optimal design of controllers for power network connected SOFC using of multi-objective PSO

2018 ◽  
Vol 15 (2) ◽  
pp. 145-163 ◽  
Author(s):  
Amin Safari ◽  
Hossein Shahsavari ◽  
Farshad Babaei
Keyword(s):  
Damping Ratio ◽  
Damping Factor ◽  
Small Signal ◽  
Small Signal Stability ◽  
Machine System ◽  
Multi Objective ◽  
Signal Stability ◽  
Power Oscillations ◽  
System Stabilizer ◽  
Small Signal Modeling

In this paper, we study the concept and forming manner of Solid Oxide Fuel Cell (SOFC) into the electrical system and then, its effect on small signal stability is investigated. The paper illustrates the essential module, mathematical analysis and small signal modeling of the SOFC joined to single machine system. The aim of this study is to reduce power oscillations in the presence of the SOFC with optimal stabilizer. The multi-objective Particle Swarm Optimization (MOPSO) technique has been used for designing a Power System Stabilizer (PSS) in order to improve the performance of the system. Two objective functions are regarded for the design of PSS parameters in order to maximize the damping factor and the damping ratio of the system. To evaluate the efficiency of the proposed optimal stabilizers, four scenarios are considered and then, its results have been analyzed. The proposed PSS tuning technique can be applied to a multi-machine system connected to the SOFC. The efficiency of MOPSO based proposed PSS on the oscillations the system related to SOFC is illustrated by time-domain simulation and also, the comparison of the MOPSO based proposed PSS with the PSS based-single objective method has been prepared.

scholarly journals Optimal Integration of the Renewable Energy to the Grid by Considering Small Signal Stability Constraint

2017 ◽  
Vol 7 (5) ◽  
pp. 2329
Author(s):  
I Made Wartana ◽  
Ni Putu Agustini ◽  
Jai Govind Singh
Keyword(s):  
Genetic Algorithm ◽  
Renewable Energy ◽  
Wind Turbine ◽  
Optimal Allocation ◽  
Optimization Problems ◽  
Small Signal ◽  
Small Signal Stability ◽  
Nsga Ii ◽  
Signal Stability ◽  
Optimal Integration

In recent decades, one of the main management’s concerns of professional engineers is the optimal integration of various types of renewable energy to the grid. This paper discusses the optimal allocation of one type of renewable energy i.e. wind turbine to the grid for enhancing network’s performance. A multi-objective function is used as indexes of the system’s performance, such as increasing system loadability and minimizing the loss of real power transmission line by considering security and stability of systems’ constraints viz.: voltage and line margins, and eigenvalues as well which is representing as small signal stability. To solve the optimization problems, a new method has been developed using a novel variant of the Genetic Algorithm (GA), specifically known as Non-dominated Sorting Genetic Algorithm II (NSGA-II). Whereas the Fuzzy-based mechanism is used to support the decision makers prefer the best compromise solution from the Pareto front. The effectiveness of the developed method has been established on a modified IEEE 14-bus system with wind turbine system, and their simulation results showed that the dynamic performance of the power system can be effectively improved by considering the stability and security of the system.

Coordinated control among PSS, WTG and BESS for improving Small-Signal Stability

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Feba Alias ◽  
Manohar Singh
Keyword(s):  
Reactive Power ◽  
Coordinated Control ◽  
Small Signal ◽  
Small Signal Stability ◽  
Local Modes ◽  
Control Approach ◽  
Signal Stability ◽  
Damping Controllers ◽  
The Impact ◽  
Inertia Response

Abstract The goal towards attaining a sustainable future has led to the rapid increase in the integration of converter control based generators (CCBGs). The low inertia response characteristics of CCBGs and the weak tie lines in interconnected systems pose a huge threat to Small-Signal Stability (SSS). Adequate damping of low-frequency oscillations (LFO) is pivotal in ensuring the maximum power transfer through the critical transmission corridors. These operational issues become more serious with the significant reduction in system inertia as a result of the high penetration of CCBGs. Therefore, appropriate control techniques are an absolute requirement for preventing LFOs from limiting the penetration of CCBGs in interconnected networks. This may also eventually lead to revisions in grid codes mandating CCBGs to provide auxiliary damping control. But, the progressive addition of multiple damping controllers for specific target modes can lead to the drifting of eigenvalues (EVs) associated with other electromechanical modes (EMs) in the system. This is due to the adverse interactions between multiple damping controllers in the uncoordinated control approach and may result in deteriorating SSS. Therefore, this paper proposes a simultaneous coordinated control among Battery Energy Storage System (BESS), Wind Turbine Generators (WTG) and Power System Stabilizer (PSS) for enhancing SSS in networks with high wind penetration by considering both inter-area (IA) and local modes. The performance of the proposed coordinated control is corroborated using IEEE 68 bus system for multiple operating scenarios for which the critical modes in the system have the lowest damping index (DI). The effectiveness of modulating the active power, reactive power and simultaneous modulation of both active and reactive power injected by BESS along with a dual-channel Optimized WTG Damping Controller (DOWDC) and PSS is evaluated. The impact of the different coordinated control strategies on voltage dynamics is also investigated. The simulation results validate the better performance of the proposed coordinated control over uncoordinated control approaches.

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