scholarly journals Optimal Reactive Power for Voltage Stability in Distribution Systems Connected Wind Turbine Farm using Particle Swarm Optimization

2017 ◽  
Author(s):  
Mongkol Treekijjanon ◽  
Suparat Srimongkol ◽  
Uthen Leeton ◽  
Boonruang Marungsri ◽  
Thanatchai Kulworawanichpong
Keyword(s):  
Particle Swarm Optimization ◽  
Wind Turbine ◽  
Distribution Systems ◽  
Voltage Stability ◽  
Reactive Power ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Stability In Distribution

scholarly journals REAL POWER LOSS REDUCTION & VOLTAGE STABILITY AMPLIFICATION BY HYBRIDIZATION OF RESTARTED SIMULATED ANNEALING WITH PARTICLE SWARM OPTIMIZATION ALGORITHM

2018 ◽  
Vol 6 (9) ◽  
pp. 246-258
Author(s):  
K. Lenin
Keyword(s):  
Particle Swarm Optimization ◽  
Simulated Annealing ◽  
Swarm Intelligence ◽  
Optimization Algorithm ◽  
Voltage Stability ◽  
Reactive Power ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Intelligence Algorithm ◽  
Swarm Intelligence Algorithm

This paper presents an algorithm for solving the multi-objective reactive power dispatch problem in a power system. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. Evolutionary algorithm and Swarm Intelligence algorithm (EA, SI), a part of Bio inspired optimization algorithm, have been widely used to solve numerous optimization problem in various science and engineering domains. Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm that shares many similarities with evolutionary computation techniques. However, the PSO is driven by the simulation of a social psychological metaphor motivated by collective behaviors of bird and other social organisms instead of the survival of the fittest individual. The Simulated Annealing (SA) algorithm is a probabilistic hill-climbing technique that is based on the annealing/cooling process of metals. In total, most moves may be accepted at initial stages, but at the final stage only improving ones are likely to be allowed. This can help the procedure jump out of a local minimum. However, sometimes it is better to move back to a former solution that was significantly better rather than always moving from the current state. This process is called “restarting” of SA & called as Restarted Simulated Annealing (RSA). In this paper we proposed a hybridized restarted simulated annealing particle swarm optimization (RSAPSO) technique to find global minima more efficiently and robustly. The proposed RSAPSO combines the global search ability of PSO and the local search ability of RSA, and offsets the weaknesses of each other. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other reported algorithms.

scholarly journals Particle swarm optimization with constriction factor for optimal reactive power dispatch

2013 ◽  
Vol 16 (2) ◽  
pp. 89-101
Author(s):  
Dieu Ngoc Vo ◽  
Dung Anh Le ◽  
Tu Phan Vu
Keyword(s):  
Particle Swarm Optimization ◽  
Voltage Stability ◽  
Reactive Power ◽  
Particle Swarm ◽  
Total Power ◽  
Swarm Optimization ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Reactive Power Dispatch ◽  
Constriction Factor

This paper proposes a simple particle swarm optimization with constriction factor (PSO-CF) method for solving optimal reactive power dispatch (ORPD) problem. The proposed PSO-CF is the conventional particle swarm optimization based on constriction factor which can deal with different objectives of the problem such as minimizing the real power losses, improving the voltage profile, and enhancing the voltage stability and properly handle various constraints for reactive power limits of generators and switchable capacitor banks, bus voltage limits, tap changer limits for transformers, and transmission line limits. The proposed method has been tested on the IEEE 30-bus and IEEE 118-bus systems and the obtained results are compared to those from other PSO variants and other methods in the literature. The result comparison has shown that the proposed method can obtain total power loss, voltage deviation or voltage stability index less than the others for the considered cases. Therefore, the proposed PSO-CF can be favorable solving the ORPD problem.

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