Author response for "Bio‐inspired hybrid BFOA‐PSO algorithm‐based reactive power controller in a standalone wind‐diesel power system"

2020 ◽  
Author(s):  
Raju Wagle ◽  
Pawan Sharma ◽  
Charu Sharma ◽  
Terje Gjengedal ◽  
Chittaranjan Pradhan
Keyword(s):  
Power System ◽  
Reactive Power ◽  
Pso Algorithm ◽  
Author Response ◽  
Power Controller

Research on the Reactive Power Optimization

2013 ◽  
Vol 385-386 ◽  
pp. 991-994
Author(s):  
Yan Yan Wang ◽  
Yan Song Li
Keyword(s):  
Power System ◽  
Reactive Power ◽  
Power Optimization ◽  
Low Voltage ◽  
Pso Algorithm ◽  
Reactive Power Optimization ◽  
Voltage Level ◽  
Line Network ◽  
Improved Pso

The power system is facing line losses, low voltage level and some other issues, this article begin with the point of the reactive power optimization, and through with the improved PSO algorithm, we find a way to reduce the line network loss.

Multi-Objective VAR Dispatch Using Particle Swarm Optimization

2005 ◽  
Vol 4 (1) ◽  
Author(s):  
Mr. S. Durairaj ◽  
Dr. P.S. Kannan ◽  
Dr. D. Devaraj
Keyword(s):  
Particle Swarm Optimization ◽  
Power System ◽  
Reactive Power ◽  
Optimization Technique ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Voltage Profile ◽  
Control Variables ◽  
Swarm Optimization ◽  
Voltage Stability Enhancement

Reactive Power Dispatch (RPD) is one of the important tasks in the operation and control of power system. The objective is to apply Particle Swarm Optimization (PSO) algorithm for arriving optimal settings of RPD problem control variables. Incorporation of PSO as a derivative free optimization technique in solving RPD problem significantly relieves the assumptions imposed on the optimized objective functions. The proposed algorithm has been applied to find the optimal reactive power control variables in IEEE 30-bus system and in a practical Indian power system with different objectives that reflect loss minimization, voltage profile improvement and voltage stability enhancement. The results of this approach have been compared with the results of Genetic Algorithm (GA). The results are promising and show the effectiveness and robustness of the proposed approach.

scholarly journals Optimal Management of Reactive Power Considering Voltage and Location of Control Devices Using Artificial Bee Algorithm

2021 ◽  
Vol 12 (1) ◽  
pp. 27
Author(s):  
Hassan Shokouhandeh ◽  
Sohaib Latif ◽  
Sadaf Irshad ◽  
Mehrdad Ahmadi Kamarposhti ◽  
Ilhami Colak ◽  
...  
Keyword(s):  
Power Systems ◽  
Power System ◽  
Artificial Bee Colony ◽  
Reactive Power ◽  
Optimization Problems ◽  
Pso Algorithm ◽  
Reactive Power Compensation ◽  
Voltage Profile ◽  
Bee Colony ◽  
Control Devices

Reactive power compensation is one of the practical tools that can be used to improve power systems and reduce costs. These benefits are achieved when the compensators are installed in a suitable place with optimal capacity. This study solves the issues of optimal supply and the purchase of reactive power in the IEEE 30-bus power system, especially when considering voltage stability and reducing total generation and operational costs, including generation costs, reserves, and the installation of reactive power control devices. The modified version of the artificial bee colony (MABC) algorithm is proposed to solve optimization problems and its results are compared with the artificial bee colony (ABC) algorithm, the particle swarm optimization (PSO) algorithm and the genetic algorithm (GA). The simulation results showed that the minimum losses in the power system requires further costs for reactive power compensation. Also, optimization results proved that the proposed MABC algorithm has a lower active power loss, reactive power costs, a better voltage profile and greater stability than the other three algorithms.

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