scholarly journals Passerine swarm optimization algorithm for solving optimal reactive power dispatch problem

2020 ◽  
Vol 9 (2) ◽  
pp. 101
Author(s):  
Lenin Kanagasabai
Keyword(s):  
Optimization Algorithm ◽  
Power Loss ◽  
Reactive Power ◽  
Passerine Bird ◽  
Swarm Optimization ◽  
Real Power ◽  
The Real ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Reactive Power Dispatch

<span>This paper presents Passerine Swarm Optimization Algorithm (PSOA) for solving optimal reactive power dispatch problem. This algorithm is based on behaviour of social communications of Passerine bird. Basically, Passerine bird has three common behaviours: search behaviour, adherence behaviour and expedition behaviour. Through the shared communications Passerine bird will search for the food and also run away from hunters. By using the Passerine bird communications and behaviour, five basic rules have been created in the PSOA approach to solve the optimal reactive power dispatch problem. Key aspect is to reduce the real power loss and also to keep the variables within the limits. Proposed Passerine Swarm Optimization Algorithm (PSOA) has been tested in standard IEEE 30 bus test system and simulations results reveal about the better performance of the proposed algorithm in reducing the real power loss and enhancing the static voltage stability margin</span>

scholarly journals IMPROVED BABOON ALGORITHM FOR MINIMIZATION OF REAL POWER LOSS

2017 ◽  
Vol 5 (1) ◽  
pp. 33-42
Author(s):  
K. Lenin ◽  
B.Ravindhranath Reddy ◽  
M.Surya Kalavathi
Keyword(s):  
Power Loss ◽  
Reactive Power ◽  
Real Power ◽  
The Real ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Reactive Power Dispatch ◽  
Simulation Results ◽  
Better Than ◽  
Bus System

This paper projects Improved Baboon Algorithm (IBA) for solving the Reactive Power dispatch problem. The key feature in this problem is reduction of real power loss and to keep voltage profiles within limits. This algorithm is inspired from the tree climbing procedures of Baboons, where the Baboons look for the highest tree by climbing up from their positions. The simulation results expose amended performance of the IBA in solving an optimal reactive power dispatch problem. In order to evaluate up the performance of the proposed algorithm, it has been tested on Standard IEEE 30 bus system and compared to other stated algorithms. Simulation results show that IBA is better than other algorithms in reducing the real power loss and voltage profiles also within the limits.

scholarly journals AMENDED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR REAL POWER LOSS REDUCTION AND STATIC VOLTAGE STABILITY MARGIN INDEX ENHANCEMENT

2018 ◽  
Vol 6 (2) ◽  
pp. 146-156
Author(s):  
K. Lenin
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Reactive Power ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Power Loss Reduction ◽  
Reactive Power Dispatch

In this paper, Amended Particle Swarm Optimization Algorithm (APSOA) is proposed with the combination of Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) for solving the optimal reactive power dispatch Problem. PSO is one of the most widely used evolutionary algorithms in hybrid methods due to its simplicity, convergence speed, an ability of searching Global optimum. GSA has many advantages such as, adaptive learning rate, memory-less algorithm and, good and fast convergence. Proposed hybridized algorithm is aimed at reduce the probability of trapping in local optimum. In order to assess the efficiency of proposed algorithm, it has been tested on Standard IEEE 30 system and compared to other standard algorithms. The simulation results demonstrate worthy performance of the Amended Particle Swarm Optimization Algorithm (APSOA) in solving optimal reactive power dispatch problem.

scholarly journals CROWDING DISTANCE BASED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR SOLVING OPTIMAL REACTIVE POWER DISPATCH PROBLEM

2018 ◽  
Vol 6 (6) ◽  
pp. 226-237
Author(s):  
K. Lenin
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Reactive Power ◽  
Particle Swarm ◽  
Test System ◽  
Swarm Optimization ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Crowding Distance ◽  
Reactive Power Dispatch

In this paper, Crowding Distance based Particle Swarm Optimization (CDPSO) algorithm has been proposed to solve the optimal reactive power dispatch problem. Particle Swarm Optimization (PSO) is swarm intelligence-based exploration and optimization algorithm which is used to solve global optimization problems. In PSO, the population is referred as a swarm and the individuals are called particles. Like other evolutionary algorithms, PSO performs searches using a population of individuals that are updated from iteration to iteration. The crowding distance is introduced as the index to judge the distance between the particle and the adjacent particle, and it reflects the congestion degree of no dominated solutions. In the population, the larger the crowding distance, the sparser and more uniform. In the feasible solution space, we uniformly and randomly initialize the particle swarms and select the no dominated solution particles consisting of the elite set. After that by the methods of congestion degree choosing (the congestion degree can make the particles distribution more sparse) and the dynamic e infeasibility dominating the constraints, we remove the no dominated particles in the elite set. Then, the objectives can be approximated. Proposed crowding distance based Particle Swarm Optimization (CDPSO) algorithm has been tested in standard IEEE 30 bus test system and simulation results shows clearly the improved performance of the projected algorithm in reducing the real power loss and static voltage stability margin has been enhanced.

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