scholarly journals TAILORED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR SOLVING OPTIMAL REACTIVE POWER PROBLEM

2020 ◽  
Vol 5 (12) ◽  
pp. 246-255
Author(s):  
K. Lenin
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Membrane Computing ◽  
Particle Swarm Optimization Algorithm ◽  
Reactive Power ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Neighbourhood Search ◽  
A Cell ◽  
Power Problem

This paper presents Tailored Particle Swarm Optimization (TPSO) algorithm for solving optimal reactive power problem. Particle Swarm optimization algorithm based on Membrane Computing is proposed to solve the problem. Tailored Particle Swarm Optimization (TPSO) algorithm designed with the framework and rules of a cell-like P systems, and particle swarm optimization with the neighbourhood search.  In order to evaluate the efficiency of the proposed algorithm, it has been tested on standard IEEE 118 & practical 191 bus test systems and compared to other specified algorithms. Simulation results show that Tailored Particle Swarm Optimization (TPSO) algorithm is superior to other algorithms in reducing the real power loss.

scholarly journals Progressive Particle Swarm Optimization Algorithm for Solving Reactive Power Problem

2015 ◽  
Vol 1 (3) ◽  
pp. 125
Author(s):  
Kanagasabai Lenin ◽  
Bhumanapally Ravindhranath Reddy ◽  
Munagala Surya Kalavathi
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Reactive Power ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Test System ◽  
Position Vector ◽  
Swarm Optimization ◽  
Power Problem

In this paper a Progressive particle swarm optimization algorithm (PPS) is used to solve optimal reactive power problem. A Particle Swarm Optimization algorithm maintains a swarm of particles, where each particle has position vector and velocity vector which represents the potential solutions of the particles. These vectors are modernized from the information of global best (Gbest) and personal best (Pbest) of the swarm. All particles move in the search space to obtain optimal solution. In this paper a new concept is introduced of calculating the velocity of the particles with the help of Euclidian Distance conception. This new-fangled perception helps in finding whether the particle is closer to Pbest or Gbest and updates the velocity equation consequently. By this we plan to perk up the performance in terms of the optimal solution within a rational number of generations. The projected PPS has been tested on standard IEEE 30 bus test system and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss with control variables are within the limits.

scholarly journals ACTUAL POWER LOSS REDUCTION BY AUGMENTED PARTICLE SWARM OPTIMIZATION ALGORITHM

2018 ◽  
Vol 6 (9) ◽  
pp. 212-219
Author(s):  
K. Lenin
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Reactive Power ◽  
Particle Swarm ◽  
Bacterial Foraging Optimization ◽  
Swarm Optimization ◽  
Bacterial Foraging ◽  
Power Loss Reduction ◽  
Power Problem

This paper presents an advanced particle swarm optimization Algorithm for solving the reactive power problem in power system. Bacterial Foraging Optimization Algorithm (BFOA) has recently emerged as a very powerful technique for real parameter optimization. In order to overcome the delay in optimization and to further enhance the performance of BFO, this paper proposed a new hybrid algorithm combining the features of BFOA and Particle Swarm Optimization (PSO) called advanced bacterial foraging-oriented particle swarm optimization (ABFPSO) algorithm for solving reactive power problem. The simulation results demonstrate good performance of the ABFPSO in solving an optimal reactive power problem. In order to evaluate the proposed algorithm, it has been tested on IEEE 57 bus system and compared to other algorithms.

Reactive Power Compensation of Distribution Network Based on Immune and Particle Swarm Optimization Algorithm

2012 ◽  
Vol 229-231 ◽  
pp. 1030-1033
Author(s):  
Wei Cui ◽  
Lin Chuan Li ◽  
Lei Zhang ◽  
Qian Sun
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Reactive Power ◽  
Distribution Network ◽  
Particle Swarm ◽  
Reactive Power Compensation ◽  
Swarm Optimization ◽  
Operation Costs ◽  
Sweep Algorithm

The reactive power compensation optimization in distribution network has the important meaning in maintaining system voltage stability, decreasing network loss and reducing operation costs. In order to meet factual conditions, we assume the system operates in minimum, normal and maximum three load modes and the objective function of problem includes the costs of power loss and the dynamic reactive power compensation devices allocated. In this paper we use Artificial Immune Algorithm(AIA) and Particle Swarm Optimization Algorithm(PSO) to determine compensate nodes and use the back/forward sweep algorithm calculate load flows. After applied into 28-nodes system, the result demonstrates the method is feasible and effective.

Sign in / Sign up

Export Citation Format

Share Document