Name
Title | ||
|---|---|---|
Optimal Reactive Power Dispatch Using Particle Swarms Optimization Algorithm Based Pareto Optimal Set |
Abstract | ||
|---|---|---|
An improved particle swarms optimization algorithm based on Pareto Optimal set is proposed to optimize the reactive power in power system, which is a multiple objectives optimization problem. The proposed algorithm develops the new fitness assignment and random inertia weight strategy, problem-specific linkages can be learned by examining a randomly chosen collection of points in the search space, the improved algorithm also has the ability to avoid getting trapped in local optima due to prematurity, applying it to the calculation of the power systems of IEEE6-bus and IEEE14-bus, the calculation results prove its effectiveness. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-01513-7_17 | ISNN (3) |
Keywords | Field | DocType |
reactive power,pareto optimal set,multiple objective,calculation result,optimal reactive power dispatch,proposed algorithm,new fitness assignment,particle swarms optimization algorithm,improved particle swarm,improved algorithm,optimization problem,power system,search space | Mathematical optimization,Local optimum,Computer science,Meta-optimization,Electric power system,Multi-objective optimization,AC power,Multi-swarm optimization,Artificial intelligence,Inertia,Optimization problem,Machine learning | Conference |
Volume | ISSN | Citations |
5553 | 0302-9743 | 4 |
PageRank | References | Authors |
0.71 | 5 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yan Li | 1 | 330 | 19.85 |
| Pan-Pan Jing | 2 | 4 | 0.71 |
| De-Feng Hu | 3 | 4 | 0.71 |
| Bu-Han Zhang | 4 | 4 | 1.05 |
| Chengxiong Mao | 5 | 19 | 11.90 |
| Xinbo Ruan | 6 | 407 | 76.53 |
| Xiao-Yang Miao | 7 | 4 | 0.71 |
| De-Feng Chang | 8 | 4 | 0.71 |