Multiobjective optimal power flow using strength Pareto evolutionary algorithm
In this paper, a novel multiobjective evolutionary algorithm for optimal power flow (OPF) problem is presented. The OPF problem is formulated as a nonlinear constrained multiobjective optimization problem where the fuel cost and the voltage stability index are to be minimized simultaneously. A new s...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | article |
| Published: |
2004
|
| Subjects: | |
| Online Access: | https://eprints.kfupm.edu.sa/id/eprint/14605/1/14605_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14605/2/14605_2.doc |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | In this paper, a novel multiobjective evolutionary algorithm for optimal power flow (OPF) problem is presented. The OPF problem is formulated as a nonlinear constrained multiobjective optimization problem where the fuel cost and the voltage stability index are to be minimized simultaneously. A new strength Pareto evolutionary algorithm (SPEA) based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and non-commensurable objectives. A hierarchical clustering algorithm is imposed to provide the decision maker with a representative and manageable Pareto-optimal set. The results demonstrate the capabilities of the proposed approach to generate true and well-distributed Pareto-optimal nondominated solutions in one single run. The results also show the superiority of the proposed approach and confirm its potential to solve the multiobjective OPF problem. |
|---|