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...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | |
| التنسيق: | article |
| منشور في: |
2004
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://eprints.kfupm.edu.sa/id/eprint/14605/1/14605_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14605/2/14605_2.doc |
| الوسوم: |
إضافة وسم
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| الملخص: | 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. |
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