Multi-objective transmission expansion planning based on Pareto dominance and neural networks

被引:0
作者
Miranda, Felipe L. [1 ]
Oliveira, Leonardo W. [1 ]
Oliveira, Edimar J. [1 ]
Nepomuceno, Erivelton G. [2 ]
Dias, Bruno H. [1 ]
机构
[1] Fed Univ Juiz de Fora UFJF, Dept Elect Energy, Juiz De Fora, MG, Brazil
[2] Maynooth Univ, Dept Elect Engn, Ctr Ocean Energy Res, Maynooth, Ireland
关键词
Transmission expansion planning; Multi-objective optimization; Reliability; Monte Carlo simulation; Neural network;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper presents an algorithm to solve the multi-objective transmission expansion planning (TEP) problem including the investment and reliability criteria. The reliability is considered by using the Expected energy not supplied (EENS) index. The main contribution consists on handling the reliability criterion in the optimization process, which tends to provide solutions with better trade-off between the mentioned criteria. For that purpose, a novel probabilistic algorithm called non-dominated Monte Carlo simulation (ND-MCS) is proposed to allow solving the multi-objective TEP problem with suitable computational effort and efficacy even considering the probabilistic feature of reliability in the optimization. In addition, a Support Vector Machine (SVM) network is applied embedded within the ND-MCS. The proposed methodology integrates the Pareto dominance method as a convergence criterion to MCS and a fuzzy criterion to support the decision making. The effectiveness of the proposed approach is tested in three systems, including a practical Brazilian network.
引用
收藏
页数:9
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