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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Carrano, E.G. Souza, B.B. Neto, O.M. Takahashi, R. |
| Copyright Year | 2008 |
| Description | Author affiliation: Centro Fed. de Educ., Tecnol. de Minas Gerais, Belo Horizonte (Carrano, E.G.) |
| Abstract | This work proposes an immune inspired memetic algorithm for the expansion planning of electric distribution systems. This algorithm is based on a clonal selection algorithm and a local search method which is built using network distance concepts abstracted from continuous spaces. The memetic algorithm is intended to find not only the optimal solution for the design conditions, but a whole set of viable solutions, that can be considered as alternatives under perturbed operation conditions. Those alternatives are used for handling with load evolution uncertainties, which are inherently related with long term evaluation of the distribution system. The post-optimization analysis of solutions has been made using a Monte Carlo simulation and a multiobjective sensitivity analysis, in order to estimate their robustness under perturbed load conditions. The results achieved by the proposed algorithm in a practical problem indicate that this method can be more suitable for designing distribution system under load evolution uncertainties. |
| Starting Page | 3252 |
| Ending Page | 3258 |
| File Size | 162374 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781424418220 |
| DOI | 10.1109/CEC.2008.4631238 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-06-01 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Uncertainty Algorithm design and analysis Evolutionary computation Evolution (biology) Optimization Robustness Load modeling |
| Content Type | Text |
| Resource Type | Article |
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