Name
Abstract | ||
|---|---|---|
Wind farms (WFs) are important components of smart grid. The modeling and optimal planning of the WF is preliminary before its construction. In this article, a bi-level multi-objective optimization framework is presented, with the aim of simultaneously designing the configuration of wind turbines (WTs) as well as the topology of electrical collector system in an offshore WF. The installation capacity of the WF, the positioning of the WTs and the planning scheme of the electrical system are balanced to achieve a better performance of the WF. In this proposal, there is an outer layer along with two inner layers. The objectives of the outer-layer model are the maximization of the WF's daily profit rate, the daily average capacity factor, and power quality. It is tackled by the Non-dominated Sorting Genetic Algorithm-III (NSGA-III). The objectives of the two inner layer models are to determine the topology of the electrical system and the generation schedule of other generators, and are solved by means of the Binary Particle Swarm Optimization (BPSO) algorithm and the quadratic programming (QP) method respectively. The WF is assumed to be connected to the IEEE-24 bus test system. The simulation results validate the adaptability and effectiveness of the proposed approach with the main factors that affect the WF layout being analyzed. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TSG.2020.3022378 | IEEE Transactions on Smart Grid |
Keywords | DocType | Volume |
Multi-objective optimization,bi-level programming,wind turbine micro-siting,optimal cabling | Journal | 12 |
Issue | ISSN | Citations |
1 | 1949-3053 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Siyu Tao | 1 | 0 | 0.68 |
| Qingshan Xu | 2 | 1 | 2.75 |
| Andrés Feijóo | 3 | 1 | 1.37 |
| Gang Zheng | 4 | 109 | 19.51 |