Wang, Yong and Liu, Hao and Long, Huan and Zhang, Zijun and Yang, Shengxiang (2018) Differential Evolution With a New Encoding Mechanism for Optimizing Wind Farm Layout. IEEE Transactions on Industrial Informatics, 14 (3). pp. 1040-1054. DOI https://doi.org/10.1109/TII.2017.2743761
Wang, Yong and Liu, Hao and Long, Huan and Zhang, Zijun and Yang, Shengxiang (2018) Differential Evolution With a New Encoding Mechanism for Optimizing Wind Farm Layout. IEEE Transactions on Industrial Informatics, 14 (3). pp. 1040-1054. DOI https://doi.org/10.1109/TII.2017.2743761
Wang, Yong and Liu, Hao and Long, Huan and Zhang, Zijun and Yang, Shengxiang (2018) Differential Evolution With a New Encoding Mechanism for Optimizing Wind Farm Layout. IEEE Transactions on Industrial Informatics, 14 (3). pp. 1040-1054. DOI https://doi.org/10.1109/TII.2017.2743761
Abstract
This paper presents a differential evolution algorithm with a new encoding mechanism for efficiently solving the optimal layout of the wind farm, with the aim of maximizing the power output. In the modeling of the wind farm, the wake effects among different wind turbines are considered and the Weibull distribution is employed to estimate the wind speed distribution. In the process of evolution, a new encoding mechanism for the locations of wind turbines is designed based on the characteristics of the wind farm layout. This encoding mechanism is the first attempt to treat the location of each wind turbine as an individual. As a result, the whole population represents a layout. Compared with the traditional encoding, the advantages of this encoding mechanism are twofold: 1) the dimension of the search space is reduced to two, and 2) a crucial parameter (i.e., the population size) is eliminated. In addition, differential evolution serves as the search engine and the caching technique is adopted to enhance the computational efficiency. The comparative analysis between the proposed method and seven other state-of-the-art methods is conducted based on two wind scenarios. The experimental results indicate that the proposed method is able to obtain the best overall performance, in terms of the power output and execution time.
Item Type: | Article |
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Uncontrolled Keywords: | Differential evolution (DE); encoding mechanism; optimization; wake effect; wind farm layout |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 26 Jun 2018 13:10 |
Last Modified: | 16 May 2024 19:20 |
URI: | http://repository.essex.ac.uk/id/eprint/21657 |
Available files
Filename: IEEE TII.pdf