On determining optimal number and layout of wind turbines using space decomposed cost-energy trade-off algorithm

Mittal, Prateek and Mitra, Kishalay (2018) On determining optimal number and layout of wind turbines using space decomposed cost-energy trade-off algorithm. In: Indian Control Conference (ICC), 4-6 January 2017, Kanpur.

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Continuous depletion of conventional sources of energy has arisen the need of renewable sources of energy and wind energy is one of the most promising alternative sources in this regard. Wind turbines are utilized to harness wind energy. However, finding the optimal layout (numbers and positions) of wind turbines inside a wind farm is a challenging task as velocity deficits caused by wake effects have to be minimized. In this study, using a linear wake model, a wind farm layout optimization has been carried out with the aim of maximization of energy and the minimization of the investment cost. A novel space decomposition approach is proposed to solve the cost-energy multi-objective optimization problem to determine the optimal layout of turbines. An indexed form of Binary - real coded Non-dominated sorting genetic algorithm, termed as i-NSGA II, has been proposed. The proposed approach is first validated with the rigorously explored literature case study and applied further on a realistic wind farm data. It has been found that the proposed method is able to provide ~133 % increase in power produced and ~14% improvement in cost-energy ratio as compared to the benchmark case study. Besides, ~5% improvement in the cost-energy ratio is also observed as compared to the other reported works. Moreover, in contrast to previous studies, the generated Pareto optimal front (PO) allows a decision maker to choose among various layouts of turbines instead of a single solution.

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IITH Creators:
IITH CreatorsORCiD
Mitra, Kishalayhttp://orcid.org/0000-0001-5660-6878
Item Type: Conference or Workshop Item (Paper)
Subjects: Chemical Engineering
Divisions: Department of Chemical Engineering
Depositing User: Team Library
Date Deposited: 13 Aug 2018 11:05
Last Modified: 13 Aug 2018 11:05
URI: http://raiith.iith.ac.in/id/eprint/4389
Publisher URL: http://doi.org/10.1109/INDIANCC.2018.8307969
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