Optimizing the number and locations of turbines in a wind farm addressing energy-noise trade-off: A hybrid approach

Mittal, P and Mitra, Kishalay and Kulkarni, K (2017) Optimizing the number and locations of turbines in a wind farm addressing energy-noise trade-off: A hybrid approach. Energy Conversion and Management, 132. pp. 147-160. ISSN 0196-8904

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Abstract

Micro-siting is an optimal way of placing turbines inside a wind farm while considering various design objectives and constraints. Using a well-established Jensen wake model and ISO-9613-2 noise calculation, this study performs a wind farm layout optimization based on a multi-objective trade-off between minimization of the noise propagation and maximization of the energy generation. A novel hybrid methodology is developed which is a combination of probabilistic real-binary coded multi-objective evolutionary algorithm and a newly proposed deterministic gradient based non-dominated normalized normal constraint method. Based on the Inverted Generational Distance metric, the performance of the proposed method is found to be better than the conventional normalized normal constraint method or the concerned evolutionary method alone. Moreover, in contrast to the previous studies, the generated non-dominated front is capable of providing a trade-off between various alternative energy-noise solutions, along with an additional information about the corresponding turbine numbers and their optimal location coordinates. As a result, the decision maker can choose from different competing wind turbine layouts based on existing noise and other standard regulations.

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IITH Creators:
IITH CreatorsORCiD
Mitra, Kishalayhttp://orcid.org/0000-0001-5660-6878
Item Type: Article
Uncontrolled Keywords: Wind; Optimization; Noise; Pareto; Classical; Evolutionary
Subjects: Chemical Engineering > Biochemical Engineering
Divisions: Department of Chemical Engineering
Depositing User: Team Library
Date Deposited: 24 Nov 2016 10:57
Last Modified: 10 Nov 2017 05:00
URI: http://raiith.iith.ac.in/id/eprint/2899
Publisher URL: https://doi.org/10.1016/j.enconman.2016.11.014
OA policy: http://www.sherpa.ac.uk/romeo/issn/0196-8904/
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