Wind farm layout optimization using particle filtering approach |
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| Affiliation: | 1. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;2. Department of Engineering, University of Cambridge, UK;1. Department of Industrial, Manufacturing, & Systems Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA;2. Neuroscience Statistics Research Lab, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA;3. The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA;4. Department of Mathematics, The University of Texas at Arlington, Arlington, TX 76019, USA;5. Department of Electrical Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA |
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| Abstract: | In this study, a particle filtering approach is used to get an optimized layout of a wind farm that has the minimum wake effects and maximum power generation. There are two main constraints of the problem, which are the wind farm boundary and the distance of any two turbines to each other. The constraints and wake effects of the wind turbines are integrated to the solution methodology. Particle filtering is a new approach and used to optimize the layout model of the problem with three different cases of the wind speed and its direction distribution of the windy site. Results show that the particle filtering approach can compete with ant colony and evolutionary strategy algorithms available in the literature. |
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