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https://doi.org/10.1088/1755-1315/40/1/012037
Title: | Wind farm micro-siting optimization using novel cell membrane approach | Authors: | Huang, W Che, W.X Tan, R.S Li, M.X Liu, Q |
Keywords: | Cytology Electric utilities Wakes Wind power Constant speed Gene algorithms Local optimal solution Micro-siting Variable speed Velocity deficits Wind farm micro-siting Wind resources Wind turbines algorithm experimental study membrane operations technology optimization velocity structure wake wind farm wind turbine |
Issue Date: | 2016 | Citation: | Huang, W, Che, W.X, Tan, R.S, Li, M.X, Liu, Q (2016). Wind farm micro-siting optimization using novel cell membrane approach. IOP Conference Series: Earth and Environmental Science 40 (1) : 12037. ScholarBank@NUS Repository. https://doi.org/10.1088/1755-1315/40/1/012037 | Rights: | Attribution 4.0 International | Abstract: | Micro-siting aims to determine every wind turbine's position to reduce velocity deficits caused by the wake effect. The Novel CMO (cell membrane optimization) approach is proposed to overcome this weakness. It plays a vital role to utilize more wind resources while the type of wind turbine and the area to build a wind farm have been determined. The work is based on the Jensen wake model, and the hypothetical situations are the same as those used by the former researchers. There are three wind cases: constant speed with one direction, constant speed with variable directions and variable speeds with variable directions. The area of wind farm is assumed to be a plane 2km×2km square. The numbers of the wind turbines is 26, 19 and 15 in three cases respectively. Compared with Gene Algorithm introduced by G. Mosetti, CMO's results are acceptable and the velocity deficit is smaller, which results from that CMO's variables is continuous and can make the most of the area the wind turbines can be placed. Moreover, it performs well to avoid the local optimal solutions by dividing the searching particles into different types which move according to different rules. © Published under licence by IOP Publishing Ltd. | Source Title: | IOP Conference Series: Earth and Environmental Science | URI: | https://scholarbank.nus.edu.sg/handle/10635/179910 | ISSN: | 17551307 | DOI: | 10.1088/1755-1315/40/1/012037 | Rights: | Attribution 4.0 International |
Appears in Collections: | Staff Publications Elements |
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