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دانلود رایکان مقاله انگلیسی ISI با موضوع بهینه سازی طرح باد مزرعه با استفاده از الگوریتم ژنتیک با ارتفاع هاب متفاوت توربین های بادی

عنوان فارسی مقاله:

بهینه سازی طرح باد مزرعه با استفاده از الگوریتم ژنتیک با ارتفاع هاب متفاوت توربین های بادی

عنوان انگلیسی مقاله:

Wind farm layout optimization using genetic algorithm with different hub height wind turbines

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بخشی از مقاله انگلیسی :

4. Case studies with results and discussion

Due to the limitation of computing capacity, we decide the given wind farm’s size as 500 m 500 m, which is further divided into 400 cells with a cell size of 25 m 25 m as shown in Fig. 3. Although this cell size is not as small as 1 m 1 m cell size used in Refs. [15,21], it should be good enough to provide sufficient potential locations for wind turbines. Instead of locating wind turbines into the center of each cell, we decide to place all wind turbines at the intersection points in the grid (shown in Fig. 3) within the area of the given wind farm. Considering the size of tower foundation, the available positions will not include those intersect ion points at four edges. For example, the intersect ion point (25, 25) is a potential position, but (0, 25) is not a potential position. Therefore, there are 361 potential positions available in this small wind farm, which means n is equal to 361 in Table 2. However , according to the closest distance constraint, the actual number of wind turbines that can be placed in this wind farm will be less than 361. To allow larger turbine spacing, the closest distance between any two turbines is set as 100 m considering the turbine hub height and rotor radius used in this paper. However, a higher value may be used in practice, such as 4 or 5 times of rotor diameter.