利用粒子族群演算法研究風車陣列之最佳間距; Particle Swarm Optimization was used to study the optimal spacing of wind turbine array.

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Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/1275

Title:	利用粒子族群演算法研究風車陣列之最佳間距;Particle Swarm Optimization was used to study the optimal spacing of wind turbine array.
Authors:	許靜宜;Jinyi Hsu
Contributors:	土木工程研究所
Keywords:	粒子族群演算法;最佳化間距;風機尾流;風力發電廠;wind farm;turbine wake;optimal spacing;particle swarm optimization
Date:	2008-07-16
Issue Date:	2009-09-18 17:25:33 (UTC+8)
Publisher:	國立中央大學圖書館
Abstract:	大型的風力發電廠(Wind Farm)因為風機尾流的緣故，風機排列的方式會影響其總發電量。本研究利用粒子族群演算法(Particle Swarm Optimization, PSO)來研究風力發電廠的風機排列之最佳化間距。研究設定在一個有限的區域範圍內，風機的排列方式呈現規則的陣列型態，分別利用風機尾流風速公式與尾流發電量公式計算風機在不同的排列間距─前後向間距與側向間距的排列情境下，風機陣列的發電效益。本研究探討在不同的風場條件下，比較不同的發電量計算方式與目標函數對於風車陣列最佳間距的影響。研究結果顯示出，風車陣列的間距除了受到風向的影響外，另外在考量風機設置成本的因素下，不同的目標函數所得到的優化結果也有很大的差異。 The spacing between wind turbines in a wind farm could influence the total power output of the wind farm. In this study, Particle Swarm Optimization (PSO) was used to study the optimal spacing (both streamwise and lateral spacing) of wind turbine array. The power output of downstream wind turbines were calculated by two different methods - mean wind speed method and wake power curve method. Under different wind directions, the optimal spacing found by the PSO were compared and analyzed. The results show that the optimal spacing of wind turbines was not only influenced by the objective function of optimization, but also the calculation method of power output.
Appears in Collections:	[Graduate Institute of Civil Engineering] Electronic Thesis & Dissertation

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