離岸風場最佳化佈局之研究

因為近年來再生能源越來越被重視，加上大型風場的土地取得不易，離岸式風場的建置在世界上也漸趨流行。由於它的範圍可從幾平方公里沿伸到數十平方公里遠，所以風場內的風機和纜線要如何建置及規劃即為一個最重要的課題。本研究探討離岸風場在固定的風機台數與場址範圍下，風場內的風機之最佳化排列。並在風機建置完成後，執行風場的纜線配置。為了獲得最佳的風場建置方式，本文考慮風機間的尾流效應所造成之風能損耗，透過粒子群演算法和電荷搜尋演算法做風場最佳化排列。本文還使用兩種不同高度風機之最佳化排列和前述只使用一種高度風機的最佳化排列做比較，藉此可知道在風場中使用不同高度風機是否會減少尾流效應的影響。在線路配置上則使用蟻拓演算法做輻射型配線，K-means演算法做星型配線，並比較其差異。本論文使用台灣離岸實際的風速資料做模擬，期望對於未來規劃離岸式風場的建設公司能在系統規劃時有適當的參考目標。

關鍵字

尾流效應； K-means演算法；蟻拓演算法；電荷搜尋法；粒子群演算法；風場layout

並列摘要

In the recent, since it isn’t easy to obtain a big onshore wind farm and the valued of the renewable energy, the offshore wind farm is become more and more popular in the world. However, the range of offshore wind farms may outspread in the range of several to tens of kilometers, so how to contribute a wind farm layout and plan a transmission topology are the most important topics. This study investigate the optimal offshore wind farm layout in the condition of fix number of wind turbines and the range of site. And execution the connection of transmission lines when finishing the wind farm layout. In order to obtain a best wind farm layout, this thesis considered the wind decay of the wake effect, and use PSO and CSS algorithms to obtain the best wind farm layout. This thesis also compared the result of two different hub height wind turbines to the single hub height wind turbine, and we can know whether the efficiency of wake effect will be reduce or not. On the other hand, we used ACS and K-means to simulate transmission connection of the radial design and the star design, and compare the difference of them. This thesis utilized the actual wind data in Taiwan to simulate, expect that this study could be a reference to the planning offshore wind farm in the future.

並列關鍵字

K-means ； ants colony search ； charged search system ； particle swarm optimization ； wake effect ； wind farm layout

參考文獻

[1] L. Ekonomou, S. Lazarou, G.E. Chatzarakis and V. Vita, “Estimation of wind turbines optimal number and produced power in a wind farm using an artificial neural network model,” Simulation Modelling Practice and Theory, pp. 21-25, 2012.

[2] Markus Wagner, Jareth Day and Frank Neumann, “A fast and effective local search algorithm for optimizing the placement of wind turbines,” Renewable Energy, pp.64-70, 2013.

[3] S.D.O. Turner, D.A. Romero, P.Y. Zhang, C.H. Amon and T.C.Y. Chan, “A new mathematical programming approach to optimize wind farm layouts,” Renewable Energy, pp.674-680, 2014.

[5] M.X. Song, K. Chen, Z.Y. He and X. Zhang, “Bionic optimization for micro-siting of wind farm on complex terrain,” Renewable Energy, pp.551-557, 2013.

[6] Andrew Kusiak and Zhe Song, “Design of wind farm layout for maximum wind energy capture,” Renewable Energy, pp.685-694, 2010.

國際替代計量

離岸風場最佳化佈局之研究

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