運用免疫演算法於風力發電場之風力發電機最佳配置問題

Use of IA for the Wind Turbine Placement in the Large Wind Farm

林鈺如(Yu-Ru Lin)

指導教授 ： 陳大正

國立虎尾科技大學/管理學院/資訊管理研究所/碩士(2013年)

摘要

風力發電場(wind farm)之總發電量與效率會受其尾流效應(亦指上風處的風力渦輪機造成下風處產生尾流)的影響導致降低。因此本研究欲考量具總運轉成本、最低效率要求的條件限制，且具備風力渦輪機尾流效應的特性下，探討如何同時決定其風力渦輪機數目以及設置的位置，欲使特定風力發電場配置的風力渦輪機總發電量達到最大。本研究中將提出以免疫演算法解決上述困難，以求取最佳或近似最佳大型風力發電場之部署，並當其解非唯一時，能提供決策者有更多不同思維的決策制訂，如某一最佳方案風力渦輪機的部署太靠近居住區，而另一方案則比較遠離居住區，則決策者可選擇後者。預期此方法較其他傳統方法簡易，且所提出之方法應優於目前各種不同之文獻所提方法。

關鍵字

免疫演算法 ； 風力發電場 ； 風力渦輪機

並列摘要

Wind energy has gained great attentions because it is a renewable energy. It is able to diminish the people’s reliance on fossil fuel sources and the serious pollution impacts to the global environment. In this study, it is to investigate the resource constrained wind turbine placement problems in which the numbers of wind turbine and the corresponding locations on the wind farm are to be decided simultaneously so as to maximum the electronic power generated from all the wind turbines in a wind farm as well as to minimize the operating cost of all turbines. Moreover, the wake effects to the downstream turbines and the constraints including cost, efficiency are all considered in this research. In literature, only the allocation of a number of turbines was considered in this problem. However, resource constraints for turbines are never considered. The problem discussed in this work is more general model than that in the previous study so that the problems discussed in the literature become the special case in this study. Through this thesis, it is hoped to build up the mathematical model and then provide the best strategy to allocate the wind turbines optimally. In this study, a grid computing based artificial immune algorithm has been developed for overcoming the difficulties and finding the optimal solutions efficiently and effectively. Finally, the performance of the proposed methodology has been evaluated to show that the proposed approach is better than or equal to others in literature.

並列關鍵字

IA ； wind farm ； wind turbine

參考文獻

39.曹惠鈴，2007，“運用混合式進化演算法於法則探勘之回應模型”，國立虎尾科技大學資訊管理系，碩士論文。

37. 古志強，2004，“應用分散式類免疫演算法於多值域結構拓樸最佳化”，大同大學機械工程研究所，碩士論文。

40. 郭世勳，2008，“台灣地區離岸式風力發電成本效益分析”，國立臺北大學自然資源與環境管理研究所，碩士論文。

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