利用超經驗人工蜂群演算法解決基於成本效益分析之風力發電場細部場址規劃問題

A Hyper-ABC Algorithm for Optimal Micro-Siting of Wind Farms Based on Cost-Benefit Analysis

李庚熹(Geng-Shi Li)

指導教授 ： 尹邦嚴

國立暨南國際大學/管理學院/資訊管理學系/碩士(2014年)

https://doi.org/10.6837/NCNU.2014.00201

摘要

近年來環保議題日益高漲，二氧化碳濃度的上升造成地球暖化，以至於氣候開始產生異常；石化能源的存量也日漸減少，也因為石化能源生成的時間過長，因此具有再生性的綠色能源逐漸被重視，例如太陽能、風力等。台灣近年來也逐漸發展風力發電產業，而本論文主題為探討一個風力發電場中，找出風機配置的最佳排列組合；
　　影響到風力發電的因子有很多，其中尤以尾流效應最為顯著，因此風場內並非建置越多風機，產出的效能越好。本論文透過混合多種次經驗法則(Meta Heuristic)，計算出尾流效應的影響、求出最佳排列組合，並與過去文獻探討比較。

關鍵字

次經驗演算法 ； 風力發電場 ； 風機 ； 尾流效應 ； 人工蜂群演算法

並列摘要

The ascending of carbon dioxide density is the main reason causing the global warming which occasionally results in extremely abnormal weather. Due to the decreasing capacity of fossil materials on earth, practitioners and researchers now pay more attentions on the renewable energy such as solar and wind power. Recent years, Taiwan government intrigued the development of wind power industry. This thesis is devoted to find the optimal placement of wind turbines in a wind farm.
　　There are many factors affecting the efficiency of wind power production. Among them, wake effect is the most significant. Therefore, the wind power production efficiency does not necessarily grows with the increasing number of installed wind turbines. This thesis applied a hyper-heuristic algorithm combining several metaheuristics to construct an optimal wind turbine placement considering wake effect influence. Finally, we compare our approach with existing works in the literature.

並列關鍵字

Metaheuristic ； Wind farm ； Wind turbine ； Wake effect ； ABC algorithm

參考文獻

1. Cowling, P., Kendall, G., & Soubeiga, E. (2001). A hyperheuristic approach to scheduling a sales summit Practice and Theory of Automated Timetabling III (pp. 176-190): Springer.

2. Dorigo, M., Maniezzo, V., & Colorni, A. (1996). Ant system: optimization by a colony of cooperating agents. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, 26(1), 29-41.

3. Eberhart, R. C., & Kennedy, J. (1995). A new optimizer using particle swarm theory. Paper presented at the Proceedings of the sixth international symposium on micro machine and human science.

4. Glover, F. (1989). Tabu search-part I. ORSA Journal on computing, 1(3), 190-206.

5. Gonzalez, J. S., Gonzalez Rodriguez, A. G., Mora, J. C., Santos, J. R., & Payan, M. B. (2010). Optimization of wind farm turbines layout using an evolutive algorithm. Renewable energy, 35(8), 1671-1681.