以基因演算法進行多目標模糊參數之被動式濾波器規劃

Multi-Objective Passive Filter Planning with Fuzzy Parameters Using Genetic Algorithms

黃偉芬(Wei-Feng Huang)

指導教授 ： 洪穎怡

中原大學/工學院/電機工程研究所/碩士(2001年)

https://doi.org/10.6840/cycu200100015

摘要

由於工業配電中，諧波污染電力品質的問題日趨嚴重，現有許多研究均在探討被動式濾波器之規劃，以抑制某些特定諧波流入配電系統中而污染系統或傷害設備。
本論文利用基因演算法及處罰函數之概念，並應用交談式模糊多目標非線性規劃法來設計濾波器，在將濾波器總成本極小化之同時，並且使得系統中因諧波所產生的電壓畸變降到最小，以有效地抑制配電系統中之諧波問題，其中更考慮系統負載及短路容量不確定性，而得到配電系統被動式濾波器規劃的新方法。
本文所提出配電系統被動式濾波器之規劃，是以一個18個匯流排電力系統進行測試，由模擬測試過程中找出最佳的運算參數設定值與各種測試情況之最佳解。由測試的結果顯示，本研究提出的方法實屬可行，並能使電力系統諧波問題獲得有效的改善。

關鍵詞：諧波、被動式濾波器、基因演算法、處罰函數、交談式模糊多目標非線性規劃法。

關鍵字

被動式濾波器 ； 交談式模糊多目標非線性規劃法 ； 基因演算法 ； 諧波

並列摘要

The power quality in the industry distribution system becomes deteriorated due to harmonic pollution. Many researches have been proposed for investigating the passive filter planning to reduce harmonic voltage distortions.
In this thesis, a new method based on the Genetic Algorithms and interactive decision making for multiobjective nonlinear programming problems with fuzzy parameters incorporated with the penalty functions to study the passive filter planning is proposed. The harmonic voltages and the filter cost are minimized while satisfying the harmonic standard and harmonic power plow equations. The uncertainty of the individual loads and the short circuit capacity is considered.
An 18-bus system is used as a test system for showing the applicability of the proposed method. The various parameters in Genetic Algorithms and various aspects of the results are also investigated for examining performance of the proposed method.

Key words: harmonic, passive filter, Genetic Algorithms, penalty function, interactive decision making, multiobjective NLP.

並列關鍵字

harmonic ； interactive decision making ； Genetic Algorithms ； multiobjective NLP ； passive filter

參考文獻

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