應用馬可夫模型與量子進化演算法求解配電系統無效電力控制

Reactive Power Control in Distribution System Using Markov Model and Quantum Evolutionary Algorithm

彭冠霖(Kuan-Lin Peng)

指導教授 ： 洪穎怡

中原大學/工學院/電機工程研究所/碩士(2009年)

https://doi.org/10.6840/cycu200901122

摘要

近年來分散式發電逐漸受到重視及採用，但因為風力發電的不穩定性，併入電力系統時會對於系統造成嚴重的電壓變動問題。
本論文首先應用量子進化演算法使系統的有效功率損失最小化及新增電容器組數最小化，滿足所有的運轉限制式。運用馬可夫模型求得風力機及負載狀態的變化，並將系統中風力機電壓、靜態電容器以及變壓器抽頭當作控制器去調整系統電壓之大小，針對不符合CBEMA電壓標準的電力潮流狀態進行研究分析。
透過17個匯流排配電系統以及25個匯流排澎湖電力系統分析模擬，証實本文所提出方法之可行性，且計算結果較基因演算法所得之結果更好。

關鍵字

馬可夫模型 ； 隨機變數 ； 無效功率補償 ； 分散式發電 ； 電壓變動 ； 電壓控制 ； 基因演算法 ； 間歇性 ； 量子進化演算法

並列摘要

Recently distributed generation has been used and paid much attention. Because generation of wind generation is intermittent, it will make seriously voltage fluctuated in the power system.
The proposed method based on quantum evolutionary algorithm is applied to minimize MW loss and new static compensator. The operational constraints are fulfilled. Markov model is used to attain the change of state of the wind generations and loads. The wind generator voltage, static compensator and transformer tap are considered to regulate the voltage profile in the distribution system for those power flows that do not meet the CBEMA voltage standard.
The applicability of proposed method is verified through simulation using a 17-bus system and an autonomous 25-bus (Penghu) system. The simulation result obtained by the proposed method is better than that obtained by genetic algorithms.

並列關鍵字

intermittent ； quantum evolutionary algorithm ； genetic algorithm ； reactive power and voltage control ； voltage fluctuation ； random variables ； distributed generation ； markov model

參考文獻

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