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頁籤選單縮合
題 名 | 配電系統無效電力之預測=Load Forecasting of Reactive Power in Distribution System |
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作 者 | 朱文成; 許超雲; 湯振興; 柯俊守; 邱清泉; 黃金選; 周思良; | 書刊名 | 台電工程月刊 |
卷 期 | 583 1997.03[民86.03] |
頁 次 | 頁80-94 |
分類號 | 448.115 |
關鍵詞 | 負載預算; 無效功率; 配電系統; 配電調度系統; 類神經網路; Load forecasting; Reactive power; Distribution system; DDS; Artificial neural network; |
語 文 | 中文(Chinese) |
中文摘要 | 電力工程界對無效功率的預測大多依照功率因數的經驗值,計算需要增購的電容 器數量。為了使日後預估的電容器補償量更為合理,更為準確,本計劃擬發展一套預測配電 系統無效功率的方法,作為日後採購電容器的參考。本計劃在兼顧使用者方便,收集資料最 少,充分反應當地配電系統的特性等因素的考量下,採用饋線或主變壓器當年的尖峰負載記 錄,輸入類神經網路予於訓練,再根據次年實功率成長的情形計算出增加的無效功率負載量 。對尖峰負載的預測,在步驟上異於傳統上以系統最高尖峰記錄作為預測的數據,本計劃擬 定的方法是自尖峰日晨間離峰時段開始以小時為單位使用△ P - △ Q 的關係逐步預測至尖 峰時段。 |
英文摘要 | Most of the Power engineers predicted reactive power in the light of experience value of power factor, and then computed necessary quantity of capacitors. In order to estimate quantity of capacitors in distribution system more reasonably and accurately, an applicable method to forecast reactive power was developed. Under the consideration of easy use, less data collection and load representation of local distribution system, the summer peak daily records of feeders or main transformers in this year, were input to artificial neural network to calculate the increased amount of reactive power according to the growth of real power in the next year. For peak-VAR prediction, an unconventional method using the hourly incremental relationship of real power and reactive power was adopted. |
本系統中英文摘要資訊取自各篇刊載內容。