國立大專院校用電負載資料探勘研究——以交通大學為例

Initial Research of University Campus Electricity Meter Data Mining--A Case Study of National Chiao Tung University

劉立仁(Li-Ren Liu)

指導教授 ： 黃世昌

國立交通大學/工學院/土木工程系所/碩士(2019年)

摘要

找出電表數據中潛在的資訊會是理解館舍用電的開端，為了達成該目標，本研究收集了交通大學校園館舍的用電數據，並將之整理與視覺化來剖析館舍用電負載曲線，並分析館舍基本負載與館舍⻑期用電規律，以期找出使用者行為對於用電曲線之影響。
而尖峰負載一直都是供電端與用電端的共同問題，為了深入分析尖峰負載，本研究透過電費帳單分析校園整體用電概況、契約容量與最高需量，再從用電規模試證單一館舍尖峰負載與校園整體尖峰負載之關聯，並結合空間分類與巧合因子以及超約時間用電量來探討具有尖峰用電削峰潛力之館舍。

關鍵字

電表數據視覺化 ； 用電曲線 ； 基本負載 ； 使用者行為 ； 空間分類 ； 巧合因子 ； 尖峰用電削峰

並列摘要

Finding the hidden information in electricity meter data is the beginning of understanding electricity consumption of a building. To reach the goal, the electricity usage data of buildings in NCTU campus is collected in this study. In the hope of finding the influence of occupants’ behavior on electricity load curve, the data is organized and visualized to analyze building load curve, base load and long term pattern of electricity consumption.
Peak load has been a common problem between power supplier and consumer. To further interpret peak load, the general situation of campus energy usage, contract capacity and maximum demand are dissected. The connection between single-building peak load and campus peak load is examined from the aspect of magnitude. Through space classification, coincidence factor and energy usage in a specific time, buildings with peak load shaving potential are discovered.

並列關鍵字

data visualization ； electricity load curve ； base load ； Occupants' behavior ； space categorize ； coincidence factor ； peak load shaving

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