- 學位論文
油浸式電力變壓器絕緣老化壽命估測
Estimation of oil-immersed power transformer insulation aging life
摘要
油浸式電力變壓器需承受長時間高電壓、大電流、運轉溫昇及電磁力、機械力等衝擊。發生故障容易造成大範圍用戶的停電及重大之損失，而且本身之價格也相當昂貴。維持電力變壓器的正常運轉，甚至進一步延長變壓器運轉壽命是相當重要的。良好的變壓器維護機制，並藉由試驗及診斷技術來評估變壓器老化程度，可以了解此變壓器目前狀態，並即時針對各個情況採取反應措施。 本論文主要針對變壓器絕緣油中之成份及相關資訊可用以評估絕緣紙老化壽命，該等成份或相關資訊包括：糠醛、氣體（CO2, CO）、負載量、最熱點溫度、水分、介質損失等因素，分別探討其與絕緣紙老化之關係。依據標準與文獻發現糠醛、水汽及油中最熱點溫度等對變壓器絕緣壽命估測有較好之診斷。接著提出常見之評估絕緣油老化壽命之方法，並比較各方法之差異。利用老化試驗得出之相關數據：糠醛值、一氧化碳、二氧化碳等影響因數，來量化變壓器的壽命損失。並以類神經網路為基礎，獲得各影響因數與變壓器老化之關連性。透過二輸入與四輸入變數評估模式，將變壓器老化年數，作為類神經網路的輸出，經過網路學習訓練完成後，利用已訓練完成之模式來估測變壓器老化壽命損失。
並列摘要
Oil-immersed power transformer needs to endure for an extended period of time high voltage, high current, temperature rise, and the impacts of electromagnetic and mechanical forces, and any malfunction may lead to large-scale power outages and other drastic losses. Oil-immersed power transformer is also highly expensive. It is therefore of crucial importance to keep the transformer in normal operation and to prolong its service life. Using effective maintenance mechanism and test-diagnostic techniques to measure the aging degree of a power transformer helps trace the current status of the power transformer and enables the operator to initiate proper responses to contingencies and irregularities. The study accordingly aims at measuring the aging life of insulation paper by examining the elements and related parameters in transformer oil. The relationships between aging of insulation paper and major elements of transformer oil, notably furan, dissolved gases (CO2, CO), loading, hot-spot, temperature, moisture, and dielectric loss, are analyzed. Based on the standard and literature review, furan, moisture, and hot-spot temperature of oil help provide better diagnostic results. The study then proceeds to examine the methods frequently used to evaluate the aging life of transformer oil and compare the differences between the various methods. Obtained figures related to major affecting factors like furan, CO2, and CO are adopted to quantify the life loss of power transformer. Artificial neural network (ANN) is further applied to identify and examine the correlations between the aging of power transformer and affecting factors. Using two- and four-input-variable assessment models, the study has the functions of transformer life loss served as the ANN outputs to facilitate network training. The trained model is then used to measure and forecast the life loss of aging power transformers.
參考文獻
延伸閱讀
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