低碳電力工業物聯網於數位孿生 監控系統研製

Abstract

隨著淨零科技能源管理快速進展，數據的深度挖掘與綠能永續，已成為發展 電力工業物聯網之關鍵。然為了系統須能精準且即時地傳輸電力資訊、故障位置 與控制低碳電力運轉，須有賴於雲端與近端運算能力實現工業物聯網，感測通訊 整合系統數據，遠程監測及時運轉狀態，預測設備老化損壞。本論文建置一個電 力設備與感知通訊，結合數位化資訊擷取與監控平台，企圖展現物聯網技術、數 位化分析與資料建模的優勢，同時因應未來電網智慧化及狀態維護保養之需求， 新設計之電力能源管理系統，應於場域加入智慧型監控模組，以監測溫度、含水 量、排碳量與電力資訊，亦可成為預防性維護解決方案，提供數據化監測、自動 化控制，以達到最佳化維護週期，預防保養建議及預期設備壽命評估。

With the rapid advancement of net zero technology and energy management, the deeply data mining and the pursuit of green sustainability have become key factors in the development of the power industry's Internet of Things (IIOT). However, to achieve accurate and real-time transmission of power information, fault locations, and lowcarbon power operation, its emphasis lies in cloud and edge computing power to realize the IIOT, which involves sensor communication systems, remote monitoring and control real-time operation, and predictive maintenance for aging equipment. This research establishes a supervisory control and data acquisition (SCADA) integrated power transmission and communication platform. With the increasing usage of IIOT technology, digital analysis, and data mining, the advantages of the issue serve as the basis for digital twin processing-oriented research. Additionally, in response to smart grid and condition-based maintenance (CBM), an energy management system should incorporate an intelligent monitoring module into the field. Meanwhile, it can also serve as a proactive maintenance solution. It provides automated control to achieve optimized maintenance recommendations and the expected equipment lifespan based on its operational status.