SCADA Data-Based Working Condition Classification for Condition Assessment of Wind Turbine Main Transmission System

Abstract

Due to the complex and variable conditions under which wind turbines operate, existing working condition classification methods are inadequate for condition assessment of the main transmission system. Because working conditions are too few after classification, it cannot effectively describe the complex and variable working conditions of wind turbine. This can lead to high false-alarm rates in the condition monitoring, which affect normal operations. This paper proposes a working condition classification method for the main transmission system of wind turbines based on supervisory control and data acquisition (SCADA) data. Firstly, correlation analysis of SCADA data acquired by wind farm is used to select the parameters relevant to the main transmission system. Secondly, according to the wind turbine control principle, the working conditions are initially divided into four phases: shutdown, start-up, maximum wind energy tracking, and constant speed. The k-means clustering algorithm is used to subdivide the maximum wind energy-tracking phase and constant speed phase, which account for a larger proportion of the working conditions, to achieve better classification. Finally, a case study is used to demonstrate the calculation of alarm thresholds and alarm rates for each working condition. The results are compared with the direct use of k-means clustering for working condition classification. It is concluded that the proposed method can significantly reduce the false-alarm rate of the vibration detection process.

Smart Energy Management System: Design of a Monitoring and Peak Load Forecasting System for an Experimental Open-Pit Mine

“…The smart energy management system (SEMS), as shown in Figure 1, is a dataflow of energy consumption, generation data, between SCADA, SCADA back up for redundancy, the database, and the supervision dashboard, which shows the forecasted and predicted energy profile and demand response of the different components of the open-pit mine electrical grid. It detects all anomalous equipment and its placement using a geographical information system for easy and direct maintenance [4]. mine electrical grid.…”

“…mine electrical grid. It detects all anomalous equipment and its placement using a geographical information system for easy and direct maintenance [4].…”

“…The open-pit mine was designed in the first place for production regardless of energy consumption or grid quality predictive maintenance. So, to overcome this challenge, new hardware was installed in parallel with the existent infrastructure, including smart meters, programmable logic controllers and servers [4]. The developed communication and data recording program was tested and validated through the prototype before implementing it in the open-pit mine.…”

“…The maintenance technicians use a curative and preventive maintenance system. The supervisory control and data acquisition (SCADA) was completely oriented to process machining supervision and production key performance indicators [4]. The goal of this study is to redesign the control system and integrate the energy and electrical grid data by giving insights and predictions.…”

Dynamic behavior analysis method for the normal and faulty drivetrain of wind turbine under multi‐working conditions

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