Abstract
Smooth integration of intermittent energy sources, such as solar and wind power, into the electrical grid induces new operating conditions of the hydraulic turbine by increasing the off-design operations, start/stops, and load variations. Therefore, hydraulic turbines are subject to unstable flow conditions and unfavorable load fluctuations. Predicting load fluctuations on the runner using indirect measurements can allow for optimized operations of the turbine units, increase turbine refurbishment time intervals, and avoid structural failures in extreme cases. This paper investigates an experimental methodology to assess and predict the flow condition and load fluctuations on a Kaplan turbine runner at several steady-state operations by performing measurements on the shaft in the rotating and stationary frame of references. This unit is instrumented with several transducers such as miniature pressure transducers, strain gages, and proximity probes. The results show that for any propeller curve of a Kaplan turbine, the guide vane opening corresponding to the minimum pressure and strain fluctuations on the runner blade can be obtained by axial, torsion, and bending measurements on the shaft. Torsion measurements on the shaft could support index-testing in Kaplan turbines particularly for updating the cam-curve during the unit operation. Furthermore, a signature of every phenomenon observed on the runner blade signals, e.g., runner frequency, rotating vortex rope components, and rotor-stator interaction, is found in the data obtained from the shaft.
Highlights
The significant increase in the installation of renewable power generation capacity continued globally over years and maintained more than 8% average growth in the previous five years to reach2588 GW in 2019 [1]
Experimental measurements were performed on a prototype Kaplan turbine at eleven steady-state operating points
The results of four pressure transducers installed on a runner blade pressure side (P-PS-2, P-PS3, P-PS-4, and P-PS-6), two strain gages close to the hub (S-SS-5R and S-SS-5T), and two strain gages close to the trailing edge (S-SS-6R and S-SS-6T), as well as axial, torsion, and bending measurements in two directions on the turbine shaft, and shaft displacement are presented
Summary
The significant increase in the installation of renewable power generation capacity continued globally over years and maintained more than 8% average growth in the previous five years to reach2588 GW in 2019 [1]. The significant increase in the installation of renewable power generation capacity continued globally over years and maintained more than 8% average growth in the previous five years to reach. On one hand, this share of intermittent energy sources directly influences the hydropower generation and demands more flexible operations of hydropower under transient operations to stabilize the electrical grid. Hydropower still provides most of the renewable electricity production in the world. Hydraulic turbines are considered as one of the key players in the electricity market that have to undergo increasing off-design operations with large load fluctuations. Condition monitoring and safe operation of hydraulic turbines are ensured with monitoring systems that actively monitor and protect the turbine’s health. Without a reliable health monitoring system, the turbine may encounter severe issues, and in a worst-case scenario, a catastrophic failure can occur. Condition monitoring can be used for life expectancy determination and cost estimation
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