Next Article in Journal
Discrete Indoor Three-Dimensional Localization System Based on Neural Networks Using Visible Light Communication
Next Article in Special Issue
Micro-Capillary Coatings Based on Spiropyran Polymeric Brushes for Metal Ion Binding, Detection, and Release in Continuous Flow
Previous Article in Journal
The Height-Adaptive Parameterized Step Length Measurement Method and Experiment Based on Motion Parameters
Previous Article in Special Issue
Printing and Folding: A Solution for High-Throughput Processing of Organic Thin-Film Thermoelectric Devices

Sensor-Based Optimized Control of the Full Load Instability in Large Hydraulic Turbines

Center for Industrial Diagnostics and Fluid Dynamics (CDIF), Polytechnic University of Catalonia (UPC), Av. Diagonal, 647, ETSEIB, 08028 Barcelona, Spain
Author to whom correspondence should be addressed.
Sensors 2018, 18(4), 1038;
Received: 28 February 2018 / Revised: 27 March 2018 / Accepted: 28 March 2018 / Published: 30 March 2018
(This article belongs to the Special Issue I3S 2017 Selected Papers)
Hydropower plants are of paramount importance for the integration of intermittent renewable energy sources in the power grid. In order to match the energy generated and consumed, Large hydraulic turbines have to work under off-design conditions, which may lead to dangerous unstable operating points involving the hydraulic, mechanical and electrical system. Under these conditions, the stability of the grid and the safety of the power plant itself can be compromised. For many Francis Turbines one of these critical points, that usually limits the maximum output power, is the full load instability. Therefore, these machines usually work far away from this unstable point, reducing the effective operating range of the unit. In order to extend the operating range of the machine, working closer to this point with a reasonable safety margin, it is of paramount importance to monitor and to control relevant parameters of the unit, which have to be obtained with an accurate sensor acquisition strategy. Within the framework of a large EU project, field tests in a large Francis Turbine located in Canada (rated power of 444 MW) have been performed. Many different sensors were used to monitor several working parameters of the unit for all its operating range. Particularly for these tests, more than 80 signals, including ten type of different sensors and several operating signals that define the operating point of the unit, were simultaneously acquired. The present study, focuses on the optimization of the acquisition strategy, which includes type, number, location, acquisition frequency of the sensors and corresponding signal analysis to detect the full load instability and to prevent the unit from reaching this point. A systematic approach to determine this strategy has been followed. It has been found that some indicators obtained with different types of sensors are linearly correlated with the oscillating power. The optimized strategy has been determined based on the correlation characteristics (linearity, sensitivity and reactivity), the simplicity of the installation and the acquisition frequency necessary. Finally, an economic and easy implementable protection system based on the resulting optimized acquisition strategy is proposed. This system, which can be used in a generic Francis turbine with a similar full load instability, permits one to extend the operating range of the unit by working close to the instability with a reasonable safety margin. View Full-Text
Keywords: hydraulic turbine; dynamic behavior; physical sensors hydraulic turbine; dynamic behavior; physical sensors
Show Figures

Figure 1

MDPI and ACS Style

Presas, A.; Valentin, D.; Egusquiza, M.; Valero, C.; Egusquiza, E. Sensor-Based Optimized Control of the Full Load Instability in Large Hydraulic Turbines. Sensors 2018, 18, 1038.

AMA Style

Presas A, Valentin D, Egusquiza M, Valero C, Egusquiza E. Sensor-Based Optimized Control of the Full Load Instability in Large Hydraulic Turbines. Sensors. 2018; 18(4):1038.

Chicago/Turabian Style

Presas, Alexandre, David Valentin, Mònica Egusquiza, Carme Valero, and Eduard Egusquiza. 2018. "Sensor-Based Optimized Control of the Full Load Instability in Large Hydraulic Turbines" Sensors 18, no. 4: 1038.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop