Abstract
In 2010, rivers in France provided 12 % of the country’s electricity. However, as locations for new hydraulic power plants are no longer plentiful, the efficiency of the existing ones has to be increased. The aim of the PENELOP2 project is to study the influence of different factors contributing to the disturbance of low-head turbine function, in order to develop ways in which to optimize sites and production methods and thus increase production rates. For the purposes of the project, it is planned to install a significant quantity of instrumentation (current meters, ADCP sensors, and ASFM) on a generating set at the Vaugris power station on the Rhône. Owned by CNR, the Vaugris plant is equipped with 4 bulb turbines supplied by Alstom in the 1970s. These have runner diameters of 6.25 m and deliver 18 MW each under 5.65 m net head. Data collected from Vaugris test sites will be used for calibrating and adjusting several different physical and numerical models. Although a normal study schedule foresees the calibration of numerical models in line with data recorded on site, local constraints have led to the development of an initial 3D numerical model that will allow flow to be determined, thus allowing equipment to be optimally positioned. In this case, it is therefore a matter of using the preliminary results to optimize the use of site data, to find the optimum location for placing equipment and to obtain the most coherent data possible to inform a posteriori calibration of the physical and numerical models.
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This work was carried as part of the PENELOP2 project approved by the Tenerrdis competitiveness cluster, with funding granted in the framework of the 9th Fonds Unique Interministériel (FUI) programme. The project partners are Alstom Power, CNR, Artelia, LEGI (Grenoble INP), In Vivo, Actoll, and JKL.
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© 2014 Springer Science+Business Media Singapore
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Schaguene, J. et al. (2014). Use of Numerical Modeling to Optimize the Placement of Data-Gathering Equipment in Low-Head Hydro Production Structures. In: Gourbesville, P., Cunge, J., Caignaert, G. (eds) Advances in Hydroinformatics. Springer Hydrogeology. Springer, Singapore. https://doi.org/10.1007/978-981-4451-42-0_24
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DOI: https://doi.org/10.1007/978-981-4451-42-0_24
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