Rapid reserve generation from a Francis Turbine for system frequency control
Giosio, DR and Henderson, AD and Walker, JM and Brandner, PA, Rapid reserve generation from a Francis Turbine for system frequency control, Energies, 10, (4) Article 496. ISSN 1996-1073 (2017) [Refereed Article]
The increase in contributions from non base load renewables, such as wind and solar, can have adverse effects on the stability of an electrical grid. In this study, the possibility of rapidly loading a Francis turbine from a tail water depression (TWD) mode for providing additional system frequency control is investigated. Based on the analysis of full-scale TWD test results and key findings from the transient testing of a micro-hydro scale turbine unit, a detailed description of the TWD transition process is given. The formulation of an improved turbine model for use in one-dimensional hydro-electric plant models is presented with simulation results compared to full-scale data. The analytical model, which calculates output power according to the conservation of angular momentum and identified sources of loss, is used in parallel with full-scale and model scale test observations to elucidate the events and mechanisms occurring during this proposed transition. The output response, in terms of active power, was found to be highly dependent on guide vane opening rate in both full-scale and model tests. For an approximate doubling in opening rate, the duration of the reverse power flow was reduced by 38% and 21%, for full-scale and model units, while the low pressure transient increased by 16% and 8%, respectively. The analytical model was shown to capture the general response characteristic in all cases tested; however, output power response was over predicted due to two identified model assumptions made, while, for the more rapid opening, the penstock pressure was under predicted by approximately 15%.
hydro-electric power generation, power system dynamics, hydraulic turbine, Francis Turbine, rapid start-up, transient operation, dynamic simulation model