Impact of power supply fluctuation and part load operation on the efficiency of alkaline water electrolysis
收藏NIAID Data Ecosystem2026-03-14 收录
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This is the research data folder for the paper "Impact of power supply fluctuation and part load operation on the efficiency of alkaline electrolysis".
The current-voltage model data was obtained by conducting chronopotentiometry experiments on a lab-scale electrolyser. Available performance data were analysed and used for the commercial electrolysers. The large-signal dynamic model input variables were obtained by conducting Electrochemical Impedance Spectroscopy Experiments (EIS) on a lab-scale electrolyser. While commercial systems performance data were translated into electrochemical fundamentals on electrokinetics and ohmic resistance.
Abstract:
Contrary to traditional electrolysers which operate continuously at their nominal load, future alkaline electrolysers need to be able to operate over a wide load range due to the variability of renewable electricity supply. We have investigated how the residual ripples from thyristor-based power supplies are influenced by the operating load of the system, and how these ripples affect the efficiency of alkaline electrolysers. For this, a simulation tool was developed which combines a six-pulse bridge thyristor rectifier model with closed-loop current control and semi-empirical electrolysis models. The electrolysis models can simulate the potential response to both direct and high amplitude alternating currents for lab-scale and industrial electrolysers. The electrolysis model of the lab-scale electrolyser was validated with experiments with a square wave current input. The models show that without filters the ripples result in a total system efficiency loss of 1.2 – 2.5% at full load and of 5.6 – 10.6% at a part load of 20% depending on the type of electrolyser. The implementation of an optimized L-filter suppresses residual ripples and reduces the efficiency losses to 0.5% - 0.8% at full load and to 0.8 – 1.2% at the minimum load.
创建时间:
2023-01-11



