Modeling and Scheduling of a Controllable Electrolyser in an Industrial Grid

Master thesis (2019)

Authors

R.F.P. Bentvelsen Electrical Engineering, Mathematics and Computer Science

Contributors

M. Cvetkovic Intelligent Electrical Power Grids - EEMCS (mentor)
P. Palensky Intelligent Electrical Power Grids - EEMCS (graduation committee member)
G.R. Chandra Mouli DC systems, Energy conversion & Storage - EEMCS (graduation committee member)
D. Gusain Intelligent Electrical Power Grids - EEMCS (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2019 Ron Bentvelsen
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Published Date

01-07-2019

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Natural gas has been a significant source of energy for the Netherlands for a long time, but due to developments such as climate change awareness and increased seismic activity in the Groningen area, the Dutch Government has decided to shift away from natural gas and look for alternatives. Hydrogen gas is such a contender, as it can partly use the existing natural gas pipeline infrastructure, is feasible for long-term energy storage and emits no greenhouse gasses. By utilizing green electricity from renewable energy sources, water electrolysis can be applied to produce hydrogen gas. In this thesis, the integration of a large-scale electrolyser within an industrial grid is proposed. The industrial grid consists of a 15-bus medium voltage grid with numerous industrious loads, two wind farms and a power exchange with the transmission grid. A 10MW Proton-Exchange Membrane electrolyser is coupled with a 18 MW wind farm with the aim to produce green hydrogen in a cost-effective manner, while also providing power scheduling and balancing. Load demand depends on the available wind power over the long-term, while also mitigating fluctuations due to intermittent renewable power production. The economic feasibility of the large-scale electrolyser is analysed as well.
OpenModelica is used to model the industrial grid with PSAT components, based on a CIGRE benchmark system for renewable technologies. A mathematical model is implemented to simulate the electrochemical process of water electrolysis, and a rule-based controller is designed and implemented with a smart control strategy to control the load demand of the electrolyser. The power demand is determined by various input data such as wind forecast, intraday market prices and real-time wind power. The results showcases an effective integration of a large-scale electrolyser that can adapt to changing wind power patterns to provide a stable power flow to the industrial grid. The economic analysis shows a cost price of hydrogen to be in the range of "50.99-90.65/MWh, which is still significant higher compared to natural gas prices.