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Industrial water electrolyzers mainly use old thyristor-based rectifiers to obtain the DC current required to run because of the low voltage level and high current requirements of the processes. These rectifiers cause significant ripple in the electrolyzer input current, leading to dynamic operation of the electrolyzer. Even though industrial-scale water electrolyzers are operated under such dynamic conditions, the effect on the electrolyzer performance is not well explored. In this study, current measurements from an industrial alkaline electrolyzer plant were used to define the common current ripple amplitude and frequency caused by the thyristor-based rectification. Based on the parameters obtained, laboratory measurements were conducted using an alkaline water electrolyzer to define the power losses incurred at various ripple amplitudes and frequencies. Additionally, the linearization of the electrolyzer current–voltage behavior as a function of frequency was studied using two electrode sets made of different materials. The laboratory measurements carried out in the study show that the ripple amplitude has a significant effect on increasing the losses, whereas the ripple frequency counteracts this. Thus, dynamic operation can have a large impact on losses, especially at partial loads, where the ripple current amplitudes increase significantly when using thyristor rectifiers. Lastly, the frequencies where the electrolyzer starts to behave linearly were observed to be at 68 Hz with the first electrode set and at 5 Hz with the second one. The considerable difference between the electrode sets indicates that the electrode materials and microstructure play a significant role in defining the electrolyzer frequency behavior. Because common thyristor-based power delivery systems operate at 300 Hz or 600 Hz, the results also imply that when modeling these systems, a linear model can be used for the electrolyzer to simplify the simulation. [Display omitted] • Large amplitude current ripple on alkaline electrolyzers is studied. • Ripple amplitude increases power losses, while frequency counteracts it. • As ripple frequency is increased, the electrolyzer starts to behave linearly. • The linear slope is determined purely based on the impedance. • At high frequencies, power usage can be determined from EIS measurement. [ABSTRACT FROM AUTHOR]

This paper proposes a parameter adjustable dynamic mass and energy balance simulation model for an industrial alkaline water electrolyzer plant that enables cost and energy efficiency optimization by means of system dimensioning and control. Thus, the simulation model is based on mathematical models and white box coding, and it uses a practicable number of fixed parameters. Zero-dimensional energy and mass balances of each unit operation of a 3 MW, and 16 bar plant process were solved in MATLAB functions connected via a Simulink environment. Verification of the model was accomplished using an analogous industrial plant of the same power and pressure range having the same operational systems design. The electrochemical, mass flow and thermal behavior of the simulation and the industrial plant were compared to ascertain the accuracy of the model and to enable modification and detailed representation of real case scenarios so that the model is suitable for use in future plant optimization studies. The thermal model dynamically predicted the real case with 98.7 % accuracy. Shunt currents were the main contributor to relative low Faraday efficiency of 86 % at nominal load and steady-state operation and heat loss to ambient from stack was only 2.6 % of the total power loss. [Display omitted] • Dynamic mass and energy balance simulation of a 3 MW industrial alkaline water electrolyzer. • Results are verified with measurements of an industrial plant. • Faraday efficiency at nominal operation was estimated at 86 %. • Contribution of each Faraday loss parameter was approximated. • 97 % of the stacks heat is extracted through the electrolyte circulation with heat exchangers. [ABSTRACT FROM AUTHOR]

The aim of this paper is to analyze through simulation how the energy efficiency of a single electrolysis stack at various loads is affected by shunt currents and to determine the energy-optimal load distribution between lines in a multiline electrolysis system under various magnitudes of shunt current losses. A dynamic energy and mass balance model of an industrial 3 MW , 16 bar alkaline water electrolyzer (AWE) process was developed using MATLAB. The optimization goal is to determine the power supply for each AWE line so that it can meet any hydrogen demand while minimizing the global specific energy consumption (SEC). The Particle Swarm Optimization (PSO) algorithm is used to minimize the objective function. According to the results of the single stack investigation, shunt current reduction could significantly improve the energy efficiency of partial-load operation. In addition, the optimization study revealed that whenever two or more lines are required to run in order to satisfy the hydrogen demand, the global SEC is minimized when the lines operate at equal loads. [ABSTRACT FROM AUTHOR]

Bipolar configuration electrochemical stacks with a common or circulating electrolyte supply usually embody a high amount of shunt currents that escape from the main current path to the manifold nozzles. This paper suggests a novel and simplified semiempirical model to reasonably predict the total shunt currents in industrial alkaline water electrolyzers (AWE). The aim of the study is to perform a sensitivity analysis of the model parameters and the process conditions that affect the shunt currents and the plant's specific energy consumption (SEC), and to determine the most important ones by analyzing the thermodynamic and fluidic properties of the stack. An in-house MATLAB dynamic energy and mass balance model of an industrial 3 M W , 16 b a r AWE plant process was developed. The semiempirical dynamic process model is updated with the essential shunt currents and electrochemical, fluidic, and circulation impurity models. The study revealed the influence of the supplied current, the electrolyte temperature, the process pressure, the electrolyte flow rate, and the potassium hydroxide concentration on the shunt currents and the plant's SEC. • Simulation of a validated 3 MW industrial-scale AWE semi-empirical transient model. • Sensitivity analysis of the process conditions affecting the shunt currents in bipolar-configuration stacks. • Effect of the current supply, stack temperature, and electrolyte flow rate on the plant SEC. • Plant model parametrization and uncertainty analysis for the electrochemical model. • At partial loads, the shunt currents are the major source of energy loss in the system. [ABSTRACT FROM AUTHOR]

Green hydrogen production systems will play an important role in the energy transition from fossil-based fuels to zero-carbon technologies. This paper investigates a concept of an off-grid alkaline water electrolyzer plant integrated with solar photovoltaic (PV), wind power, and a battery energy storage system (BESS). The operation of the plant is simulated over 30 years with 5 min time resolution based on measured power generation data collected from a solar photovoltaic installation and a wind farm located in southeastern Finland. Levelized cost of hydrogen (LCOH) is calculated based on the capital expenditures (CAPEX), the operating expenses (OPEX), and the respective learning curves for each of the components. Component degradation and replacements during the operational lifetime are included in the model, and the capacity of the components and the system control are simultaneously optimized to obtain the minimum LCOH. A sensitivity analysis performed over different installation years and discount rates reveals that for the off-grid alkaline system, the implementation of a wind farm as the sole power supply is the most economical solution until the installation years 2035–2040. Solar PV and a BESS are found to increase the full-load hours of the electrolyzer and reduce the electricity curtailed in the off-grid plant to less than 8%. However, with the current component prices and the climate in the studied region, they are not economically beneficial. It is found that the cost of hydrogen can be reduced to 2 €/kg by the year 2030. • Optimal control and component capacities for a green hydrogen production plant. • Simulations use measured power from a solar PV installation and a wind farm. • Levelized cost of hydrogen is less than 2 €/kg by the year 2030. • Purely wind based system is the most cost-effective solution until the years 2035–2040. [ABSTRACT FROM AUTHOR]

The capacity of each component in an off-grid water electrolyzer hydrogen production plant integrated with solar photovoltaics and a battery energy storage system represents a significant factor affecting the viability and reliability of the system. This paper describes a novel method that optimizes simultaneously the component capacities and finite-state machine based control of the system to minimize the cost of green hydrogen production. The components and control in the system are referenced to a proton exchange membrane water electrolyzer stack with a fixed nominal power of 4.5 kW. The end results are thus scalable by changing the nominal power of the electrolyzer. Simulations are carried out based on data collected from a residential solar photovoltaic installation with 300 s time resolution. Optimization of the system is performed with particle swarm optimization algorithm. A sensitivity analysis performed over the prices of the different components reveals that the price of the water electrolyzer has the greatest impact on the green hydrogen production cost. It is found that the price of the battery has to be below 0.3 €/Wh to become a feasible solution as overnight energy storage. • System components and control are optimized simultaneously using PSO algorithm. • Simulations are based on data collected from an existing solar PV installation. • Electrolyzer price has the strongest effect on off-grid hydrogen production cost. • Overnight hydrogen production becomes economic below 0.3 €/Wh battery system price. [ABSTRACT FROM AUTHOR]