Public Reference Data for Megawatt-Scale Hydrogen Electrolysis ? Simulated Wave
The U.S. Department of Energy and the National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis, hydrogen compression and storage, and variable hydrogen fuel cell power production using megawatt-scale equipment at NLR?s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence (AI) data centers and other variable loads.This dataset entry describes hydrogen production using a single, simulated wave energy conversion device. The electrolyzer is a 1.25-MW proton exchange membrane type MC250 system manufactured by Nel Hydrogen. While the unit supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack.For the wave energy, NLR used a wave energy converter model from PacWave. These devices can be equipped with accumulators and pressure relief values to smooth the power output by storing and releasing hydraulic energy. Using a peak power output of 10 MW, the model created two 25-minute profiles: one with and one without the accumulators and pressure relief valves. To down select the profile data from the native resolution of 20 Hz to 1 Hz, NLR took the mean of every 20 data points.NLR experimented with two simulated wave energy power plants: one that peaks at 10 MW, and one that peaks at 5 MW. These profiles were scaled for the physical 1.25 MW electrolyzer by multiplying the original profiles by one eighth and one quarter, respectively. The first profile matches the capacity rating of eight of the 1.25 MW electrolyzers, while the second matches four electrolyzers. Finally, NLR experimented with two settings for the electrolyzer power supply minimum and maximum current ramp rates (gain and slew): 200 and 400 amperes per second.The simulated profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz frequency. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. Each .zip file represents a single wave electrolysis experiment and is formatted as follows:{technology}-{accumulator?}_{number of 1.25 MW electrolyzers connected}-{electrolyzer ramp rate in amperes/second}For instance, ?wavePacWave-Noacc_4-400.zip? represents the 25 minute-long experiment using the PacWave?s wave energy converter model, equipped with no accumulator, connected to four 1.25-MW electrolyzers with their power supplies set to a maximum current ramp rate (gain and slew) of 400 A/s. Each .zip folder contains the following files:A .csv file containing raw data.An .xlsx file explaining all the fields in the raw data.A .png plot showing the time series of hydrogen production in kilograms per hour, electrolysis power consumption, and input wave power.An experiment, labeled ?characterization_200.zip?, demonstrates the MC250 electrolyzer steady-state response with 30 minute load steps for a total duration of 5 hours.Finally, a .csv file is provided with all wave profiles combined into one dataset labeled "combined_wave_experiments.csv".NLR also built an AI/machine-learning predictive model based on these datasets. The model ingests the electrolyzer current command in amperes, as well as various pressures and temperatures across the system, and predicts hydrogen output in kilograms per hour. The complete model can be found at https://huggingface.co/NatLabRockies/ptmelt-hydrogen-electrolysis.
Citation Formats
TY - DATA
AB - The U.S. Department of Energy and the National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis, hydrogen compression and storage, and variable hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence (AI) data centers and other variable loads.This dataset entry describes hydrogen production using a single, simulated wave energy conversion device. The electrolyzer is a 1.25-MW proton exchange membrane type MC250 system manufactured by Nel Hydrogen. While the unit supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack.For the wave energy, NLR used a wave energy converter model from PacWave. These devices can be equipped with accumulators and pressure relief values to smooth the power output by storing and releasing hydraulic energy. Using a peak power output of 10 MW, the model created two 25-minute profiles: one with and one without the accumulators and pressure relief valves. To down select the profile data from the native resolution of 20 Hz to 1 Hz, NLR took the mean of every 20 data points.NLR experimented with two simulated wave energy power plants: one that peaks at 10 MW, and one that peaks at 5 MW. These profiles were scaled for the physical 1.25 MW electrolyzer by multiplying the original profiles by one eighth and one quarter, respectively. The first profile matches the capacity rating of eight of the 1.25 MW electrolyzers, while the second matches four electrolyzers. Finally, NLR experimented with two settings for the electrolyzer power supply minimum and maximum current ramp rates (gain and slew): 200 and 400 amperes per second.The simulated profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz frequency. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. Each .zip file represents a single wave electrolysis experiment and is formatted as follows:{technology}-{accumulator?}_{number of 1.25 MW electrolyzers connected}-{electrolyzer ramp rate in amperes/second}For instance, “wavePacWave-Noacc_4-400.zip” represents the 25 minute-long experiment using the PacWave’s wave energy converter model, equipped with no accumulator, connected to four 1.25-MW electrolyzers with their power supplies set to a maximum current ramp rate (gain and slew) of 400 A/s. Each .zip folder contains the following files:A .csv file containing raw data.An .xlsx file explaining all the fields in the raw data.A .png plot showing the time series of hydrogen production in kilograms per hour, electrolysis power consumption, and input wave power.An experiment, labeled “characterization_200.zip”, demonstrates the MC250 electrolyzer steady-state response with 30 minute load steps for a total duration of 5 hours.Finally, a .csv file is provided with all wave profiles combined into one dataset labeled "combined_wave_experiments.csv".NLR also built an AI/machine-learning predictive model based on these datasets. The model ingests the electrolyzer current command in amperes, as well as various pressures and temperatures across the system, and predicts hydrogen output in kilograms per hour. The complete model can be found at https://huggingface.co/NatLabRockies/ptmelt-hydrogen-electrolysis.
AU - Abel, Riley
A2 - Schwarz, Marty
A3 - Leighton, Daniel
A4 - Gevorgian, Vahan
A5 - Wimer, Nicholas
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Laboratory of the Rockies
DO -
KW - hydrogen
KW - electrolysis
KW - proton exchange membrane electrolyzer
KW - wave technology
KW - wave energy
KW - hydrogen production
KW - energy storage
KW - ARIES
KW - Hydrogen and Fuel Cell Technologies Office
KW - machine learning
KW - AI/ML
KW - LSTM
KW - forecasting
KW - uncertainty quantification
KW - PT-MELT
KW - HFTO
LA - English
DA - 2025/12/12
PY - 2025
PB - National Laboratory of the Rockies
T1 - Public Reference Data for Megawatt-Scale Hydrogen Electrolysis – Simulated Wave
UR - https://data.openei.org/submissions/8586
ER -
Abel, Riley, et al. Public Reference Data for Megawatt-Scale Hydrogen Electrolysis ? Simulated Wave. National Laboratory of the Rockies, 12 December, 2025, NREL. https://data.nlr.gov/submissions/306.
Abel, R., Schwarz, M., Leighton, D., Gevorgian, V., & Wimer, N. (2025). Public Reference Data for Megawatt-Scale Hydrogen Electrolysis ? Simulated Wave. [Data set]. NREL. National Laboratory of the Rockies. https://data.nlr.gov/submissions/306
Abel, Riley, Marty Schwarz, Daniel Leighton, Vahan Gevorgian, and Nicholas Wimer. Public Reference Data for Megawatt-Scale Hydrogen Electrolysis ? Simulated Wave. National Laboratory of the Rockies, December, 12, 2025. Distributed by NREL. https://data.nlr.gov/submissions/306
@misc{OEDI_Dataset_8586,
title = {Public Reference Data for Megawatt-Scale Hydrogen Electrolysis ? Simulated Wave},
author = {Abel, Riley and Schwarz, Marty and Leighton, Daniel and Gevorgian, Vahan and Wimer, Nicholas},
abstractNote = {The U.S. Department of Energy and the National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis, hydrogen compression and storage, and variable hydrogen fuel cell power production using megawatt-scale equipment at NLR?s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence (AI) data centers and other variable loads.This dataset entry describes hydrogen production using a single, simulated wave energy conversion device. The electrolyzer is a 1.25-MW proton exchange membrane type MC250 system manufactured by Nel Hydrogen. While the unit supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack.For the wave energy, NLR used a wave energy converter model from PacWave. These devices can be equipped with accumulators and pressure relief values to smooth the power output by storing and releasing hydraulic energy. Using a peak power output of 10 MW, the model created two 25-minute profiles: one with and one without the accumulators and pressure relief valves. To down select the profile data from the native resolution of 20 Hz to 1 Hz, NLR took the mean of every 20 data points.NLR experimented with two simulated wave energy power plants: one that peaks at 10 MW, and one that peaks at 5 MW. These profiles were scaled for the physical 1.25 MW electrolyzer by multiplying the original profiles by one eighth and one quarter, respectively. The first profile matches the capacity rating of eight of the 1.25 MW electrolyzers, while the second matches four electrolyzers. Finally, NLR experimented with two settings for the electrolyzer power supply minimum and maximum current ramp rates (gain and slew): 200 and 400 amperes per second.The simulated profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz frequency. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter.\ Each .zip file represents a single wave electrolysis experiment and is formatted as follows:{technology}-{accumulator?}_{number of 1.25 MW electrolyzers connected}-{electrolyzer ramp rate in amperes/second}For instance, ?wavePacWave-Noacc_4-400.zip? represents the 25 minute-long experiment using the PacWave?s wave energy converter model, equipped with no accumulator, connected to four 1.25-MW electrolyzers with their power supplies set to a maximum current ramp rate (gain and slew) of 400 A/s.\ Each .zip folder contains the following files:A .csv file containing raw data.An .xlsx file explaining all the fields in the raw data.A .png plot showing the time series of hydrogen production in kilograms per hour, electrolysis power consumption, and input wave power.An experiment, labeled ?characterization_200.zip?, demonstrates the MC250 electrolyzer steady-state response with 30 minute load steps for a total duration of 5 hours.Finally, a .csv file is provided with all wave profiles combined into one dataset labeled "combined_wave_experiments.csv".NLR also built an AI/machine-learning predictive model based on these datasets. The model ingests the electrolyzer current command in amperes, as well as various pressures and temperatures across the system, and predicts hydrogen output in kilograms per hour. The complete model can be found at https://huggingface.co/NatLabRockies/ptmelt-hydrogen-electrolysis.},
url = {https://data.nlr.gov/submissions/306},
year = {2025},
howpublished = {NREL, National Laboratory of the Rockies, https://data.nlr.gov/submissions/306},
note = {Accessed: 2026-06-08}
}
Details
Data from Dec 12, 2025
Last updated Mar 12, 2026
Submitted Dec 12, 2025
Organization
National Laboratory of the Rockies
Contact
Riley Abel
Authors
Original Source
https://data.nlr.gov/submissions/306Research Areas
Keywords
hydrogen, electrolysis, proton exchange membrane electrolyzer, wave technology, wave energy, hydrogen production, energy storage, ARIES, Hydrogen and Fuel Cell Technologies Office, machine learning, AI/ML, LSTM, forecasting, uncertainty quantification, PT-MELT, HFTODOE Project Details
Project Name Public Reference Data for Megawatt-Scale Hydrogen Electrolysis Production and Energy Storage Using Fuel Cell Power
Project Number WBS 7.3.0.508

