#1ONREL Transforming ENERGY U.S. Wind to Hydrogen Modeling, Analysis, Testing, and Collaboration Genevieve Saur Kazunori Nagasawa (co-presenter) National Renewable Energy Laboratory DOE WBS #7.2.9.15 June 7, 2023 DOE Hydrogen Program 2023 Annual Merit Review and Peer Evaluation Meeting Project ID: TA060 Photo from iStock-627281636 This presentation does not contain any proprietary, confidential, or otherwise restricted information#2• • Project Goal This project explores electrolytic hydrogen production hydrogen from offshore wind turbines, a promising pathway for decarbonization for multiple energy sectors. Topics: - - Assessment for current and near-term technologies Pursue international collaboration to share learnings and advance the technology Support industry partners in research and demonstration activities • FY23 Goals • - - Joint techno-economic assessment to identify a common framework for evaluation of projects, key barriers, and research needs Hardware testing to accelerate development of an integrated, in-turbine offshore wind-hydrogen system The impact is to accelerate development and de-risk a promising hydrogen production pathway. NREL 2#3• • • . Timeline and Budget Project Start Date: 01/01/2022 FY22 DOE Funding: $300k FY23 Planned DOE Funding: $300k Total DOE Funds Received to Date**: $600k ** Since the project started Overview Barriers ⚫ J. Renewable Electricity Generation Integration • ⚫ F. Capital Cost • H. Footprint, Size and Weight • L. Operations and Maintenance • M. Control and Safety Partners . Experimental Task: - Giner, GE Research, HYGRO, Plug Power TEA Assessment: - TNO (Netherlands) NREL 3#4Potential Impact • What: Collection of projects addressing analytic and experimental requirements for developing proof-of-concept offshore wind-hydrogen projects • Why: Offshore wind-H2 is a promising pathway for tightly integrated renewable H2 Addressing grid and coastal constraints as renewable electricity is built out - High-throughput, economically-scalable energy delivery via undersea pipelines - Overlaps with two DOE Energy Earthshots - Hydrogen and Floating Offshore Wind • Why: Offshore wind is still early market, especially in the US; offshore wind-H2 is in infancy with no operational demonstrations to-date (though several projects in development) - Offshore conditions and requirements are very different compared to onshore - - System design and operations must be considered for harsh, remote locations Industry interest is considerable • How: FY23 activity was focused on - Renewable electricity generation integration through experimental setup with industry Capital cost, gap/uncertainty, common framework assessment through international working group NREL | 4#5Integrated testing for distributed offshore wind- electrolysis system (experimental project) Utilizing test facilities at NREL#6• . Approach: Integrated testbed for distributed wind-electrolysis system Goal: Accelerate development of a distributed wind-electrolysis system through use of NREL testing facilities. - Industry partners: Giner (electrolysis), GE Research (wind), HYGRO (integration, and Plug Power (stack supplier) [See also TA051] Initial de-risk testing to understand fast- control effects that the PEM electrolyzer will have on wind turbine controls Target data: NREL's 750-kW stack test bed to obtain high-fidelity data (~40 ms) to assess closely integrated system NREL's Hydrogen Infrastructure Testing and Research Facility (HITRF) Infrastructure Fueling o Electrolyzer System Production Future Power Supplies NREL 6#7Approach: Simulation models and data preparation TurbSim & OpenFAST to create power profiles Generate AC output profiles Estimate DC output with a rectifier efficiency Data Flows Wind speed (mean) = {4, 6, 8, 10, 12, 14, 16, 20} m/s TurbSim Model RSCAD/LabVIEW Model Simulated wind profile (offline data) Wind Speed OpenFAST Model Turbine Response Open-loop (decoupled)- Current Setpoint Electrolyzer Stack RSCAD model sends current setpoints to the electrolyzer system Up to 50 us (target: 40 ms) Synchronized sensor measurements and storage Open-loop simulation OpenFAST and RSCAD are decoupled: 1) prepare offline data and 2) feed it into the RSCAD model RTDS Sensor measurements Database Real-time control systems Hardware H2SCADA Stack Testbed Real-time control systems Hardware NREL 7#8Approach: System configuration with sensor measurements • Power converter AC power • Stack data - Current - Voltage - Cell-level voltage monitoring Anode and cathode pressures Temperature • H2 production Data acquisition plan to assess stack responses and degradation Tap Water Supply Deionization O₂/H₂O Phase Separator Oxygen to Vent or Storage Water Quality of H₂ H₂/H₂O Mass flow rate Pressure Dryer Temperature > 1 MQ-cm Fluoride concentration DI Polishing Pump Water quality Water How rate Stack temperature Anode pressure Circulation Pump H₂/H₂O Phase Separator Cathode pressure Key H₂/H₂O Cooling Pump - Current to mass flow rate conversion Water loop Inflow water quality Outflow fluoride Heat concentrations: anode and Exchanger cathode sides (effluent water sampling) PEM Electrolyzer Oxygen Wet Hydrogen DC Power Cell voltage DC current DC voltage AC/DC Rectifier Desalinated Water Dry Hydrogen AC Power Deionized Water DC Power Electrical Power AC Power AC power Sensor Measurement NREL 8#9Accomplishments: Simulation framework for experiments Wind speed TurbSim according to IEC 61400 DLC 1.2 (NTM), class IB, with mean wind speed of {4, 6, 8, 10, 12, 14, 16, 20} m/s Power curve OpenFAST simulating IEA 15 MW WTG response • Power converter model • • Efficiency curve or fixed efficiency Polarization model Power-to-current relationship Stack temperature effects Degradation (state of the stack condition) Integration with the main control scheme H2SCADA at ESIF Time delays of each control block (communication delay) Transient stack characteristics (electrochemical response/delay) Power Curve Wind Speed 10 12 Wind speed. S [m/s] 30 0 0 200 400 600 800 1000 1200 1400 12 Time step (40 ms/step) Data 14 Model Gompertz 10 15 20 Wind speed. S [m/s] Hardware Integration Power, P [MW] 60 4. 2- 10 14 Built the simulation framework for hardware experiments Power Profile 0- 200 400 600 800 1000 1200 1400 Time step (40 ms/step) Idc Pac (scaled) Power Converter Model dc Polarization Model ESIF Control Scheme Pdc, Idci m (kgH₂/h) IEA 15 MW reference: https://www.nrel.gov/docs/fy20osti/75698.pdf Wind class parameters: https://cleanpower.org/wp-content/uploads/2021/05/ACP-61400-1-202x Draft.pdf OpenFAST documentation: https://buildmedia.readthedocs.org/media/pdf/openfast/latest/openfast.pdf NREL 9#10• Break-in test Accomplishments: Test procedures - 500 hours of break-in operation Dynamic test 1. 24 hours/test 2. Take a polarization curve at fixed stack temperature 3. Hold at fixed current; avoid shutdowns/startups (keep BOP operation) 4. Perform 8 dynamic tests Break-in Test Dynamic Test Experimental testing to begin in May 2023 500 hours of unattended operation at STB1/STB2 Run 8 tests (wind speeds): 192 hours at minimum 24+ hours/test of unattended operation at STB1/STB2 Break-in Period Dynamic Exp. Polarization Hold NREL 10 Time#11Offshore wind-hydrogen working group International collaboration between researchers at NREL (US) and TNO (Netherlands)#12Approach: NREL-TNO International Working Group on Offshore Wind-H2 What: An international working group on offshore wind-H2 between NREL and TNO is leveraging cross-Atlantic research to aid understanding. • Why: TNO and NREL are often requested to analyse or review the techno- economics of these offshore hydrogen production concepts, summarized in techno-economic analyses (TEA's). - - No concepts in operations, so many assumptions are made. Drivers are landing cables challenges in built-up coastlines and development cost of electricity infrastructure further offshore • How: TNO and NREL have compared several existing techno-economic analyses of the different concepts, to identify: - Compare concepts and identify knowledge gaps NREL Transforming ENERGY - Identify which factors in the TEAS have the highest uncertainty and impact TNO innovat - Outline strategies for lowering the uncertainty NREL 12#13Approach: NREL-TNO International Working Group on Offshore Wind-H2 1. Define TEA input sheet 2. Complete TEA input sheet 4. Compare results 5. Sensitivity analysis > NREL-TNO revise and agree on template and base scenario parameters for TEA input sheet > TNO and NREL complete (individually) TEA input sheet › Compare values and certainties, consciously agree on each item in the input sheet › Special focus on items showing discrepancies between NL and USA, large uncertainty > Determine what uncertainties have the highest impact > Prioritize in the uncertain parameters 6. Define next steps › Identify actions required to converge and reduce uncertainties In FY23 capital costs were the focus topic. NREL TNO Innovation Transforming ENERGY for life NREL 13#14Approach: NREL-TNO OSW-H2 Case Studies CASE 1 Distributed in-turbine electrolysis CASE 2 Centralized offshore platform H Hydrogen Offshore Energy VERDIC CASE 3 Onshore electrolysis Image from Strom of Strohm, Siemens concept Image from Recharge The case studies were chosen based on common studies already in progress at NREL and TNO. They represent basic concepts to focus initial efforts. Image from Howden of Holland Hydrogen 1 innovation NREL TNO for life NREL | 14 Transforming ENERGY#15Approach: NREL-TNO Initial Assumptions • The goal of this study was not Offshore conditions Sea depth to present precise values, but: - - Evaluate general trends between concepts Identify highest uncertainties and differences - Identify differences between European and US considerations Identify components/subsystems of the offshore hydrogen value chain where additional effort/research/demonstrations can reduce uncertainties. Wind farm Distance from shore Produced electric power Turbine size 40 m 100 km 1 GW 15 MW Electrolyzer (on platforms) Technology H2 transport Power transmission Onshore boundary . 67 PEM 100-200 MW Nr. of turbines Module size Delivered pressure 30 bar New pipeline (dedicated for wind farm only) New HVDC cable (dedicated for wind farm only) Export pressure 50 bar PEM electrolysis assumed as best available technology for offshore (due to footprint and dynamic response) Initial assumptions provided common basis for expert interpretation of differences in the comparison. innovation ONREL TNO for Transforming ENERGY NREL 15#16• . CASE 1 Accomplishment: NREL-TNO OSW-H2 Case Distributed in-turbine electrolysis Necessity of additional compression and storage beyond turbine level for inter- array and export pipeline Infield design of pipelines and collection not designed or optimized · O&M requirements for distributed electrolysis unclear • . Uncertainties CASE 2 Centralized offshore platform Platform size and cost is a big uncertainty and major contribution (footprint and weight of electrolysis system) Optimization of windfarm size to electrolyzer capacity not performed Installation and O&M costs uncertain (also Case 1) • CASE 3 Onshore electrolysis • Grid connection not considered, but is factor in optimal sizing and operation Buffer storage dependant on demand scenario (offshore- case 1&2- may be able to use inherent pipeline storage or inexpensive undersea storage) Trade-off between CapEX and OPEX for offshore operation not optimized. More uncertainty for system design offshore. ONREL Transforming ENERGY TNO for life innovation NREL 16#17. Accomplishment: NREL-TNO OSW-H2 Key Insights Electrolyzer costs in US are more aggressive due to Hydrogen Earthshot • Offshore wind costs in Netherlands lower due to more mature supply chain including turbine manufacturing and installation vessels • Jones Act will require purpose built ships registered in US - US supply chain is still under-developed, but ramping up Case study takeaways: - - The in-turbine case has the most competitive CAPEX, but also biggest uncertainties around OPEX and design • Capital cost assessment completed, but not available publicly yet • A lot of similarities in US-NL assessments, differences from supply chain and R&D cost reduction expectations Central offshore electrolysis may benefit from cost of export pipelines vs electrical infrastructure, but platform costs are very significant and OPEX uncertain Onshore electrolysis benefits from flexibility of grid connection, but less hydrogen storage and pipeline cost flexibility NREL TNO for life Transforming ENERGY innovation NREL 17#18. Accomplishment: NREL-TNO OSW-H2 Reducing costs and uncertainty Main potential cost reductions through innovation: - - In-turbine electrolysis: process intensification via turbine-electrolyzer integration Electrolyzer: R&D on stack level to increase durability/reliability and reduce footprint and cost Modularization / standardization of modules • Main uncertainties: - - - • Pilots and demonstrations will be key for reducing uncertainty Additional CAPEX due to offshore (unmanned) operations, including e.g. additional equipment and reliability/redundancy O&M costs for electrolysis, to model offshore ramifications and optimize between system design and operation considerations. Uncertainties in dynamic operation to understand operational performance window (effect of running above nominal load, at min load, cold start, hot start etc); degradation and optimized dispatch BoP requirements for the electrolysis system to understand the trade-off between reliability and flexibility - Turn down rate or minimum load is very important uncertainty affecting the design. Differs per technology. NREL TNO Transforming ENERGY innovation NREL 18#19• • Accomplishment: NREL-TNO OSW-H2 Recommendations for improving TEA Explicit CAPEX assumptions along with equipment sizing and utilization Clear description of modelling to the subsystem level to understand the electrical and H2 flow performance impact on BoP ( such as compression, pipelines, storage, water desalinization). • Detailed modelling of siting considerations (size and weight) of subsystems needed for platform analysis • Modelling at multiple time scales to understand dynamic range impact on BoP • OPEX modelling is a · • Operation analysis is needed to understand the impact of maintenance regimes O&M data is needed from onshore electrolysis to model the impact of offshore maintenance strategies key need to fully evaluate concepts • Failure Modes and Effects Analysis (FMEA) is needed to understand the impact of subsystem failures on the system design • Pipeline modelling to understand the compression needs, size consideration, and feasibility of use as inherent buffer storage NREL TNO for life innovation NREL 19 Transforming ENERGY#20Accomplishments and Progress: Response to Previous Year Reviewers' Comments • This project has not been reviewed previously NREL 20#21Collaboration and Coordination • Experimental project is in support of an industry team of Giner (electrolysis), GE Research (wind), HYGRO (integration, and Plug Power (stack supplier) Gε GINERLABS: GE Research HYGRO plug TM . The OSW-H2 working group is in collaboration with TNO (supported by RVO in the Netherlands) innovation TNO for life NREL 21#22. . Remaining Challenges and Barriers Experimental project will commence testing end of May 2023 - Results from testing will help guide next steps The OSW-H2 working group has an analysis on capital costs, but is working on ways to present results along with the uncertainty inherent in analysis of systems that don't yet exist. NREL 22#23Proposed Future Work Experimental project: - - Results of testing will be collected and analyzed Results of dynamic response rate testing will inform future needs to de-risk design • NREL-TNO OSW-H2 working group - Publish joint white paper on current results and begin work on OPEX contribution to overall economics and system design *For new projects, this criteria counts for 25% of your score. NREL 23#24. • Summary Offshore wind-H2 systems are very different from on-shore systems: Environmental factors being remote and in harsh conditions - - Integration of closely coupled systems that must be economic and reliable Offshore wind-H2 has no operational projects (yet) so there are a lot of uncertainties and areas to work through NREL is has a collection of projects to tackle: - Hardware integration and product development with industry - Analysis so we can address the right questions through internal and international collaborations NREL 24#25Experimental OSW-H2: Judith Lattimer (PI), Shirley Zhong (Giner) Kazunori Nagasawa, Kumaraguru Prabakar, Dan Leighton (NREL) Rogier Blom, Arvind Tiwari (GE Research) Hugo Groenemans, Elena Khramenkova (HYGRO) Cortney Mittelsteadt, Zach Green (Plug Power) Thank You US-NL OSW-H2 Working Group: Lennert Buijs, Michele Tedesco (TNO) Michael Hahn (DOE/HFTO) www.nrel.gov NREL/PR-5400-86008 This work was authored in part by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Hydrogen and Fuel Cell Technologies Office. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes. NREL Transforming ENERGY#26Technical Backup and Additional Information#27. Technology Transfer Activities • The experimental project is pursuing several funding opportunities . and the goal is product development of an in-turbine electrolysis system. The OSW-H2 working group is not pursuing technology transfer activities. NREL 27#28. Special Recognitions and Awards None at this time NREL 28#29Publications and Presentations • Hugo Groenemans, Genevieve Saur, Cortney Mittelsteadt, Judith Lattimer, Hui Xu, "Techno-economic analysis of offshore wind PEM water electrolysis for H2 production", Current Opinion in Chemical Engineering, Volume 37, 2022, 100828, ISSN 2211- 3398, https://doi.org/10.1016/j.coche.2022.100828. NREL 29