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Hydrogen Hubs: Electrolyzers, Storage, Transport, and End-Use Cases

Original price was: USD $99.00.Current price is: USD $59.00.

Design, size, and dispatch real-world hydrogen hubs.

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Course Description

Hydrogen Hubs: Electrolyzers, Storage, Transport, and End-Use Cases is a three-day, hands-on program focused on designing an end-to-end hydrogen hub that is bankable, operable, and certification-ready. Participants will learn how to size electrolyzer-based production for grid and renewable energy coupling, compare storage and transport pathways, and define end-use delivery requirements across industrial, mobility, and power sectors. The program integrates techno-economic analysis through LCOH modeling, logistics planning, safety and codes alignment, and carbon-intensity accounting. Participants will complete the course with a preliminary hub design, a sizing and LCOH worksheet, a storage/transport pathway selection, and a dispatch plan supported by KPIs and a carbon-intensity snapshot.


Aim

To equip participants to design, size, and dispatch an end-to-end hydrogen hub—from electrolyzers through storage, transport, and end-use—by applying techno-economic analysis (CAPEX/OPEX, LCOH), safety and codes compliance, logistics optimization, and carbon-intensity accounting, resulting in a defensible hub plan with KPIs and a carbon-intensity snapshot suitable for certification and investment discussions.


Course Objectives

Participants will be able to:

  • Compare PEM, Alkaline, and SOEC electrolyzers based on efficiency, dynamics, degradation, and duty-cycle fit.

  • Size production systems and balance-of-plant for grid versus renewable coupling, including power quality and utilization impacts.

  • Build and stress-test an LCOH model with sensitivity analysis for major cost and performance drivers.

  • Select storage and transport pathways (CGH₂, LH₂, LOHC, NH₃) with quantified costs, energy penalties, and losses.

  • Define end-use delivery requirements across sectors, including purity, pressure, ramping, and reliability expectations.

  • Calculate carbon intensity (kg CO₂e/kg H₂) and align documentation with certification and guarantees of origin.

  • Apply hydrogen safety principles and key codes, including ventilation, detection, zoning, siting, and emergency planning.

  • Develop a dispatch plan and operating governance approach using telemetry, KPIs, SLAs, and risk controls.


Course Structure

Module 1: Electrolyzers and Hydrogen Production

  • Technology overview: PEM, Alkaline, SOEC (efficiency, responsiveness, water requirements, degradation behavior)

  • Sizing and coupling: grid vs renewables (PV/wind), capacity factor, curtailment absorption, power quality considerations

  • Economics and policy: CAPEX/OPEX drivers, stack replacement, key LCOH levers, incentives and permitting factors

  • Safety fundamentals: hydrogen properties, ventilation strategy, detection and monitoring, area classification

  • Practical session: develop a quick plant sizing and LCOH calculator for a sample hub

Module 2: Storage and Transport Pathways

  • Storage options: CGH₂, LH₂, LOHC, NH₃ (energy penalties, boil-off, turnaround, operational constraints)

  • Assets and codes: vessels, cryogenic tanks, tube trailers; siting setbacks and key standards considerations

  • Networks and logistics: trucking vs pipeline options, blending limits, compression energy, hub-and-spoke design logic

  • Risk and HSE: leak scenarios, dispersion principles, sensor placement, emergency response planning

  • Practical session: size storage, select a transport mix, and estimate logistics costs and pathway losses

Module 3: End-Use Integration and Hub Dispatch

  • End-use sectors: refining, DRI steel, chemicals, turbines/engines, fuel cells (mobility/backup) with purity and duty-cycle requirements

  • Integration design: demand portfolios, temporal matching, hybrid hydrogen–power operation, curtailment valorization

  • Carbon intensity and certification: CI accounting (kg CO₂e/kg H₂), guarantees of origin, low-carbon labeling readiness

  • Operations and governance: telemetry and KPIs, SLAs, risk register, stakeholder coordination

  • Practical session: build a hub dispatch plan linking production, storage, and deliveries; generate CI and KPI snapshots


Who Should Enrol

  • Energy, process, chemical, mechanical, or electrical engineers

  • Project developers, EPC teams, and hydrogen OEM stakeholders (electrolyzers, storage, transport)

  • Industrial users in refining, DRI steel, chemicals, power, and mobility integration

  • Utilities, IPPs, and renewable energy planners working on grid coupling and project design

  • City/state energy planners, ports and logistics operators, and hub consortium leads

  • HSE and risk professionals, compliance officers, and safety managers

  • Policy, permitting, and regulatory officials

  • Investors, lenders, and commercial/finance analysts evaluating hydrogen projects

  • Researchers and senior students in energy systems


Workshop Outcomes

Participants will leave with:

  • Electrolyzer sizing and power/water requirement estimates for PEM, Alkaline, and SOEC pathways

  • A grid vs renewable coupling strategy accounting for utilization, curtailment, and power quality

  • A working LCOH model including CAPEX/OPEX, stack life, incentives, and sensitivity analysis

  • A justified storage and transport mix (CGH₂/LH₂/LOHC/NH₃) with cost and loss estimates

  • End-use requirement alignment across key sectors including purity and duty-cycle matching

  • Carbon intensity calculation outputs suitable for certification/GoO discussion

  • A safety and codes baseline checklist (ventilation, detection, zoning, siting)

  • A dispatch plan with KPI and CI snapshot plus governance basics

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Certification

  • Upon successful completion of the workshop, participants will be awarded a Certificate of Completion, validating their skills and knowledge in advanced AI ethics and regulatory frameworks. This certification can be added to your LinkedIn profile or shared with employers to demonstrate your commitment to ethical AI practices.

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