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Advanced Scheduling of Electrolyzer Modules for Grid Flexibility

Angelina Lesniak, Andrea Gloppen Johnsen, Noah Rhodes, Line Roald

TL;DR

This work tackles scheduling a wind-powered alkaline electrolyzer system for hydrogen production under day-ahead market conditions. It introduces a MILP framework that models multiple electrolyzer modules and uses a piecewise-linear hydrogen-production curve to capture efficiency variations. Key findings show that increasing the number of modules and using a detailed 88-segment curve increases hydrogen output and revenue due to a lower effective minimum operating capacity and better alignment with the efficiency peak. The results underscore the practical value of modular design for grid flexibility and economics of green hydrogen in ERCOT-like settings.

Abstract

As the transition to sustainable power generation progresses, green hydrogen production via electrolysis is expected to gain importance as a means for energy storage and flexible load to complement variable renewable generation. With the increasing need for cost-effective and efficient hydrogen production, electrolyzer optimization is essential to improve both energy efficiency and profitability. This paper analyzes how the efficiency and modular setup of alkaline hydrogen electrolyzers can improve hydrogen output of systems linked to a fluctuating renewable power supply. To explore this, we propose a day-ahead optimal scheduling problem of a hybrid wind and electrolyzer system. The novelty of our approach lies in modeling the number and capacity of electrolyzer modules, and capturing the modules' impact on the hydrogen production and efficiency. We solve the resulting mixed-integer optimization problem with several different combinations of number of modules, efficiency and operating range parameters, using day-ahead market data from a wind farm generator in the ERCOT system as an input. Our results demonstrate that the proposed approach ensures that electrolyzer owners can better optimize the operation of their systems, achieving greater hydrogen production and higher revenue. Key findings include that as the number of modules in a system with the same overall capacity increases, hydrogen production and revenue increases.

Advanced Scheduling of Electrolyzer Modules for Grid Flexibility

TL;DR

This work tackles scheduling a wind-powered alkaline electrolyzer system for hydrogen production under day-ahead market conditions. It introduces a MILP framework that models multiple electrolyzer modules and uses a piecewise-linear hydrogen-production curve to capture efficiency variations. Key findings show that increasing the number of modules and using a detailed 88-segment curve increases hydrogen output and revenue due to a lower effective minimum operating capacity and better alignment with the efficiency peak. The results underscore the practical value of modular design for grid flexibility and economics of green hydrogen in ERCOT-like settings.

Abstract

As the transition to sustainable power generation progresses, green hydrogen production via electrolysis is expected to gain importance as a means for energy storage and flexible load to complement variable renewable generation. With the increasing need for cost-effective and efficient hydrogen production, electrolyzer optimization is essential to improve both energy efficiency and profitability. This paper analyzes how the efficiency and modular setup of alkaline hydrogen electrolyzers can improve hydrogen output of systems linked to a fluctuating renewable power supply. To explore this, we propose a day-ahead optimal scheduling problem of a hybrid wind and electrolyzer system. The novelty of our approach lies in modeling the number and capacity of electrolyzer modules, and capturing the modules' impact on the hydrogen production and efficiency. We solve the resulting mixed-integer optimization problem with several different combinations of number of modules, efficiency and operating range parameters, using day-ahead market data from a wind farm generator in the ERCOT system as an input. Our results demonstrate that the proposed approach ensures that electrolyzer owners can better optimize the operation of their systems, achieving greater hydrogen production and higher revenue. Key findings include that as the number of modules in a system with the same overall capacity increases, hydrogen production and revenue increases.
Paper Structure (23 sections, 10 equations, 4 figures, 3 tables)

This paper contains 23 sections, 10 equations, 4 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Background
  3. Literature Review
  4. Contributions
  5. Optimal Scheduling of a Hybrid Power Plant
  6. Electrolyzer Modeling
  7. Mathematical Model Formulation
  8. Hydrogen Production Curve
  9. Operating Range
  10. Economic Constraint on Grid Power Sales
  11. Ramp Rate
  12. Start-up time
  13. Start-up Cost
  14. Power Balance
  15. Optimization Variables and Constraints
  16. ...and 8 more sections

Figures (4)

  • Figure 1: Hydrogen production (left) and efficiency curves (right) approximated using 8 (blue) or 88 (red) linear segments
  • Figure 2: Total wind power consumed by each multi-modular electrolyzer system across a 24-hour period. The lines in the magnified view indicate the minimum power threshold for each configuration.
  • Figure 3: Total hydrogen produced by each multi-modular electrolyzer system over 24 hours, using the 88-segment hydrogen production approximation.
  • Figure 4: Power consumed by individual modules for 1 (blue) and 4 (red) module electrolyzer systems across 24 hours in alignment with their respective efficiency curves, utilizing the 88-segment hydrogen production approximation.