Green Hydrogen Microgrid Simulation in MATLAB

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Introduction

Green hydrogen, produced through water electrolysis powered by renewable energy, is a critical enabler of the global energy transition. It supports decarbonization of hard-to-abate sectors such as heavy industry, long-distance transport, and long-duration energy storage. In renewable microgrids, green hydrogen functions as a long-term energy buffer by converting surplus solar PV or wind power into hydrogen, reducing curtailment, improving resilience, and enhancing energy autonomy in islanded or weak-grid systems.

This project presents a MATLAB/Simulink-based simulation framework for a green hydrogen microgrid incorporating solar PV (or hybrid PV-wind), battery energy storage, PEM or alkaline electrolyzer, hydrogen storage tank, and an optional fuel cell. Using Simscape Electrical, Fluids, and Thermal libraries, the model evaluates multi-day operation under realistic weather conditions. Key outputs include hydrogen production (kg/day), electrolyzer efficiency, battery SoC dynamics, renewable utilization, curtailment reduction, and levelized cost of hydrogen (LCOH), supporting techno-economic analysis, control strategy validation, and scalable microgrid design.

Methodology

 

 Green Hydrogen Microgrid Simulation (MATLAB/Simulink)

  1. Multi-Physics Simulation Framework
    MATLAB/Simulink (R2024b+) with Simscape Electrical, Fluids, and Thermal libraries for system-level microgrid modeling.

  2. Renewable Energy Generation Modeling
    PV array (optional wind) with MPPT control (P&O / Incremental Conductance) using real or synthetic weather data.

  3. DC Microgrid & Energy Storage System
    Lithium-ion battery with SoC estimation, bidirectional DC-DC converter, and 400–800 V common DC bus.

  4. Electrolyzer System Modeling
    PEM or alkaline electrolyzer with V–I characteristics, 60–80% efficiency, Faraday-based hydrogen production, and thermal management.

  5. Hydrogen Storage & Fuel Cell Integration
    Compressed hydrogen tank with pressure–temperature dynamics; optional PEM fuel cell for re-electrification.

  6. Energy Management & Control Strategy
    Rule-based EMS prioritizing battery charging, hydrogen production, and curtailment minimization using Stateflow.

  7. Simulation Scenarios & Solver Setup
    Time-domain simulations (ode23t) using load profiles and long-term weather data.

  8. Performance Metrics & Validation
    Hydrogen yield, system efficiency, curtailment, utilization factor, and benchmark validation.