Abstract

This paper presents a real-time simulation with a hardware-in-the-loop (HIL)-based approach for verifying the performance of electrolyzer systems in providing grid support. Hydrogen refueling stations may use electrolyzer systems to generate hydrogen and are proposed to have the potential of becoming smarter loads that can proactively provide grid services. On the basis of experimental findings, electrolyzer systems with balance of plant are observed to have a high level of controllability and hence can add flexibility to the grid from the demand side. A generic front end controller (FEC) is proposed, which enables an optimal operation of the load on the basis of market and grid conditions. This controller has been simulated and tested in a real-time environment with electrolyzer hardware for a performance assessment. It can optimize the operation of electrolyzer systems on the basis of the information collected by a communication module. Real-time simulation tests are performed to verify the performance of the FEC-driven electrolyzers to provide grid support that enables flexibility, greater economic revenue, and grid support for hydrogen producers under dynamic conditions. The FEC proposed in this paper is tested with electrolyzers, however, it is proposed as a generic control topology that is applicable to any load.

Highlights

  • The widespread adoption and deployment of distributed energy resources (DERs) is one of the most dynamic features of the modern-day electric grid

  • The paper is organized into the following sections: Section 1 provides background information related to the need of smarter loads providing flexibility to the grid; Section 2 describes the front end controller (FEC), which enables controllability of loads such as eletrolyzer systems used in hydrogen refueling stations; Section 3 details the description of the 120 and 250 kW proton exchange membrane (PEM) electrolyzer stack; Section 4 discusses the real-time simulations with controllable hydrogen refueling stations providing grid support; and Section 5 concludes the research findings of the paper

  • The power consumption of the electrolyzer during the peak time was maintained at a minimum, and during the off-peak time with a low SOC, the electrolyzer power consumption was maximized in order to produce cheap hydrogen

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Summary

Introduction

The widespread adoption and deployment of distributed energy resources (DERs) is one of the most dynamic features of the modern-day electric grid. The observability and controls can become quite involved on the basis of the type, ownership, operational characteristics, and so forth of the DER Another complicating trend in the changing landscape of the electric grid is the increasing penetration of renewable energy sources, such as solar and wind power plants, at the transmission or subtransmission levels of the electric grid [2]. The choice of electrolyzers for demonstrating flexibility addition to the grid is based on the increasing hydrogen demand for transportation and its inherent controllability at a subsecond-level time resolution. This describes the ultimate objective of adding flexibility via loads from the distribution network. The paper is organized into the following sections: Section 1 provides background information related to the need of smarter loads providing flexibility to the grid; Section 2 describes the FEC, which enables controllability of loads such as eletrolyzer systems used in hydrogen refueling stations; Section 3 details the description of the 120 and 250 kW PEM electrolyzer stack; Section 4 discusses the real-time simulations with controllable hydrogen refueling stations providing grid support; and Section 5 concludes the research findings of the paper

Front End Controller
Modules in the Front End Controller
Front End Controller Operation and Customization for Electrolyzers
Characterization of the Electrolyzer Stack
Test Approach
Tests for Fast-Loop Optimization
Electrolyzers Providing Frequency Support
Electrolyzers Providing Voltage Support
Tests for Slow-Loop Optimization
Demonstrating Demand Response Participation
Concluding Remarks
Full Text
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