Abstract

This paper presents an approach to extend the capabilities of smart grid laboratories through the concept of Power Hardware-in-the-Loop (PHiL) testing by re-purposing existing grid-forming converters. A simple and cost-effective power interface, paired with a remotely located Digital Real-time Simulator (DRTS), facilitates Geographically Distributed Power Hardware Loop (GD-PHiL) in a quasi-static operating regime. In this study, a DRTS simulator was interfaced via the public internet with a grid-forming ship-to-shore converter located in a smart-grid testing laboratory, approximately 40 km away from the simulator. A case study based on the IEEE 13-bus distribution network, an on-load-tap-changer (OLTC) controller and a controllable load in the laboratory demonstrated the feasibility of such a setup. A simple compensation method applicable to this multi-rate setup is proposed and evaluated. Experimental results indicate that this compensation method significantly enhances the voltage response, whereas the conservation of energy at the coupling point still poses a challenge. Findings also show that, due to inherent limitations of the converter’s Modbus interface, a separate measurement setup is preferable. This can help achieve higher measurement fidelity, while simultaneously increasing the loop rate of the PHiL setup.

Highlights

  • Sustainable energy needs for the future are driving the increasing adoption of Renewable EnergySources that have altered the makeup of the traditional power grid

  • The test system used in this study is a modified version of the IEEE 13-bus feeder, which was modelled in RSCAD and executed on a PB5-based Real-time Digital Simulators (RTDS) simulator

  • The target test case for this study reviewed the suitability of a grid-forming converter for Quasi-static PHiL (QsPHiL)

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Summary

Introduction

Sustainable energy needs for the future are driving the increasing adoption of Renewable EnergySources that have altered the makeup of the traditional power grid. Sustainable energy needs for the future are driving the increasing adoption of Renewable Energy. The increasing complexity and scale of the power system requires tools that can carry out large scale simulations to study its interactions and interoperability with newer hardware and novel control schemes and develop advanced assessment methods. This entails a radical shift from static, offline load flow simulations towards dynamic, online real-time simulations with higher-fidelity. Simulation of large-scale power grids with detailed distributed energy resource models and control systems is a major challenge.

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