DOE OSTI · 2588459
Customized open source renewable energy models validated through PHIL lab experiments
Abstract
Energy models for power systems require ongoing updates to reflect advancements in equipment technology and the increasing complexity of power electronic devices. This study utilizes a Power Hardware-in-the-Loop (PHIL) experimental setup to validate custom photovoltaic (PV) inverter models, aiming to enhance and expedite the development of advanced renewable energy models. The research compares the performance of a physical inverter with generic Renewable Energy Source (RES) models recommended by the Western Electricity Coordinating Council (WECC). As inverter-based renewable energy sources become more prevalent in modern electrical grids, it is crucial that dynamic models accurately represent their real-world behavior. Accurate models improve our understanding of these energy resources and their interactions with the grid. The proposed model enhancements are designed to better reflect real inverter performance, based on insights from PHIL experiments. These models are developed using the open source Modelica language and the OpenIPSL Modelica Library, allowing integration across various simulation tools without re-implementation. The paper concludes with a thorough assessment, comparing the enhanced models with PHIL experiments on a real PV inverter in a controlled laboratory setting. As a result, the study provides the enhanced WECC RES models and validation data as open source resources, facilitating further research and development.
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Fachini, Fernando [Rensselaer Polytechnic Institute, Troy, NY (United States)] (ORCID:0009000833033542), Chang, Hao [Rensselaer Polytechnic Institute, Troy, NY (United States)], Bogodorova, Tetiana [Rensselaer Polytechnic Institute, Troy, NY (United States)] (ORCID:0000000233129244), Vanfretti, Luigi [Rensselaer Polytechnic Institute, Troy, NY (United States)] (ORCID:0000000241251055). 2025-02-19. Customized open source renewable energy models validated through PHIL lab experiments. https://doi.org/10.1016/j.renene.2025.122627
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