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ZENODO
Report . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Report . 2025
License: CC BY
Data sources: Datacite
ZENODO
Report . 2025
License: CC BY
Data sources: Datacite
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Smart Inverter Droop Setting to Solve Voltage Issues in Distribution Networks (Smart-Droop)

Authors: Savascı, Alper; Çakır, Muhammed Turhan; Ceylan, Oguzhan;

Smart Inverter Droop Setting to Solve Voltage Issues in Distribution Networks (Smart-Droop)

Abstract

This report details the results and experiences of the project titled Smart Inverter Droop Setting to Solve Voltage Issues in Distribution Networks (Smart-Droop)”, conducted under the ERIGrid 2.0. Smart-Droop project focused on improving the voltage regulation performance of the electrical power distribution networks by utilizing the Volt-VAr and Volt-Watt droop curves of the Smart Inverters (SIs). The primary objective of the project was to improve voltage performance by applying rule-based and optimal power flow (OPF)-based control algorithms. During the two-week access period at the DER-TF, the project team including researchers from Abdullah Gül University (AGU), Kadir Has University (KHAS) and Marmara University (MU) successfully implemented a series of tests, implementing the control techniques to improve the voltage performance. The team initially dealt with the experimental setup including the microgrid formation with distributed energy resources(DERs) such as photovoltaics (PV), combined heat and power (CHP), battery energy storage system (BESS). Then, a secure communication between control room and the grid was established over Modbus communication. The test system was simulated using Open Source Distribution System Simulator (OpenDSS) and the power flow results for various cases was compared to the actual measurements from the SCADA system. Then the developed rule-based and Optimal Power Flow (OPF) based simulations were conducted. Lastly, experiments were carried out by applying rule-based and optimal power flow (OPF)based management frameworks. One of the key achievements of the project was successfully applying model-based droop control in a real-world power grid, which was a major step forward for dynamic voltage regulations. For this aim, the research team carefully used an experimental test bed with the guidance from RSE experts, whose close collaboration has helped in overcoming complex technical challenges. The ERIGrid 2.0 platform also played a key role, providing the advanced infrastructure needed to run realistic, high-precision experiments. This allowed the research team to test and validate their ideas in practice, helping move them closer to real-world implementation on a larger scale. The Smart-Droop project has successfully combined droop control techniques with power flow analysis and Optimal Power Flow (OPF) algorithms, leading to major improvements in voltage regulation capabilities. The results show just how important collaboration, flexible testing approaches, and forward-thinking control systems are for today’s power grids. These breakthroughs highlight the growing need for smart, responsive control strategies and set a new standard for improving grid efficiency in distribution networks with many distributed energy sources.

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Keywords

User Project, Smart-Droop, Report, ERIGrid 2.0, H2020, European Union (EU), Lab Access, GA 870620

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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