Dynamic Modeling of Distribution Power Systems with Renewable Generation for Stability Analysis

Darko Madjovski, Ivan Dumancic and Carolina Tranchita ()
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Darko Madjovski: Computer Science & Engineering, Frankfurt University of Applied Sciences, 60318 Frankfurt am Main, Germany
Ivan Dumancic: Computer Science & Engineering, Frankfurt University of Applied Sciences, 60318 Frankfurt am Main, Germany
Carolina Tranchita: Computer Science & Engineering, Frankfurt University of Applied Sciences, 60318 Frankfurt am Main, Germany

Energies, 2024, vol. 17, issue 20, 1-29

Abstract: This paper presents a comprehensive study on the dynamic modeling of distribution power systems with a focus on the integration of renewable energy sources (RESs) for stability analysis. Our research delves into the static and dynamic behavior of distribution systems, emphasizing the need for enhanced load modeling to mitigate planning and operational uncertainties. Using MATLAB/Simulink ® , we simulate four distinct study cases characterized by varying load types and levels of distributed generation (DG), particularly solar PV, under both balanced and unbalanced conditions. Our findings highlight the critical role of DG in influencing voltage stability, revealing that deviations in voltage and current during grid imbalances remain within acceptable limits. The study underscores the importance of DG-based inverters in maintaining grid stability through reactive power support and sets the stage for future research on microgrid simulations and battery storage integration to further enhance system stability and performance.

Keywords: load modeling; renewable energy; distribution power system; static load model; dynamic load model; composite load model; stability analysis; distributed generation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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