Location-Based Sizing of Battery Energy Storage for Voltage Regulation in MV/LV Distribution Networks

The increasing integration of Distributed Energy Resources (DER) and excess generation export has brought about problems in maintaining voltage profiles in MV/LV distribution networks. Battery Energy Storage Systems (BESS) offer a promising solution by providing ancillary services, including voltage regulation. This paper presents a methodology for determining locations for BESS deployment in MV/LV distribution networks to improve voltage regulation. The proposed approach integrates time-series loads and renewable energy generation profiles to identify critical locations where BESS can effectively mitigate feeder overvoltage. A multi- objective mathematical optimization model utilizing Genetic Algorithms (GAs) to size BESS units is introduced, minimizing voltage deviations beyond operational limits through BESS active-power import. A Quasi-Dynamic Simulation (QDS) investigation on the IEEE 34 bus test feeder integrated with rooftop solar PV using DIgSILENT PowerFactory demonstrates the methodology's effectiveness. It illustrates how strategic BESS locations can improve voltage profiles. Moreover, the outputs of the simulations provide recommendations for BESS sizing in terms of kW/kWh and the specific bus locations for optimizing voltage profiles in MV/LV distribution networks.

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Publication Details

Published
2024-10-07
DOI
https://doi.org/10.1109/powerafrica61624.2024.10759377
Primary Topic
Microgrid Control and Optimization
Type
article
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article

Location-Based Sizing of Battery Energy Storage for Voltage Regulation in MV/LV Distribution Networks

John Van Coller, Lesedi Masisi, Mapfumo Frank Mudimu
Microgrid Control and Optimization
article

Location-Based Sizing of Battery Energy Storage for Voltage Regulation in MV/LV Distribution Networks

John Van Coller, Lesedi Masisi, Mapfumo Frank Mudimu
article en

Abstract

The increasing integration of Distributed Energy Resources (DER) and excess generation export has brought about problems in maintaining voltage profiles in MV/LV distribution networks. Battery Energy Storage Systems (BESS) offer a promising solution by providing ancillary services, including voltage regulation. This paper presents a methodology for determining locations for BESS deployment in MV/LV distribution networks to improve voltage regulation. The proposed approach integrates time-series loads and renewable energy generation profiles to identify critical locations where BESS can effectively mitigate feeder overvoltage. A multi- objective mathematical optimization model utilizing Genetic Algorithms (GAs) to size BESS units is introduced, minimizing voltage deviations beyond operational limits through BESS active-power import. A Quasi-Dynamic Simulation (QDS) investigation on the IEEE 34 bus test feeder integrated with rooftop solar PV using DIgSILENT PowerFactory demonstrates the methodology's effectiveness. It illustrates how strategic BESS locations can improve voltage profiles. Moreover, the outputs of the simulations provide recommendations for BESS sizing in terms of kW/kWh and the specific bus locations for optimizing voltage profiles in MV/LV distribution networks.

University of the Witwatersrand (ZA)
Affordable and clean energy
Openalex Percentile: Top 70%
Microgrid Control and Optimization
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