Tamer Mohamed Elsaid Elkhodragy
Asst. Professor
Optimal Size and Location of Photovoltaic and Battery Energy Storage System with Reactive Load Integration Using a Hybrid Algorithm
25th International Middle East Power System Conference (MEPCON) • 2024
Publication Information
Authors
Manar A. Khalil, Tamer M. Elkhodragy , Waleed A.A. Salem
Keywords
Photovoltaic, Power Factor, Voltage Stability
Indices, Hybrid Algorithms
Journal
25th International Middle East Power System Conference (MEPCON)
Publisher
IEEE Advancing Technology for Humanity
Volume
25th
Issue
Not Available
Pages
6
publication.type
International
Paper Link
Not Available
Supplementary Materials
Not Available
Abstract
This study introduces a novel hybrid algorithm
designed to optimize the location and sizing (OLS) of distributed
generation (DG) sources in a distribution system (DS),
considering the impact of reactive load integration. By
combining the Novel Line Stability Index (NLSI) with the
Artificial Rabbit Optimization (ARO) algorithm, the approach
strategically identifies the OLS for photovoltaic (PV) and
battery energy storage systems (BESS) across different seasonal
load scenarios. The main objectives are boosting voltage
stability, refining voltage profiles, and minimizing power losses
(PL). Applied to the IEEE 33-bus DS, the hybrid algorithm
demonstrates remarkable improvements, achieving up to a
95.16% reduction in energy losses and a 99.65% reduction in
voltage deviation. These impressive results underscore the
algorithm's ability to enhance system efficiency significantly
over conventional techniques. Additionally, this study highlights
system behavior under atypical conditions with reactive load
integration, offering a robust and effective solution for
improving DS performance in challenging scenarios
designed to optimize the location and sizing (OLS) of distributed
generation (DG) sources in a distribution system (DS),
considering the impact of reactive load integration. By
combining the Novel Line Stability Index (NLSI) with the
Artificial Rabbit Optimization (ARO) algorithm, the approach
strategically identifies the OLS for photovoltaic (PV) and
battery energy storage systems (BESS) across different seasonal
load scenarios. The main objectives are boosting voltage
stability, refining voltage profiles, and minimizing power losses
(PL). Applied to the IEEE 33-bus DS, the hybrid algorithm
demonstrates remarkable improvements, achieving up to a
95.16% reduction in energy losses and a 99.65% reduction in
voltage deviation. These impressive results underscore the
algorithm's ability to enhance system efficiency significantly
over conventional techniques. Additionally, this study highlights
system behavior under atypical conditions with reactive load
integration, offering a robust and effective solution for
improving DS performance in challenging scenarios