Improved Lyrebird optimization for multi microgrid sectionalizing and cost efficient scheduling of distributed generation DOI Creative Commons
Karthik Nagarajan,

R. Arul,

Mohit Bajaj

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: May 19, 2025

The rising energy demand, substantial transmission and distribution losses, inconsistent power quality in remote regions highlight the urgent need for innovative solutions to ensure a stable electricity supply. Microgrids (MGs), integrated with distributed generation (DG), offer promising approach address these challenges by enabling localized generation, improved grid flexibility, enhanced reliability. This paper introduces Improved Lyrebird Optimization Algorithm (ILOA) optimal sectionalizing scheduling of multi-microgrid systems, aiming minimize costs active losses while ensuring system To enhance search efficiency, ILOA incorporates Levy Flight technique local search, which adaptive step sizes long-distance jumps, improving exploration-exploitation balance. Unlike conventional strategies that rely on fixed sizes, prevents premature convergence allowing algorithm escape optima explore solution space more effectively. Additionally, chaotic sine map is global capability, better diversity superior optimization performance compared traditional algorithms. Simulation studies are conducted modified 33-bus segmented into three independent microgrids. evaluated under single-objective scenarios (cost loss minimization) multi-objective framework combining both objectives. In optimization, achieves cost $19,254.64/hr 0.7118 kW loss, demonstrating marginal improvements over standard significant gains Genetic (GA) Jaya (JAYA). surpasses competing methods achieving $89,792.18/hr 10.26 loss. results indicate that, IEEE-33 bus without considering EIR, proposed savings approximately 0.0014%, 0.0041%, 0.657% operation LOA, JAYA, GA, respectively, when MG-1, MG-2, MG-3 operational. analysis real reduction demonstrates effectively minimizes 0.692%, 1.696%, 1.962% comparison operational conditions MG-3. reliability constraints based Energy Index Reliability (EIR) incorporated, further validating robustness approach. Considering highlights 1.319%, 2.069%, 2.134% scenario where active. confirm highly efficient reliable sectionalizing, showcasing its potential real-world applications such as dynamic economic dispatch demand response integration smart systems.

Language: Английский

Optimal energy managing and power scheduling of microgrid in grid-connected mode using modified multi-objective manta ray technique DOI
Ahmed Osama,

Dalia Allam,

Alaa Eldin Hussein Abozeid Ahmed

et al.

Energy Reports, Journal Year: 2025, Volume and Issue: 13, P. 4781 - 4799

Published: April 21, 2025

Language: Английский

Citations

0
Improved Lyrebird optimization for multi microgrid sectionalizing and cost efficient scheduling of distributed generation DOI Creative Commons
Karthik Nagarajan,

R. Arul,

Mohit Bajaj

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: May 19, 2025

The rising energy demand, substantial transmission and distribution losses, inconsistent power quality in remote regions highlight the urgent need for innovative solutions to ensure a stable electricity supply. Microgrids (MGs), integrated with distributed generation (DG), offer promising approach address these challenges by enabling localized generation, improved grid flexibility, enhanced reliability. This paper introduces Improved Lyrebird Optimization Algorithm (ILOA) optimal sectionalizing scheduling of multi-microgrid systems, aiming minimize costs active losses while ensuring system To enhance search efficiency, ILOA incorporates Levy Flight technique local search, which adaptive step sizes long-distance jumps, improving exploration-exploitation balance. Unlike conventional strategies that rely on fixed sizes, prevents premature convergence allowing algorithm escape optima explore solution space more effectively. Additionally, chaotic sine map is global capability, better diversity superior optimization performance compared traditional algorithms. Simulation studies are conducted modified 33-bus segmented into three independent microgrids. evaluated under single-objective scenarios (cost loss minimization) multi-objective framework combining both objectives. In optimization, achieves cost $19,254.64/hr 0.7118 kW loss, demonstrating marginal improvements over standard significant gains Genetic (GA) Jaya (JAYA). surpasses competing methods achieving $89,792.18/hr 10.26 loss. results indicate that, IEEE-33 bus without considering EIR, proposed savings approximately 0.0014%, 0.0041%, 0.657% operation LOA, JAYA, GA, respectively, when MG-1, MG-2, MG-3 operational. analysis real reduction demonstrates effectively minimizes 0.692%, 1.696%, 1.962% comparison operational conditions MG-3. reliability constraints based Energy Index Reliability (EIR) incorporated, further validating robustness approach. Considering highlights 1.319%, 2.069%, 2.134% scenario where active. confirm highly efficient reliable sectionalizing, showcasing its potential real-world applications such as dynamic economic dispatch demand response integration smart systems.

Language: Английский

Citations

0