A Mixed-Integer Convex Optimization Framework for Cost-Effective Conductor Selection in Radial Distribution Networks While Considering Load and Renewable Variations DOI Creative Commons
Oscar Danilo Montoya, Oscar David Flórez-Cediel, Luis Fernando Grisales-Noreña

et al.

Sci, Journal Year: 2025, Volume and Issue: 7(2), P. 72 - 72

Published: June 3, 2025

The optimal selection of conductors (OCS) in radial distribution networks is a critical aspect system planning, directly impacting both investment costs and energy losses. This paper proposed mixed-integer convex (MI-Convex) optimization framework to solve the OCS problem under balanced operating conditions, integrating conductor losses into single objective. formulation leveraged second-order conic constraints was solved using combination branch-and-bound interior-point methods. Numerical validations on standard 27-, 33-, 85-bus test systems confirmed effectiveness proposal. In 27-bus grid, MI-Convex approach achieved total cost $550,680.25, outperforming or matching best results reported by state-of-the-art metaheuristic algorithms, including vortex search algorithm (VSA), Newton’s (NMA), generalized normal optimizer (GNDO), tabu (TSA). method demonstrated consistent repeatable results, contrast variability observed heuristic techniques. Further analyses considering three-period daily load profiles led reductions up 27.6%, incorporating distributed renewable generation $705,197.06—approximately 22.97% lower than peak-load planning. Moreover, methodology proved computationally efficient, requiring only 1.84 s for 12.27 peak scenario 85-bus. These demonstrate superiority achieving globally optimal, reproducible, tractable solutions cost-effective selection.

Language: Английский

Technical and Optimization Insights into PV Penetration in Power Distribution Systems-based Wild Horse Algorithm: Real Cases on Egyptian Networks DOI Creative Commons
Asmaa Nasef, Mohammed H. Alqahtani,

Abdullah M. Shaheen

et al.

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104603 - 104603

Published: March 1, 2025

Language: Английский

Citations

2
A survey of Beluga whale optimization and its variants: Statistical analysis, advances, and structural reviewing DOI
Sang-Woong Lee, Amir Haider, Amir Masoud Rahmani

et al.

Computer Science Review, Journal Year: 2025, Volume and Issue: 57, P. 100740 - 100740

Published: March 3, 2025

Language: Английский

Citations

1
Performance Assessment of Modern Distribution Networks Conjoined with Electric Vehicles in Normal and Faulty Conditions DOI Creative Commons

Abdullah M. Shaheen,

Aya R. Ellien,

Ali M. El‐Rifaie

et al.

Scientific African, Journal Year: 2025, Volume and Issue: unknown, P. e02630 - e02630

Published: March 1, 2025

Language: Английский

Citations

1
Simultaneous Allocation of PV Systems and Shunt Capacitors in Medium Voltage Feeders Using Quadratic Interpolation Optimization‐Based Gaussian Mutation Operator DOI Creative Commons
Mona Gafar, Shahenda Sarhan, Abdullah M. Shaheen

et al.

International Journal of Energy Research, Journal Year: 2025, Volume and Issue: 2025(1)

Published: Jan. 1, 2025

This study introduces an enhanced version of quadratic interpolation optimization (QIO) merged with Gaussian mutation (GM) operator for optimizing photovoltaic (PV) units and capacitors within distribution systems, addressing practical considerations discrete nature capacitors. In this regard, the variations in power loading productions from PV sources are taken into consideration. The QIO is inspired by generalized (GQI) method mathematics GM that randomness solution to explore search space avoid premature convergence. proposed QIO‐GM tested on Egyptian standard IEEE demonstrating its effectiveness minimizing energy losses. Comparative studies against QIO, northern goshawk (NGO), optical microscope algorithm (OMA), as well other reported algorithms, validate QIO‐GM’s superior performance. Numerically, first system, designed achieves 2.5% improvement over a 4.4% NGO, 9.2% OMA, leading substantial reduction carbon dioxide (Co 2 ) emissions 110,823.886 79,402.82 kg, reflecting commendable 28.35% decrease. Similarly, second demonstrates significant Co 72,283.328 54,627.65 28.3% These results underscore not only losses but also contributing environmental benefits through reduced emissions.

Language: Английский

Citations

0
Photovoltaic Power Generation Forecasting With Bayesian Optimization and Stacked Ensemble Learning DOI Creative Commons

Mohamed A. Atiea,

Abdelrhman A. Abdelghaffar,

Houssem Ben Aribia

et al.

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104950 - 104950

Published: April 1, 2025

Language: Английский

Citations

0
Rapid, Precise Parameter Optimization and Performance Prediction for Multi-Diode Photovoltaic Model Using Puma Optimizer DOI Creative Commons
En-Jui Liu,

Yanhao Huang,

Chin‐Yu Lin

et al.

Energies, Journal Year: 2025, Volume and Issue: 18(11), P. 2855 - 2855

Published: May 29, 2025

Photovoltaic (PV) technology is essential for achieving net-zero emissions by 2050. PV system efficiency highly sensitive to irradiance, temperature, and shading. However, accurate parameter identification critical modeling, as models often exhibit multi-modal strongly coupled characteristics. In addition, commercial datasheets typically lack sufficient information, making precise extraction difficult limiting the accuracy of maximum power point predictions. To address these challenges, this research employs a novel metaheuristic algorithm called Puma Optimizer (PO) optimize parameters multiple models. The PO’s performance benchmarked against four advanced algorithms using convergence curves, error bars, boxplots evaluate its robustness. Results show that PO demonstrates strong adaptability reliable in optimization. Lastly, analyzes sensitivity help reduce computational resource usage. Visual analysis confirms optimization approach provides an effective practical solution enhanced energy management stable grid integration solar adoption continues expand.

Language: Английский

Citations

0
A Mixed-Integer Convex Optimization Framework for Cost-Effective Conductor Selection in Radial Distribution Networks While Considering Load and Renewable Variations DOI Creative Commons
Oscar Danilo Montoya, Oscar David Flórez-Cediel, Luis Fernando Grisales-Noreña

et al.

Sci, Journal Year: 2025, Volume and Issue: 7(2), P. 72 - 72

Published: June 3, 2025

The optimal selection of conductors (OCS) in radial distribution networks is a critical aspect system planning, directly impacting both investment costs and energy losses. This paper proposed mixed-integer convex (MI-Convex) optimization framework to solve the OCS problem under balanced operating conditions, integrating conductor losses into single objective. formulation leveraged second-order conic constraints was solved using combination branch-and-bound interior-point methods. Numerical validations on standard 27-, 33-, 85-bus test systems confirmed effectiveness proposal. In 27-bus grid, MI-Convex approach achieved total cost $550,680.25, outperforming or matching best results reported by state-of-the-art metaheuristic algorithms, including vortex search algorithm (VSA), Newton’s (NMA), generalized normal optimizer (GNDO), tabu (TSA). method demonstrated consistent repeatable results, contrast variability observed heuristic techniques. Further analyses considering three-period daily load profiles led reductions up 27.6%, incorporating distributed renewable generation $705,197.06—approximately 22.97% lower than peak-load planning. Moreover, methodology proved computationally efficient, requiring only 1.84 s for 12.27 peak scenario 85-bus. These demonstrate superiority achieving globally optimal, reproducible, tractable solutions cost-effective selection.

Language: Английский

Citations

0