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

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 Gamal, 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