International Journal of Energy Research, Год журнала: 2025, Номер 2025(1)

Опубликована: Янв. 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.

Язык: Английский