Tariq Ali^1,2,*, Muhammad Ayaz^1,2, Mohammad Hijji², Imran Baig³, MI Mohamed Ershath⁴, Saleh Albelwi²

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 3839-3858, 2025, DOI:10.32604/cmes.2025.073169 - 23 December 2025

Abstract The integration of renewable energy sources into electricity markets presents significant challenges due to the inherent variability and uncertainty of power generation from wind, solar, and other renewables. Accurate forecasting is crucial for ensuring grid stability, optimizing market operations, and minimizing economic risks. This paper introduces a hybrid forecasting framework incorporating fractional-order statistical models, fractal-based feature engineering, and deep learning architectures to improve renewable energy forecasting accuracy. Fractional autoregressive integrated moving average (FARIMA) and fractional exponential smoothing (FETS) models are explored for capturing long-memory dependencies in energy time-series data. Additionally, multifractal detrended fluctuation analysis (MFDFA) More >

Yuqian Qi^*, Yanbo Che, Liangliang Liu, Jiayu Ni, Shangyuan Zhang

Energy Engineering, Vol.122, No.10, pp. 3999-4017, 2025, DOI:10.32604/ee.2025.068054 - 30 September 2025

Abstract The process of including renewable energy sources in power networks is moving quickly, so the need for innovative configuration solutions for grid-side ESS has grown. Among the new methods presented in this paper is GA-OCESE, which stands for Genetic Algorithm-based Optimization Configuration for Energy Storage in Electric Networks. This is one of the methods suggested in this study, which aims to enhance the sizing, positioning, and operational characteristics of structured ESS under dynamic grid conditions. Particularly, the aim is to maximize efficiency. A multiobjective genetic algorithm, the GA-OCESE framework, considers all these factors simultaneously. Besides… More >

Khairul Eahsun Fahim¹, Liyanage C. De Silva², Sk. A. Shezan^3,*, Md Ashraful Islam⁴, Md Shakib Hassan⁵, Hayati Yassin^1,*, Naveed Ahmad⁶

Energy Engineering, Vol.122, No.10, pp. 3985-3997, 2025, DOI:10.32604/ee.2025.066484 - 30 September 2025

Abstract Around the world, there has been a notable shift toward the use of renewable energy technology due to the growing demand for energy and the ongoing depletion of conventional resources, such as fossil fuels. Following this worldwide trend, Brunei’s government has initiated several strategic programs aimed at encouraging the establishment of energy from renewable sources in the nation’s energy mix. These initiatives are designed not only to support environmental sustainability but also to make energy from renewable sources increasingly competitive in comparison to more conventional energy sources like gas and oil, which have historically dominated… More >

Ali S. Alghamdi^1,*, Mohamed A. Zohdy², Saad Aldoihi^3,4

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1339-1370, 2024, DOI:10.32604/cmes.2024.048839 - 20 May 2024

Abstract In the contemporary era, the global expansion of electrical grids is propelled by various renewable energy sources (RESs). Efficient integration of stochastic RESs and optimal power flow (OPF) management are critical for network optimization. This study introduces an innovative solution, the Gaussian Bare-Bones Levy Cheetah Optimizer (GBBLCO), addressing OPF challenges in power generation systems with stochastic RESs. The primary objective is to minimize the total operating costs of RESs, considering four functions: overall operating costs, voltage deviation management, emissions reduction, voltage stability index (VSI) and power loss mitigation. Additionally, a carbon tax is included in… More >