K. Naga Venkata Siva¹, Damodhar Reddy², P. Krishna Murthy³, Kiran Kumar Pulamolu⁴, M. Dharani⁵, T. Venkatakrishnamoorthy^6,*

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.072982 - 27 December 2025

Abstract Conventional multilevel inverters often suffer from high harmonic distortion and increased design complexity due to the need for numerous power semiconductor components, particularly at elevated voltage levels. Addressing these shortcomings, this work presents a robust 15-level Packed U Cell (PUC) inverter topology designed for renewable energy and grid-connected applications. The proposed system integrates a sensor less proportional-resonant (PR) controller with an advanced carrier-based pulse width modulation scheme. This approach efficiently balances capacitor voltage, minimizes steady-state error, and strongly suppresses both zero and third-order harmonics resulting in reduced total harmonic distortion and enhanced voltage regulation. Additionally, More >

Zujun Ding, Qi Xiang, Chengyi Li, Mengyu Ma, Chutong Zhang, Xinfa Gu, Jiaming Shi, Hui Huang, Aoyun Xia, Wenjie Wang, Wan Chen, Ziluo Yu, Jie Ji^*

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.070442 - 27 December 2025

Abstract In order to address environmental pollution and resource depletion caused by traditional power generation, this paper proposes an adaptive iterative dynamic-balance optimization algorithm that integrates the Improved Dung Beetle Optimizer (IDBO) with Variational Mode Decomposition (VMD). The IDBO-VMD method is designed to enhance the accuracy and efficiency of wind-speed time-series decomposition and to effectively smooth photovoltaic power fluctuations. This study innovatively improves the traditional variational mode decomposition (VMD) algorithm, and significantly improves the accuracy and adaptive ability of signal decomposition by IDBO self-optimization of key parameters K and a. On this basis, Fourier transform technology… More >

Hauwau Kaoje^1,2, Adekunle Adeleke^2,3,*, Esther Anosike-Francis^2,3, Seun Jesuloluwa^2,3, Temitayo Ogedengbe^2,3, Hauwa Rasheed², Jude Okolie⁴

Journal of Renewable Materials, Vol.13, No.12, pp. 2375-2430, 2025, DOI:10.32604/jrm.2025.02025-0109 - 23 December 2025

Abstract The increasing need for sustainable energy and the environmental impacts of reliance on fossil fuels have sparked greater interest in biomass as a renewable energy source. This review provides an in-depth assessment of bio-oil and biochar generation through the pyrolysis of sawdust, a significant variety of lignocellulosic biomass. The paper investigates different thermochemical conversion methods, including fast, slow, catalytic, flash, and co-pyrolysis, while emphasizing their operational parameters, reactor designs, and effects on product yields. The influence of temperature, heating rate, and catalysts on enhancing the quality and quantity of bio-oil and biochar is thoroughly analyzed. More > Graphic Abstract

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 >

Ratan Kumar Das^1,*, Abhijit Date¹, Harun Chowdhury¹, Hamed Hassan²

Energy Engineering, Vol.122, No.12, pp. 4815-4835, 2025, DOI:10.32604/ee.2025.071727 - 27 November 2025

Abstract Bangladesh has achieved notable progress in expanding electricity access nationwide. Nonetheless, remote and topographically challenging regions such as the Chittagong Hill Tracts (CHT) continue to face coverage gaps due to grid extension difficulties. This research investigates the technical feasibility of micro-hydro power (MHP) systems as viable off-grid solutions for rural electrification in CHT. Field surveys conducted across various sites assessed available head and flow rates using GPS-based elevation measurements and portable flow meters. Seasonal fluctuations were factored into the analysis to ensure year-round operational viability. The study involved estimating power output, selecting appropriate turbine types… More > Graphic Abstract

Baiyue Song¹, Chenxi Zhang², Wei Zhang^2,*, Leiyu Wan²

Energy Engineering, Vol.122, No.12, pp. 4919-4945, 2025, DOI:10.32604/ee.2025.068971 - 27 November 2025

Abstract Hydrogen energy is a crucial support for China’s low-carbon energy transition. With the large-scale integration of renewable energy, the combination of hydrogen and integrated energy systems has become one of the most promising directions of development. This paper proposes an optimized scheduling model for a hydrogen-coupled electro-heat-gas integrated energy system (HCEHG-IES) using generative adversarial imitation learning (GAIL). The model aims to enhance renewable-energy absorption, reduce carbon emissions, and improve grid-regulation flexibility. First, the optimal scheduling problem of HCEHG-IES under uncertainty is modeled as a Markov decision process (MDP). To overcome the limitations of conventional deep… More >

Adel A.Abou El-Ela¹, Ragab A. El-Sehiemy^2,3,4,*, Abdallah Nazih¹, Asmaa A. Mubarak⁵, Eman S. Ali¹

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1349-1388, 2025, DOI:10.32604/cmes.2025.069507 - 26 November 2025

Abstract Distribution systems face significant challenges in maintaining power quality issues and maximizing renewable energy hosting capacity due to the increased level of photovoltaic (PV) systems integration associated with varying loading and climate conditions. This paper provides a comprehensive overview on the exit strategies to enhance distribution system operation, with a focus on harmonic mitigation, voltage regulation, power factor correction, and optimization techniques. The impact of passive and active filters, custom power devices such as dynamic voltage restorers (DVRs) and static synchronous compensators (STATCOMs), and grid modernization technologies on power quality is examined. Additionally, this paper… More >

Mahesh Kumar¹, Rahool Rai^2,*, Sudhakar Kumarasamy^2,3,4,*

Frontiers in Heat and Mass Transfer, Vol.23, No.5, pp. 1477-1493, 2025, DOI:10.32604/fhmt.2025.067933 - 31 October 2025

Abstract The increasing demand due to development and advancement in every field of life has caused the depletion of fossil fuels. This depleting fossil fuel reserve throughout the world has enforced to get energy from alternative/renewable sources. One of the economical ways to get energy is through the utilization of solar ponds. In this study, a mathematical model of a salt gradient solar pond under the Islamabad climatic conditions has been analyzed for the first time. The model uses a one-dimensional finite difference explicit method for optimization of different zone thicknesses. The model depicts that NCZ More >

Mir Majid Etghani¹, Homayoun Boodaghi^2,*

Energy Engineering, Vol.122, No.11, pp. 4385-4474, 2025, DOI:10.32604/ee.2025.070668 - 27 October 2025

Abstract Energy system optimization has become crucial for enhancing efficiency and environmental sustainability. This comprehensive review examines the synergistic application of Artificial Neural Networks (ANN) and Taguchi methods in optimizing diverse energy systems. While previous reviews have focused on these methods separately, this paper presents the first integrated analysis of both approaches across multiple energy applications. We systematically analyze their implementation in: Internal combustion engines, Thermal energy storage systems, Solar energy systems, Wind and tidal turbines, Heat exchangers, and hybrid energy systems. Our findings reveal that ANN models consistently achieve prediction accuracies exceeding 90% when compared More > Graphic Abstract

Wenbiao Li^1,2, Zhichong Cao^1,*, Zhengyu Li³, Wenbiao Tao³, Cheng Liu¹, Yuxin Shi³, Rundong Tian¹

Energy Engineering, Vol.122, No.11, pp. 4733-4754, 2025, DOI:10.32604/ee.2025.068683 - 27 October 2025

Abstract With the increasing penetration of renewable energy in power systems, grid structures and operational paradigms are undergoing profound transformations. When subjected to disturbances, the interaction between power electronic devices and dynamic loads introduces strongly nonlinear dynamic characteristics in grid voltage responses, posing significant threats to system security and stability. To achieve reliable short-term voltage stability assessment under large-scale renewable integration, this paper innovatively proposes a response-driven online assessment method based on energy function theory. First, energy modeling of system components is performed based on energy function theory, followed by analysis of energy interaction mechanisms during… More >