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

Yukun Yang^*, Jun He, Wenfeng Chen, Zhi Li, Kun Chen

Energy Engineering, Vol.122, No.11, pp. 4653-4678, 2025, DOI:10.32604/ee.2025.068199 - 27 October 2025

Abstract To address the issues of unclear carbon responsibility attribution, insufficient renewable energy absorption, and simplistic carbon trading mechanisms in integrated energy systems, this paper proposes an electric-heat-hydrogen integrated energy system (EHH-IES) optimal scheduling model considering carbon emission stream (CES) and wind-solar accommodation. First, the CES theory is introduced to quantify the carbon emission intensity of each energy conversion device and transmission branch by defining carbon emission rate, branch carbon intensity, and node carbon potential, realizing accurate tracking of carbon flow in the process of multi-energy coupling. Second, a stepped carbon pricing mechanism is established to… More >

Aidong Zeng^1,2,*, Zirui Wang¹, Jiawei Wang ³, Sipeng Hao^1,2, Mingshen Wang⁴

Energy Engineering, Vol.122, No.9, pp. 3793-3816, 2025, DOI:10.32604/ee.2025.069410 - 26 August 2025

Abstract With the intensification of the energy crisis and the worsening greenhouse effect, the development of sustainable integrated energy systems (IES) has become a crucial direction for energy transition. In this context, this paper proposes a low-carbon economic dispatch strategy under the green hydrogen certificate trading (GHCT) and the ladder-type carbon emission trading (CET) mechanism, enabling the coordinated utilization of green and blue hydrogen. Specifically, a proton exchange membrane electrolyzer (PEME) model that accounts for dynamic efficiency characteristics, and a steam methane reforming (SMR) model incorporating waste heat recovery, are developed. Based on these models, a… More > Graphic Abstract

Yunfei Xu¹, Jianfeng Liu^1,*, Tianxing Sun¹, Heran Kang¹, Xiaoqing Hao²

Energy Engineering, Vol.122, No.8, pp. 3155-3176, 2025, DOI:10.32604/ee.2025.065753 - 24 July 2025

Abstract In order to promote the utilization level of new energy resources for local and efficient consumption, this paper introduces the biogas (BG) fermentation technology into the integrated energy system (IES). This initiative is to study the collaborative and optimal scheduling of IES with wind power (WP), photovoltaic (PV), and BG, while integrating carbon capture system (CCS) and power-to-gas (P2G) system. Firstly, the framework of collaborative operation of IES for BG-CCS-P2G is constructed. Secondly, the flexible scheduling resources of the source and load sides are fully exploited, and the collaborative operation mode of CCS-P2G is proposed… More >

Umit Cigdem Turhal¹, Yasemin Onal^1,*, Kutalmis Turhal²

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 2307-2332, 2025, DOI:10.32604/cmes.2025.064269 - 30 May 2025

Abstract The reliability and efficiency of photovoltaic (PV) systems are essential for sustainable energy production, requiring accurate fault detection to minimize energy losses. This study proposes a hybrid model integrating Neighborhood Components Analysis (NCA) with a Convolutional Neural Network (CNN) to improve fault detection and diagnosis. Unlike Principal Component Analysis (PCA), which may compromise class relationships during feature extraction, NCA preserves these relationships, enhancing classification performance. The hybrid model combines NCA with CNN, a fundamental deep learning architecture, to enhance fault detection and diagnosis capabilities. The performance of the proposed NCA-CNN model was evaluated against other More > Graphic Abstract

Zhiyuan Zhang¹, Yongjun Wu¹, Xiqin Li¹, Minghui Song¹, Guangwu Zhang², Ziren Wang^3,*, Wei Li³

Energy Engineering, Vol.122, No.5, pp. 1919-1948, 2025, DOI:10.32604/ee.2025.063178 - 25 April 2025

Abstract The park-level integrated energy system (PIES) is essential for achieving carbon neutrality by managing multi-energy supply and demand while enhancing renewable energy integration. However, current carbon trading mechanisms lack sufficient incentives for emission reductions, and traditional optimization algorithms often face challenges with convergence and local optima in complex PIES scheduling. To address these issues, this paper introduces a low-carbon dispatch strategy that combines a reward-penalty tiered carbon trading model with P2G-CCS integration, hydrogen utilization, and the Secretary Bird Optimization Algorithm (SBOA). Key innovations include: (1) A dynamic reward-penalty carbon trading mechanism with coefficients (μ = 0.2,… More >

Arpita Johri^1,2,*, Varnita Verma³, Mainak Basu^1,*

Energy Engineering, Vol.122, No.5, pp. 1887-1918, 2025, DOI:10.32604/ee.2025.062355 - 25 April 2025

Abstract The globe faces an urgent need to close the energy demand-supply gap. Addressing this difficulty requires constructing a Hybrid Renewable Energy System (HRES), which has proven to be the most appropriate solution. HRES allows for integrating two or more renewable energy resources, successfully addressing the issue of intermittent availability of non-conventional energy resources. Optimization is critical for improving the HRES’s performance parameters during implementation. This study focuses on HRES using solar and biomass as renewable energy supplies and appropriate energy storage technologies. However, energy fluctuations present a problem with the power quality of HRES. To… More > Graphic Abstract

Baxter L. M. Williams^1,*, Henri Croft¹, James Hunt¹, Josh Viloria¹, Nathan Sherman¹, James Oliver¹, Brody Green¹, Alexey Turchin², Juan B. García Martínez², Joshua M. Pearce^3,4, David Denkenberger^1,2,*

Energy Engineering, Vol.122, No.4, pp. 1265-1285, 2025, DOI:10.32604/ee.2025.063276 - 31 March 2025

Abstract Following global catastrophic infrastructure loss (GCIL), traditional electricity networks would be damaged and unavailable for energy supply, necessitating alternative solutions to sustain critical services. These alternative solutions would need to run without damaged infrastructure and would likely need to be located at the point of use, such as decentralized electricity generation from wood gas. This study explores the feasibility of using modified light duty vehicles to self-sustain electricity generation by producing wood chips for wood gasification. A 2004 Ford Falcon Fairmont was modified to power a woodchipper and an electrical generator. The vehicle successfully produced… More >

Lei Shen^1,2, Chutong Zhang², Yuwei Ge¹, Shanyun Gu¹, Qiang Gao¹, Wei Li¹, Jie Ji^2,*

Energy Engineering, Vol.122, No.4, pp. 1581-1602, 2025, DOI:10.32604/ee.2025.061010 - 31 March 2025

Abstract The rapid development and increased installed capacity of new energy sources such as wind and solar power pose new challenges for power grid fault diagnosis. This paper presents an innovative framework, the Intelligent Power Stability and Scheduling (IPSS) System, which is designed to enhance the safety, stability, and economic efficiency of power systems, particularly those integrated with green energy sources. The IPSS System is distinguished by its integration of a CNN-Transformer predictive model, which leverages the strengths of Convolutional Neural Networks (CNN) for local feature extraction and Transformer architecture for global dependency modeling, offering significant… More > Graphic Abstract

Zhihui Feng¹, Jun Zhang¹, Jun Lu¹, Zhongdan Zhang¹, Wangwang Bai¹, Long Ma¹, Haonan Lu², Jie Lin^2,*

Energy Engineering, Vol.122, No.4, pp. 1531-1560, 2025, DOI:10.32604/ee.2025.060795 - 31 March 2025

Abstract In the background of the low-carbon transformation of the energy structure, the problem of operational uncertainty caused by the high proportion of renewable energy sources and diverse loads in the integrated energy systems (IES) is becoming increasingly obvious. In this case, to promote the low-carbon operation of IES and renewable energy consumption, and to improve the IES anti-interference ability, this paper proposes an IES scheduling strategy that considers CCS-P2G and concentrating solar power (CSP) station. Firstly, CSP station, gas hydrogen doping mode and variable hydrogen doping ratio mode are applied to IES, and combined with… More >