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  • Open Access

    ARTICLE

    Numerical Investigation on Air Distribution of Cabinet with Backplane Air Conditioning in Data Center

    Yiming Rongyang1, Chengyu Ji1, Xiangdong Ding2,*, Jun Gao1, Jianjian Wei2,3

    Frontiers in Heat and Mass Transfer, Vol.23, No.2, pp. 685-701, 2025, DOI:10.32604/fhmt.2025.063785 - 25 April 2025

    Abstract The effect of gradient exhaust strategy and blind plate installation on the inhibition of backflow and thermal stratification in data center cabinets is systematically investigated in this study through numerical methods. The validated Re-Normalization Group (RNG) k-ε turbulence model was used to analyze airflow patterns within cabinet structures equipped with backplane air conditioning. Key findings reveal that server-generated thermal plumes induce hot air accumulation at the cabinet apex, creating a 0.8°C temperature elevation at the top server’s inlet compared to the ideal situation (23°C). Strategic increases in backplane fan exhaust airflow rates reduce server 1’s inlet… More >

  • Open Access

    ARTICLE

    Optimizing Solar Air Heater Performance Using Perforated V-Shaped Barriers with Varied Geometric Designs

    Sajjad Tariq A. Shafi, Mohammed K. Al-Saadi, Ameer Abed Jaddoa*

    Frontiers in Heat and Mass Transfer, Vol.23, No.2, pp. 703-719, 2025, DOI:10.32604/fhmt.2025.063118 - 25 April 2025

    Abstract To improve the heat transfer rate and thermal performance of the solar air heater due to low efficiency, new techniques, such as artificial roughness, barriers, and obstacles, should be used to increase the heat exchange between the fluid and the absorber. In this research, perforated V-shaped blockages with new geometric shapes, which are circular, hexagonal, square, rectangular, and triangular, were used. They were fixed on the absorber plate inside the channel with dimensions of 1.5 m × 0.5 m × 0.05 m, which increased the exit temperature of the air passing through the channel. The… More >

  • Open Access

    ARTICLE

    Stackelberg Game for Bilateral Transactions between Energy Storage and Wind Farms Considering the Day-Ahead Electricity Market

    Xingxu Zhu1, Guiqing Zhao1, Gangui Yan1, Junhui Li1,*, Hongda Dong2, Chenggang Li2

    Energy Engineering, Vol.122, No.5, pp. 1645-1668, 2025, DOI:10.32604/ee.2025.063192 - 25 April 2025

    Abstract The participation of wind farms in the former energy market faces challenges such as power fluctuations and energy storage construction costs. To this end, this paper proposes a joint energy storage operation scheme for multiple wind farms based on a leasing model, which assists wind farms in bidding for participation in the former energy market through leasing services, thereby enhancing energy storage efficiency and maximizing economic benefits. In this paper, based on the Weibull probability distribution to portray the uncertainty of wind power, and considering the lifetime capacity loss caused by charging and discharging of… More > Graphic Abstract

    Stackelberg Game for Bilateral Transactions between Energy Storage and Wind Farms Considering the Day-Ahead Electricity Market

  • Open Access

    ARTICLE

    Environmental and Economic Optimization of Multi-Source Power Real-Time Dispatch Based on DGADE-HDJ

    Bin Jiang1, Houbin Wang2,*

    Energy Engineering, Vol.122, No.5, pp. 2001-2057, 2025, DOI:10.32604/ee.2025.062765 - 25 April 2025

    Abstract Considering the special features of dynamic environment economic dispatch of power systems with high dimensionality, strong coupling, nonlinearity, and non-convexity, a GA-DE multi-objective optimization algorithm based on dual-population pseudo-parallel genetic algorithm-differential evolution is proposed in this paper. The algorithm is based on external elite archive and Pareto dominance, and it adopts the cooperative co-evolution mechanism of differential evolution and genetic algorithm. Average entropy and cubic chaotic mapping initialization strategies are proposed to increase population diversity. In the proposed method, we analyze the distribution of neighboring solutions and apply a new Pareto solution set pruning approach.… More >

  • Open Access

    ARTICLE

    Energy-Efficient Air Conditioning System with Combined a Ceiling Fan for Thermal Comfort in an Office

    Linlan Chang1, Win-Jet Luo1,2, Indra Permana2, Bowo Yuli Prasetyo3, Alya Penta Agharid1, Fujen Wang2,*

    Energy Engineering, Vol.122, No.5, pp. 1771-1787, 2025, DOI:10.32604/ee.2025.062209 - 25 April 2025

    Abstract Heating, Ventilation, and Air Conditioning (HVAC) systems are critical for maintaining thermal comfort in office environments which also crucial for occupant well-being and productivity. This study investigates the impact of integrating ceiling fans with higher air conditioning setpoints on thermal comfort and energy efficiency in office environments. Field measurements and questionnaire surveys were conducted to evaluate thermal comfort and energy-saving potential under varying conditions. Results show that increasing the AC setpoint from 25°C to 27°C, combined with ceiling fan operation, reduced power consumption by 10%, achieving significant energy savings. Survey data confirmed that 85% of… More >

  • Open Access

    ARTICLE

    Short-Term Prediction of Photovoltaic Power Based on Improved CNN-LSTM and Cascading Learning

    Feng Guo, Chen Yang*, Dezhong Xia, Jingxiang Xu

    Energy Engineering, Vol.122, No.5, pp. 1975-1999, 2025, DOI:10.32604/ee.2025.062035 - 25 April 2025

    Abstract Short-term photovoltaic (PV) power forecasting plays a crucial role in enhancing the stability and reliability of power grid scheduling. To address the challenges posed by complex environmental variables and difficulties in modeling temporal features in PV power prediction, a short-term PV power forecasting method based on an improved CNN-LSTM and cascade learning strategy is proposed. First, Pearson correlation coefficients and mutual information are used to select representative features, reducing the impact of redundant features on model performance. Then, the CNN-LSTM network is designed to extract local features using CNN and learn temporal dependencies through LSTM,… More > Graphic Abstract

    Short-Term Prediction of Photovoltaic Power Based on Improved CNN-LSTM and Cascading Learning

  • Open Access

    ARTICLE

    Optimal Evaluation of Photovoltaic Consumption Schemes in Distribution Networks Based on BASS Model for Photovoltaic Installed Capacity Prediction

    Chenyang Fu*, Xinghua Wang, Zilv Li, Xixian Liu, Xiongfei Zhang, Zhuoli Zhao

    Energy Engineering, Vol.122, No.5, pp. 1805-1821, 2025, DOI:10.32604/ee.2025.061172 - 25 April 2025

    Abstract With the large-scale promotion of distributed photovoltaics, new challenges have emerged in the photovoltaic consumption within distribution networks. Traditional photovoltaic consumption schemes have primarily focused on static analysis. However, as the scale of photovoltaic power generation devices grows and the methods of integration diversify, a single consumption scheme is no longer sufficient to meet the actual needs of current distribution networks. Therefore, this paper proposes an optimal evaluation method for photovoltaic consumption schemes based on BASS model predictions of installed capacity, aiming to provide an effective tool for generating and evaluating photovoltaic consumption schemes in… More > Graphic Abstract

    Optimal Evaluation of Photovoltaic Consumption Schemes in Distribution Networks Based on BASS Model for Photovoltaic Installed Capacity Prediction

  • Open Access

    ARTICLE

    A Two-Stage Feature Extraction Approach for Green Energy Consumers in Retail Electricity Markets Using Clustering and TF–IDF Algorithms

    Wei Yang1, Weicong Tan1, Zhijian Zeng1, Ren Li1, Jie Qin1, Yuting Xie1, Yongjun Zhang2, Runting Cheng2, Dongliang Xiao2,*

    Energy Engineering, Vol.122, No.5, pp. 1697-1713, 2025, DOI:10.32604/ee.2025.060571 - 25 April 2025

    Abstract The rapid development of electricity retail market has prompted an increasing number of electricity consumers to sign green electricity contracts with retail electricity companies, which poses greater challenges for the market service for green energy consumers. This study proposed a two-stage feature extraction approach for green energy consumers leveraging clustering and term frequency-inverse document frequency (TF–IDF) algorithms within a knowledge graph framework to provide an information basis that supports the green development of the retail electricity market. First, the multi-source heterogeneous data of green energy consumers under an actual market environment is systematically introduced and… More >

  • Open Access

    ARTICLE

    Design and Development of a Small-Scale Green Hydrogen Vehicle: Hydrogen Consumption Analysis under Varying Loads for Zero-Emission Transport

    Perry Yang Tchie Hunn1, Hadi Nabipour Afrouzi2,*

    Energy Engineering, Vol.122, No.5, pp. 1789-1804, 2025, DOI:10.32604/ee.2025.060124 - 25 April 2025

    Abstract With growing interest in its potential applications across both stationary and transportation sectors, hydrogen has emerged as a promising alternative for environmentally responsible power generation. By replacing traditional fuels, hydrogen can significantly reduce greenhouse gas emissions in the transportation sector. This study focuses on the design and downsizing of a green hydrogen fuel cell car, aiming to scale the concept for larger vehicles. Key components, including fuel cells, electrolysers, and solar panels, were evaluated through extensive laboratory testing. The findings reveal that variations in sunlight impact the solar panel’s hydrogen production rate, with differences of… More > Graphic Abstract

    Design and Development of a Small-Scale Green Hydrogen Vehicle: Hydrogen Consumption Analysis under Varying Loads for Zero-Emission Transport

  • Open Access

    REVIEW

    Nanocellulose-Based Adhesives for Sustainable Wood-Polymer Composites: Recent Advancement and Future Perspective

    Amelia Hariry1, Efri Mardawati1,2,*, Apri Heri Iswanto3, Tati Karliati4, Lukmanul Hakim Zaini5,6,*, Muhammad Adly Rahandi Lubis2,7

    Journal of Renewable Materials, Vol.13, No.4, pp. 773-798, 2025, DOI:10.32604/jrm.2025.058359 - 21 April 2025

    Abstract Nanocellulose-based adhesives are gaining attention as a viable alternative to conventional adhesives, offering benefits such as cost-effectiveness and scalability, which make them suitable for various sectors, including cosmetics, pharmaceuticals, biodegradable products, and as reinforcing agents in natural adhesives. This review delves into the current advancements in nanocellulose-based adhesive solutions for sustainable and eco-friendly wood composites, using systematic review methods and bibliometric analysis. Data were collected from the Scopus database, spanning from 2007 to 2024, and visualized using VOSviewer to highlight emerging trends in the field. The analysis revealed that nanocellulose shows great potential as a More >

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