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  • Open Access

    ARTICLE

    Bibliometric Exploration of Conversion of Sugars to Furan Derivatives 2,5-Dimethylfuran by Catalytic Process

    Nuttida Chanhom1, Tossapon Katongtung2, Nakorn Tippayawong2,*

    Energy Engineering, Vol.121, No.12, pp. 3649-3665, 2024, DOI:10.32604/ee.2024.054862 - 22 November 2024

    Abstract This study investigated the conversion of sugars into furan derivatives, specifically 2,5-dimethylfuran, through catalytic processes using bibliographic analysis. This method evaluates scientific outcomes and impact within a specific field by analyzing data such as publication trends, references, collaborative models, leading authors, and institutions. The study utilized data from the reliable Scopus database and conducted analysis using the visualization of similarity (VOS) viewer program to gain in-depth insights into the current state of research on this topic. The findings revealed that “5 hydroxymethyl furfural” was the most used keyword, followed by “biomass” and “catalysis.” The research More >

  • Open Access

    ARTICLE

    Heuristic-Based Optimal Load Frequency Control with Offsite Backup Controllers in Interconnected Microgrids

    Aijia Ding, Tingzhang Liu*

    Energy Engineering, Vol.121, No.12, pp. 3735-3759, 2024, DOI:10.32604/ee.2024.054687 - 22 November 2024

    Abstract The primary factor contributing to frequency instability in microgrids is the inherent intermittency of renewable energy sources. This paper introduces novel dual-backup controllers utilizing advanced fractional order proportional integral derivative (FOPID) controllers to enhance frequency and tie-line power stability in microgrids amid increasing renewable energy integration. To improve load frequency control, the proposed controllers are applied to a two-area interconnected microgrid system incorporating diverse energy sources, such as wind turbines, photovoltaic cells, diesel generators, and various storage technologies. A novel meta-heuristic algorithm is adopted to select the optimal parameters of the proposed controllers. The efficacy… More >

  • Open Access

    REVIEW

    A Critical Review of Active Distribution Network Reconfiguration: Concepts, Development, and Perspectives

    Bo Yang1, Rui Zhang1, Jie Zhang2, Xianlong Cheng2, Jiale Li3, Yimin Zhou1, Yuanweiji Hu1, Bin He1, Gongshuai Zhang4, Xiuping Du4, Si Ji5, Yiyan Sang6, Zhengxun Guo7,8,*

    Energy Engineering, Vol.121, No.12, pp. 3487-3547, 2024, DOI:10.32604/ee.2024.054662 - 22 November 2024

    Abstract In recent years, the large-scale grid connection of various distributed power sources has made the planning and operation of distribution grids increasingly complex. Consequently, a large number of active distribution network reconfiguration techniques have emerged to reduce system losses, improve system safety, and enhance power quality via switching switches to change the system topology while ensuring the radial structure of the network. While scholars have previously reviewed these methods, they all have obvious shortcomings, such as a lack of systematic integration of methods, vague classification, lack of constructive suggestions for future study, etc. Therefore, this… More >

  • Open Access

    ARTICLE

    Photovoltaic Power Generation Power Prediction under Major Extreme Weather Based on VMD-KELM

    Yuxuan Zhao1,2,*, Bo Wang1, Shu Wang1, Wenjun Xu2, Gang Ma2

    Energy Engineering, Vol.121, No.12, pp. 3711-3733, 2024, DOI:10.32604/ee.2024.054032 - 22 November 2024

    Abstract The output of photovoltaic power stations is significantly affected by environmental factors, leading to intermittent and fluctuating power generation. With the increasing frequency of extreme weather events due to global warming, photovoltaic power stations may experience drastic reductions in power generation or even complete shutdowns during such conditions. The integration of these stations on a large scale into the power grid could potentially pose challenges to system stability. To address this issue, in this study, we propose a network architecture based on VMD-KELM for predicting the power output of photovoltaic power plants during severe weather… More >

  • Open Access

    ARTICLE

    Reinforcement Learning Model for Energy System Management to Ensure Energy Efficiency and Comfort in Buildings

    Inna Bilous1, Dmytro Biriukov1, Dmytro Karpenko2, Tatiana Eutukhova2, Oleksandr Novoseltsev2,*, Volodymyr Voloshchuk1

    Energy Engineering, Vol.121, No.12, pp. 3617-3634, 2024, DOI:10.32604/ee.2024.051684 - 22 November 2024

    Abstract This article focuses on the challenges of modeling energy supply systems for buildings, encompassing both methods and tools for simulating thermal regimes and engineering systems within buildings. Enhancing the comfort of living or working in buildings often necessitates increased consumption of energy and material, such as for thermal upgrades, which consequently incurs additional economic costs. It is crucial to acknowledge that such improvements do not always lead to a decrease in total pollutant emissions, considering emissions across all stages of production and usage of energy and materials aimed at boosting energy efficiency and comfort in… More > Graphic Abstract

    Reinforcement Learning Model for Energy System Management to Ensure Energy Efficiency and Comfort in Buildings

  • Open Access

    ARTICLE

    Slag Characteristics of Biomass Pellet Fuels with Different Additives to Tobacco-Stalk for Tobacco Curing Heating

    Jianan Wang1,*, Yikuan Fan2, Weidong Duan3, Zhaopeng Song1

    Energy Engineering, Vol.121, No.11, pp. 3401-3415, 2024, DOI:10.32604/ee.2024.055158 - 21 October 2024

    Abstract Since pure tobacco stalk (TS) biomass pellet fuels tend to slag, five anti-slagging agents were added to the crushed TS to obtain a pellet fuel that could be used in biomass burners to provide heat for tobacco curing. The obtained results revealed that the main component of TS pellet fuel was K2Si2O5. During fuel combustion process, additives generated higher melting point silicate compounds by Al–K, Ca–K, and Ca–K elemental structures to replace single K elemental structure of TS, enhancing the anti-slagging efficiency of the pellet fuel from 21.63% to 78.29% and promoting the precipitation of K, More >

  • Open Access

    ARTICLE

    Multi-Lever Early Warning for Wind and Photovoltaic Power Ramp Events Based on Neural Network and Fuzzy Logic

    Huan Ma1, Linlin Ma2, Zengwei Wang3,*, Zhendong Li3, Yuanzhen Zhu1, Yutian Liu3

    Energy Engineering, Vol.121, No.11, pp. 3133-3160, 2024, DOI:10.32604/ee.2024.055051 - 21 October 2024

    Abstract With the increasing penetration of renewable energy in power system, renewable energy power ramp events (REPREs), dominated by wind power and photovoltaic power, pose significant threats to the secure and stable operation of power systems. This paper presents an early warning method for REPREs based on long short-term memory (LSTM) network and fuzzy logic. First, the warning levels of REPREs are defined by assessing the control costs of various power control measures. Then, the next 4-h power support capability of external grid is estimated by a tie line power prediction model, which is constructed based More > Graphic Abstract

    Multi-Lever Early Warning for Wind and Photovoltaic Power Ramp Events Based on Neural Network and Fuzzy Logic

  • Open Access

    ARTICLE

    Probabilistic Calculation of Tidal Currents for Wind Powered Systems Using PSO Improved LHS

    Hongsheng Su, Shilin Song*, Xingsheng Wang

    Energy Engineering, Vol.121, No.11, pp. 3289-3303, 2024, DOI:10.32604/ee.2024.054643 - 21 October 2024

    Abstract This paper introduces the Particle Swarm Optimization (PSO) algorithm to enhance the Latin Hypercube Sampling (LHS) process. The key objective is to mitigate the issues of lengthy computation times and low computational accuracy typically encountered when applying Monte Carlo Simulation (MCS) to LHS for probabilistic trend calculations. The PSO method optimizes sample distribution, enhances global search capabilities, and significantly boosts computational efficiency. To validate its effectiveness, the proposed method was applied to IEEE34 and IEEE-118 node systems containing wind power. The performance was then compared with Latin Hypercubic Important Sampling (LHIS), which integrates significant sampling More >

  • Open Access

    ARTICLE

    Seasonal Short-Term Load Forecasting for Power Systems Based on Modal Decomposition and Feature-Fusion Multi-Algorithm Hybrid Neural Network Model

    Jiachang Liu1,*, Zhengwei Huang2, Junfeng Xiang1, Lu Liu1, Manlin Hu1

    Energy Engineering, Vol.121, No.11, pp. 3461-3486, 2024, DOI:10.32604/ee.2024.054514 - 21 October 2024

    Abstract To enhance the refinement of load decomposition in power systems and fully leverage seasonal change information to further improve prediction performance, this paper proposes a seasonal short-term load combination prediction model based on modal decomposition and a feature-fusion multi-algorithm hybrid neural network model. Specifically, the characteristics of load components are analyzed for different seasons, and the corresponding models are established. First, the improved complete ensemble empirical modal decomposition with adaptive noise (ICEEMDAN) method is employed to decompose the system load for all four seasons, and the new sequence is obtained through reconstruction based on the… More >

  • Open Access

    ARTICLE

    Improved Strategy of Grid-Forming Virtual Synchronous Generator Based on Transient Damping

    Lei Zhang1, Rongliang Shi1,2,*, Junhui Li2, Yannan Yu1, Yu Zhang1

    Energy Engineering, Vol.121, No.11, pp. 3181-3197, 2024, DOI:10.32604/ee.2024.054485 - 21 October 2024

    Abstract The grid-forming virtual synchronous generator (GFVSG) not only employs a first-order low-pass filter for virtual inertia control but also introduces grid-connected active power (GCAP) dynamic oscillation issues, akin to those observed in traditional synchronous generators. In response to this, an improved strategy for lead-lag filter based GFVSG (LLF-GFVSG) is presented in this article. Firstly, the grid-connected circuit structure and control principle of typical GFVSG are described, and a closed-loop small-signal model for GCAP in GFVSG is established. The causes of GCAP dynamic oscillation of GFVSG under the disturbances of active power command as well as More >

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