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Jicai Guo^1,2, Xiaowen Song^1,2,*, Chang Liu^1,2, Yanfeng Zhang^1,2, Shijie Guo^1,2, Jianxin Wu^1,2, Chang Cai³, Qing’an Li^3,*
Energy Engineering, Vol.121, No.7, pp. 1739-1758, 2024, DOI:10.32604/ee.2024.048854
（This article belongs to the Special Issue: Wind Energy Development and Utilization)
Abstract In winter, wind turbines are susceptible to blade icing, which results in a series of energy losses and safe operation problems. Therefore, blade icing detection has become a top priority. Conventional methods primarily rely on sensor monitoring, which is expensive and has limited applications. Data-driven blade icing detection methods have become feasible with the development of artificial intelligence. However, the data-driven method is plagued by limited training samples and icing samples; therefore, this paper proposes an icing warning strategy based on the combination of feature selection (FS), eXtreme Gradient Boosting (XGBoost) algorithm, and exponentially weighted… More >

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Yang Xiong^1,2, Jianxin Liu^1,2,*, Xianhao Yi², Bangyan Xiao², Dan Wu², Biao Wu², Chunyu Gao²
Energy Engineering, Vol.121, No.7, pp. 1759-1780, 2024, DOI:10.32604/ee.2024.048536
（This article belongs to the Special Issue: Integrated Geology-Engineering Simulation and Optimizationfor Unconventional Oil and Gas Reservoirs)
Abstract In the heterogeneous reservoirs, CO₂ flooding easily leads to CO₂ gas channeling, which can seriously affect sweeping efficiency and reduce oil recovery. After thoroughly investigating the advantages and shortcomings of various CO₂ plugging technologies, this paper focuses on the feasibility of improving conventional water-alternating gas (WAG) through CO₂-responsive gel materials. Based on the different chemical reaction mechanisms between the unique chemical structure and CO₂, changes in the material’s physical and chemical properties can respond to CO₂. The feasibility of utilizing these property changes for CO₂-responsive plugging is explored. Various CO₂-responsive gels and gel nanoparticles have been extensively researched in More >

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153

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Quan Zhou^*, Haiyang Li
Energy Engineering, Vol.121, No.7, pp. 1781-1803, 2024, DOI:10.32604/ee.2024.049387
Abstract Renewable energy is becoming more attractive as traditional fossil fuels are rapidly depleted and expensive, and their use would release pollutants. Power systems that use both wind and solar energy are more reliable and efficient than those that utilize only one energy. Hybrid renewable energy systems (HRES) are viable for remote areas operating in standalone mode. This paper aims to present the state-of-the-art research on off-grid solar-wind hybrid energy systems over the last two decades. More than 1500 published articles extracted from the Web of Science are analyzed by bibliometric methods and processed by CiteSpace… More >

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123

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Fabien Mukundufite^1,*, Jean Marie Vianney Bikorimana¹, Alexander Kyaruzi Lugatona²
Energy Engineering, Vol.121, No.7, pp. 1805-1821, 2024, DOI:10.32604/ee.2024.051398
Abstract The governmental electric utility and the private sector are joining hands to meet the target of electrifying all households by 2024. However, the aforementioned goal is challenged by households that are scattered in remote areas. So far, Solar Home Systems (SHS) have mostly been applied to increase electricity access in rural areas. SHSs have continuous constraints to meet electricity demands and cannot run income-generating activities. The current research presents the feasibility study of electrifying Remera village with the smart microgrid as a case study. The renewable energy resources available in Remera are the key sources… More >

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113

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Jie Ma¹, Pengcheng Yue², Haozheng Yu¹, Yuqing Zhang³, Youwen Zhang¹, Cuiping Li³, Junhui Li^3,*, Wenwen Qin³, Yong Guo¹
Energy Engineering, Vol.121, No.7, pp. 1823-1846, 2024, DOI:10.32604/ee.2024.048225
Abstract In recent years, the proportion of installed wind power in the three north regions where wind power bases are concentrated is increasing, but the peak regulation capacity of the power grid in the three north regions of China is limited, resulting in insufficient local wind power consumption capacity. Therefore, this paper proposes a two-layer optimal scheduling strategy based on wind power consumption benefits to improve the power grid's wind power consumption capacity. The objective of the upper model is to minimize the peak-valley difference of the system load, which is mainly to optimize the system… More >

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Ying Qu¹, Jinhao Wang¹, Xueting Cheng¹, Jie Hao¹, Weiru Wang¹, Zhewen Niu², Yuxiang Wu^2,*
Energy Engineering, Vol.121, No.7, pp. 1847-1863, 2024, DOI:10.32604/ee.2024.048300
Abstract The data-driven transient stability assessment (TSA) of power systems can predict online real-time prediction by learning the temporal features before and after faults. However, the accuracy of the assessment is limited by the quality of the data and has weak transferability. Based on this, this paper proposes a method for TSA of power systems based on an improved extreme gradient boosting (XGBoost) model. Firstly, the gradient detection method is employed to remove noise interference while maintaining the original time series trend. On this basis, a focal loss function is introduced to guide the training of… More >

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119

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Feng Zhao, Guangdi Liu^*, Xiaoqiang Chen, Ying Wang
Energy Engineering, Vol.121, No.7, pp. 1865-1882, 2024, DOI:10.32604/ee.2024.048209
Abstract In light of the prevailing issue that the existing convolutional neural network (CNN) power quality disturbance identification method can only extract single-scale features, which leads to a lack of feature information and weak anti-noise performance, a new approach for identifying power quality disturbances based on an adaptive Kalman filter (KF) and multi-scale channel attention (MS-CAM) fused convolutional neural network is suggested. Single and composite-disruption signals are generated through simulation. The adaptive maximum likelihood Kalman filter is employed for noise reduction in the initial disturbance signal, and subsequent integration of multi-scale features into the conventional CNN… More >

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101

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Penghui Liu^1,2,*, Yaning Zhang¹, Yuxing Dai², Yanzhou Sun^1,3
Energy Engineering, Vol.121, No.7, pp. 1883-1901, 2024, DOI:10.32604/ee.2024.049318
Abstract Arc grounding faults occur frequently in the power grid with small resistance grounding neutral points. The existing arc fault identification technology only uses the fault line signal characteristics to set the identification index, which leads to detection failure when the arc zero-off characteristic is short. To solve this problem, this paper presents an arc fault identification method by utilizing integrated signal characteristics of both the fault line and sound lines. Firstly, the waveform characteristics of the fault line and sound lines under an arc grounding fault are studied. After that, the convex hull, gradient product,… More >

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100

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Yan Zhang¹, Bowen Du^2,*, Benren Pan¹, Guannan Wang¹, Guoqiang Xie¹, Tong Jiang²
Energy Engineering, Vol.121, No.7, pp. 1903-1920, 2024, DOI:10.32604/ee.2024.048718
Abstract During faults in a distribution network, the output power of a distributed generation (DG) may be uncertain. Moreover, the output currents of distributed power sources are also affected by the output power, resulting in uncertainties in the calculation of the short-circuit current at the time of a fault. Additionally, the impacts of such uncertainties around short-circuit currents will increase with the increase of distributed power sources. Thus, it is very important to develop a method for calculating the short-circuit current while considering the uncertainties in a distribution network. In this study, an affine arithmetic algorithm… More >

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115

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Sichen Li^1,2, Dehua Liu^1,2,*, Liang Cheng^1,2, Pan Ma^1,2
Energy Engineering, Vol.121, No.7, pp. 1921-1943, 2024, DOI:10.32604/ee.2024.049906
（This article belongs to the Special Issue: Hydraulic Fracturing Theory and Application for Geo-energy Development)
Abstract Due to the depletion of conventional energy reserves, there has been a global shift towards non-conventional energy sources. Shale oil and gas have emerged as key alternatives. These resources have dense and heterogeneous reservoirs, which require hydraulic fracturing to extract. This process depends on identifying optimal fracturing layers, also known as ‘sweet spots’. However, there is currently no uniform standard for locating these sweet spots. This paper presents a new model for evaluating fracturability that aims to address the current gap in the field. The model utilizes a hierarchical analysis approach and a mutation model, More >

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Xin Shen¹, Jiahao Li¹, Yujun Yin¹, Jianlin Tang^2,3,*, Weibin Lin^2,3, Mi Zhou^2,3
Energy Engineering, Vol.121, No.7, pp. 1945-1961, 2024, DOI:10.32604/ee.2024.048388
Abstract Advanced carbon emission factors of a power grid can provide users with effective carbon reduction advice, which is of immense importance in mobilizing the entire society to reduce carbon emissions. The method of calculating node carbon emission factors based on the carbon emissions flow theory requires real-time parameters of a power grid. Therefore, it cannot provide carbon factor information beforehand. To address this issue, a prediction model based on the graph attention network is proposed. The model uses a graph structure that is suitable for the topology of the power grid and designs a supervised More >

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87

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Xiaodan Wu¹, Jie Li^1,*, Yongbin Cai², Sihui Huang¹
Energy Engineering, Vol.121, No.7, pp. 1963-1990, 2024, DOI:10.32604/ee.2024.048477
Abstract Aiming at the problems of large energy consumption and serious pollution of winter heating existing in the rural buildings in Southern Xinjiang, a combined active-passive heating system was proposed, and the simulation software was used to optimize the parameters of the system, according to the parameters obtained from the optimization, a test platform was built and winter heating test was carried out. The simulation results showed that the thickness of the air layer of 75 mm, the total area of the vent holes of 0.24 m, and the thickness of the insulation layer of 120… More >

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108

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ARTICLE

Tengfei Li¹, Wenhui Zhang¹, Ke Mi¹, Qingming Lin¹, Shuangwei Zhao^2,*, Jiayi Song²
Energy Engineering, Vol.121, No.7, pp. 1991-2007, 2024, DOI:10.32604/ee.2024.049460
Abstract Aiming at the problem of energy storage unit failure in the spring operating mechanism of low voltage circuit breakers (LVCBs). A fault diagnosis algorithm based on an improved Sparrow Search Algorithm (ISSA) optimized Backpropagation Neural Network (BPNN) is proposed to improve the operational safety of LVCB. Taking the 1.5kV/4000A/75kA LVCB as an example. According to the current operating characteristics of the energy storage motor, fault characteristics are extracted based on Empirical Wavelet Transform (EWT). Traditional BPNN has problems such as difficulty adjusting network weights and thresholds, being sensitive to initial weights, and quickly falling into More >

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