Phase change materials (PCM) have great latent heat but suffer from low thermal conductivity. Then, in recent years, nano particles have been added to PCM to improve their thermophysical properties such as thermal conductivity. Effect of this nano particles on thermophysical properties of PCM has been a question and many experimental and numerical studies have been done to investigate them. Artificial intelligence-based approach can be a good candidate to predict thermophysical properties of nano enhance PCM (NEPCM). Then, in this study an artificial neural network (ANN) has been developed to predict the latent heat of the NEPCM.
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Farzad Jaliliantabar1,2,*, Rizalman Mamat3, Sudhakar Kumarasamy2,4,5
Energy Engineering, Vol.119, No.3, pp. 847-861, 2022, DOI:10.32604/ee.2022.019051
Abstract Thermal characteristics of phase change material (PCM) are important in design and utilization of thermal energy storage or other applications. PCMs have great latent heat but suffer from low thermal conductivity. Then, in recent years, nano particles have been added to PCM to improve their thermophysical properties such as thermal conductivity. Effect of this nano particles on thermophysical properties of PCM has been a question and many experimental and numerical studies have been done to investigate them. Artificial intelligence-based approach can be a good candidate to predict thermophysical properties of nano enhance PCM (NEPCM). Then, in this study an artificial… More >
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Chen Wang1, Cicilia Kemunto Mesa2,*, Samuel Bimenyimana1,3, Nathan Bogonko2, George Adwek4, Yiyi Mo1, Godwin Norense Osarumwense Asemota5,6, Changfu Yuan7, Yaowen Chen7, Changtai Li8, Etienne Ntagwirumugara9, Aphrodis Nduwamungu5
Energy Engineering, Vol.119, No.3, pp. 863-881, 2022, DOI:10.32604/ee.2022.019248
（This article belongs to this Special Issue: Advanced Materials and Technologies for Sustainable Energy)
Abstract Offsetting particulate matter emissions has become a critical global aim as there are concerted efforts to deal with environmental and energy poverty challenges. This study consists of investigations of computing emissions of particulate matter from biomass fuels in various atmospheres and temperatures. The laboratory setup included a fixed bed electric reactor and a particulate matter (PM) measuring machine interfaced with the flue gas from the fixed bed reactor combustion chamber. The experiments were conducted at seven different temperatures (600°C–1200°C) and six incremental oxygen concentrations (21%–100%). Five biomass types were studied; A-cornstalk, B-wood, C-wheat straw, D-Rice husk, E-Peanut shell, each pulverized… More >
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Jiacheng Yang1, Xiaohe Zhai1, Zhongfu Tan1,2,*, Zhenghao He1
Energy Engineering, Vol.119, No.3, pp. 883-906, 2022, DOI:10.32604/ee.2022.018033
（This article belongs to this Special Issue: Advances in Modern Electric Power and Energy Systems)
Abstract There is uncertainty in the electricity price of spot electricity market, which makes load aggregators undertake price risks for their agent users. In order to allow load aggregators to reduce the spot market price risk, scholars have proposed many solutions, such as improving the declaration decision-making model, signing power mutual insurance contracts, and adding energy storage and mobilizing demand-side resources to respond. In terms of demand side, calling flexible demand-side resources can be considered as a key solution. The user's power consumption rights (PCRs) are core contents of the demand-side resources. However, there have been few studies on the pricing… More >
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Zong Bi*, Weifeng Shi, Tiewei Song
Energy Engineering, Vol.119, No.3, pp. 907-928, 2022, DOI:10.32604/ee.2022.019627
（This article belongs to this Special Issue: Advances in Modern Electric Power and Energy Systems)
Abstract In the marine electric power system, the marine generators will be disturbed by the large change of loads or the fault of the power system. The marine generators usually installed power system stabilizers to damp power system oscillations through the excitation control. This paper proposes a novel method to obtain optimal parameter values for Power System Stabilizer (PSS) to suppress low-frequency oscillations in the marine electric power system. In this paper, a newly developed immune clone selection algorithm was improved from the three aspects of the adaptive incentive degree, vaccination, and adaptive mutation strategies. Firstly, the typical PSS implementation type… More >
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Guofeng Liu*, Can Zhang, Zhengyi Zhu, Xuyan Wang
Energy Engineering, Vol.119, No.3, pp. 929-946, 2022, DOI:10.32604/ee.2022.014816
（This article belongs to this Special Issue: Advances in Modern Electric Power and Energy Systems)
Abstract Due to the increasing power consumption of whole society and widely using of new non-linear and asymmetric electrical equipment, power quality assessment problem in the new period has attracted more and more attention. The mathematical essence of comprehensive assessment of power quality is a multi-attribute optimal decision-making problem. In order to solve the key problem of determining the indicator weight in the process of power quality assessment, a rough analytic hierarchy process (AHP) is proposed to aggregate the judgment opinions of multiple experts and eliminate the subjective effects of single expert judgment. Based on the advantage of extension analysis for… More >
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Chandrakant Dondariya*, D. K. Sakravdia
Energy Engineering, Vol.119, No.3, pp. 947-963, 2022, DOI:10.32604/ee.2022.019118
（This article belongs to this Special Issue: Advances in Modern Electric Power and Energy Systems)
Abstract This paper presents a newly developed proximity indicator for voltage stability assessment which can be used to predict critical real system load and voltages at various load buses at critical loading point. The proximity indicator varies almost parabolic with total real load demand and reaches orthogonally to real load axis. This relation has been utilized to predict critical loading point. It has been shown that two operating points are needed for estimating critical point and proper selection of operating points and variation of proximity indicator near collapse point highly affect the accuracy of estimation. Simulation is based on load flow… More >
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Haibin Cao1, Houqi Dong1, Yongjie Ren1, Yuqing Wang2,*, Na Li3, Ming Zeng1
Energy Engineering, Vol.119, No.3, pp. 965-984, 2022, DOI:10.32604/ee.2022.020051
（This article belongs to this Special Issue: Energy Systems Management and Climate Change)
Abstract As the proportion of renewable energy power generation continues to increase, the number of grid-connected microgrids is gradually increasing, and geographically adjacent microgrids can be interconnected to form a Micro-Grid Community (MGC). In order to reduce the operation and maintenance costs of a single micro grid and reduce the adverse effects caused by unnecessary energy interaction between the micro grid and the main grid while improving the overall economic benefits of the micro grid community, this paper proposes a bi-level energy management model with the optimization goal of maximizing the social welfare of the micro grid community and minimizing the… More >
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Tao Guo, Gang Tian, Zhimin Ao*, Xi Fang, Lili Wei, Fei Li
Energy Engineering, Vol.119, No.3, pp. 985-996, 2022, DOI:10.32604/ee.2022.018185
（This article belongs to this Special Issue: The Role of Artificial Intelligence for Modeling and Optimizing the Energy Systems )
Abstract Ground short circuit faults in current transmission lines are common in the power systems. In order to prevent the power system from aggravating the accident caused by short-circuit faults of transmission lines, a novel convolutional neural network (CNN) model is constructed to identify the short-circuit fault of the transmission line in the power system. The CNN model is mainly consisted of five convolutional layers, three max-pooling layers, one concatenate layer, one dropout layer, one fully connected layer, and a Softmax classifier. This method uses a fixed time window to intercept system short-circuit fault data, extracts the deep features of these… More >
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Kehinde Adeyeye1,*, Nelson Ijumba1,2, Jonathan Colton1,3
Energy Engineering, Vol.119, No.3, pp. 997-1015, 2022, DOI:10.32604/ee.2022.018677
（This article belongs to this Special Issue: Wind Energy Development and Utilization)
Abstract This paper posits that a low-speed wind turbine design is suitable for harnessing wind energy in Africa. Conventional wind turbines consisting of propeller designs are commonly used across the world. A major hurdle to utilizing wind energy in Africa is that conventional commercial wind turbines are designed to operate at wind speeds greater than those prevalent in most of the continent, especially in sub-Sahara Africa (SSA). They are heavy and expensive to purchase, install, and maintain. As a result, only a few countries in Africa have been able to include wind energy in their energy mix. In this paper, the… More >
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Fugang Dong, Yuqiao Zheng*, Hao Li, Zhengwen He
Energy Engineering, Vol.119, No.3, pp. 1017-1029, 2022, DOI:10.32604/ee.2022.020430
（This article belongs to this Special Issue: Wind Energy Development and Utilization)
Abstract This work takes the bionic bamboo tower (BBT) of 2 MW wind turbine as the target, and the non-dominated sorting genetic algorithm (NSGA-II) is utilized to optimize its structural parameters. Specifically, the objective functions are deformation and mass. Based on the correlation analysis, the target optimization parameters were determined. Furthermore, the Kriging model of the BBT was established through the Latin Hypercube Sampling Design (LHSD). Finally, the BBT structure is optimized with multiple objectives under the constraints of strength, natural frequency, and size. The comparison shows that the optimized BBT has an advantage in the Design Load Case (DLC). This… More >
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