Peng Qi^1,*, Yu Shang^2,*

Energy Engineering, Vol.118, No.3, pp. 727-736, 2021, DOI:10.32604/EE.2021.014203

Abstract With the increasingly prominent environmental problems of abandoned coal mines, this paper discussed the significance of environmental vulnerability assessment of abandoned coal mines. Environmental vulnerability assessment is essentially an assessment of environmental quality. At present, the research object of environmental impact assessment method and program of mine is mostly single factor. However, the impact of abandoned coal mine on the environment is multifaceted, which was summarized into nine prominent common problems. Based on these nine factors, the environmental vulnerability assessment model of abandoned coal mine based on multifactor evaluation was established by using the analytic hierarchy process (AHP) method, the… More >

Haibo Liu^1,*, Yujie Dong², Fuzhong Wang¹

Energy Engineering, Vol.118, No.3, pp. 679-689, 2021, DOI: 10.32604/EE.2021.014630

Abstract For the problems of nonlinearity, uncertainty and low prediction accuracy in the gas outburst prediction of coal mining face, the least squares support vector machine (LSSVM) is proposed to establish the prediction model. Firstly, considering the inertia coefficients as global parameters lacks the ability to improve the solution for the traditional particle swarm optimization (PSO), an improved PSO (IPSO) algorithm is introduced to adjust different inertia weights in updating the particle swarm and solve the fitness to stagnate. Secondly, the penalty factor and kernel function parameter of LSSVM are searched automatically, and the regression accuracy and generalization performance is enhanced… More >

Chunxue Gao^1,*, Yu Hao¹, Qiuxin Liu^1,2

Energy Engineering, Vol.118, No.3, pp. 667-678, 2021, DOI:10.32604/EE.2021.014703

Abstract Based on the characteristics of sewage from beauty salons, a simulation model of a small sewage source heat pump triple supply system that can be applied to such places is established to optimize the operating conditions of the system. The results show that with the increase of sewage temperature and flow, the performance of the system also increases. In summer conditions, the system provides cooling, recovers waste heat and condensed heat from sewage, with a COP value of 8.97; in winter conditions, the system heats and produces hot water, with a COP value of 2.44; in transitional seasons, only hot… More >

Wei Shi¹, Shusheng Xiong^1,*, Wei Li², Bohao Zhang³

Energy Engineering, Vol.118, No.3, pp. 643-654, 2021, DOI:10.32604/EE.2021.014643

Abstract 48 V lithium battery micro hybrid system is the most fuel economy vehicle which can be mass produced at present. However, with the irreversible internal resistance increase of the key component 48 V lithium battery, and the capacity continues to decline, the system performance deteriorate. Worst case could be the system not functional in the middle and later age of vehicle life cycle. This paper studies the feasibility of using 48 V super capacitor as the replacement to 48 V lithium battery, and uses a 12 V module of 48 V super capacitor as the traditional 12 V power supply,… More >

Anfeng Zhu, Zhao Xiao, Qiancheng Zhao^*

Energy Engineering, Vol.118, No.3, pp. 549-563, 2021, DOI:10.32604/EE.2021.014177

Abstract Due to the frequent changes of wind speed and wind direction, the accuracy of wind turbine (WT) power prediction using traditional data preprocessing method is low. This paper proposes a data preprocessing method which combines POT with DBSCAN (POT-DBSCAN) to improve the prediction efficiency of wind power prediction model. Firstly, according to the data of WT in the normal operation condition, the power prediction model of WT is established based on the Particle Swarm Optimization (PSO) Arithmetic which is combined with the BP Neural Network (PSO-BP). Secondly, the wind-power data obtained from the supervisory control and data acquisition (SCADA) system… More >

Mamdouh El Haj Assad^1,*, Ali Khosravi², Mohammad AlShabi³, Bassam Khuwaileh³, Abdul-Kadir Hamid⁴

Energy Engineering, Vol.118, No.3, pp. 447-458, 2021, DOI:10.32604/EE.2021.014590

Abstract In this work, a life cycle analysis is accomplished for flat plate solar collectors. The purpose of this investigation is to predict the energy consumption during the manufacturing processes that results in carbon dioxide emissions. Energy consumption and system efficiency enhancement will be studied and predicted. CES EduPack software is used to perform the analysis of the currently commercial system, and the suggested changes are implemented to increase the efficiency and make the comparison. Even though cost analysis is done, the priority of selection is given to the most energy conserving and environmentally friendly alternative. However, if the compared alternatives… More >

Tianyu Liu¹, Chang Wen^1,2,3,*, Wenyu Wang¹, Kai Yan³, Yongjun Xia⁴, Rui Li³, Juan Liu⁴, Yang Zhang¹

Energy Engineering, Vol.118, No.3, pp. 473-485, 2021, DOI:10.32604/EE.2021.014870

Abstract Pretreatment before biomass combustion is significant for its efficient utilization and that combined water washing and carbonization can be efficient. An agricultural processing residues sesame stalk was selected and carried out two pretreatments separately, i.e., water washing-torrefaction (W-T) and torrefaction-water washing (T-W), to explore the effect on the fuel properties, combustion characteristics and particulate matter (PM) emission. The obtained biochar was also combusted under air and oxy50 (CO₂:O₂ = 50:50) conditions for the sake of investigating the effect of pretreatment and combustion atmosphere. The results indicate that, W-T and T-W both not only have great effect on the improvement of… More >

Vin Cent Tai^1,*, Yong Chai Tan¹, Nor Faiza Abd Rahman¹, Chee Ming Chia², Mirzhakyp Zhakiya², Lip Huat Saw³

Energy Engineering, Vol.118, No.3, pp. 507-516, 2021, DOI:10.32604/EE.2021.014868

Abstract Accurate prediction of wind turbine power curve is essential for wind farm planning as it influences the expected power production. Existing methods require detailed wind turbine geometry for performance evaluation, which most of the time unattainable and impractical in early stage of wind farm planning. While significant amount of work has been done on fitting of wind turbine power curve using parametric and non-parametric models, little to no attention has been paid for power curve modelling that relates the wind turbine design information. This paper presents a novel method that employs artificial neural network to learn the underlying relationships between… More >

Vin Cent Tai^1,*, Yong Chai Tan¹, Nor Faiza Abd Rahman¹, Hui Xin Che², Chee Ming Chia², Lip Huat Saw³, Mohd Fozi Ali⁴

Energy Engineering, Vol.118, No.3, pp. 715-725, 2021, DOI:10.32604/EE.2021.014865

Abstract Electricity demand is also known as load in electric power system. This article presents a Long-Term Load Forecasting (LTLF) approach for Malaysia. An Artificial Neural Network (ANN) of 5-layer Multi-Layered Perceptron (MLP) structure has been designed and tested for this purpose. Uncertainties of input variables and ANN model were introduced to obtain the prediction for years 2022 to 2030. Pearson correlation was used to examine the input variables for model construction. The analysis indicates that Primary Energy Supply (PES), population, Gross Domestic Product (GDP) and temperature are strongly correlated. The forecast results by the proposed method (henceforth referred to as… More >

Jianguo Zhang¹, Biao Hu^2,*, Xiyuan Li¹, Hongxing Zhou², Zhixu Dai³, Yanlei Lu³, Deyang Wang²

Energy Engineering, Vol.118, No.3, pp. 605-614, 2021, DOI:10.32604/EE.2021.014655

Abstract To accurately predict the risk of coal and gas outburst and evaluate the reliability of desorption indexes of drilling cuttings (K₁ and ∆h₂) in No. 16 coal seam of Pingmei No. 12 coal mine, two sets of coal samples were selected from the target coal seams for proximate analyses, methane adsorption/desorption tests, and desorption indexes of drilling cuttings tests. The results indicated that the desorption volume in the initial stage of desorption is large, and increases slowly in the later stage. The methane desorption volume of PMD1 and PMD2 coal samples accounts for 15.14%–18.09% and 15.72%–18.17% respectively in the first… More >