N. Domingues, Jorge Mendonça Costa, Rui Miguel Paulo
Over the years, and despite the energy efficiency measures and possibilities, there has been an increase in energy consumption worldwide. However, the resources and primary energies are limited and short stocked, and the energy production technologies have environmental and social impacts on production and exploration. One alternative is to reuse the energy waste in the processes. In this study, a trigeneration system in a large scale out of grid consumption is analyzed and a technical-economic feasibility is elaborated. The case study is based on an isolated tropical island. For the baseline scenario, two traditional energy production systems that does not contain energy recovery in the engines are assumed to be implemented. For the improved scenario, a trigeneration system absorption chiller is analyzed. An economic analysis of this project was given the indicators obtained, it was possible to conclude that the use of a trigeneration system on an isolated large scale out of grid energy consumption system, is feasible and preferable.
{"title":"Technical-Economic Feasibility Study of a Tri-Generation System in an Isolated Tropical Island","authors":"N. Domingues, Jorge Mendonça Costa, Rui Miguel Paulo","doi":"10.4018/ijeoe.309416","DOIUrl":"https://doi.org/10.4018/ijeoe.309416","url":null,"abstract":"Over the years, and despite the energy efficiency measures and possibilities, there has been an increase in energy consumption worldwide. However, the resources and primary energies are limited and short stocked, and the energy production technologies have environmental and social impacts on production and exploration. One alternative is to reuse the energy waste in the processes. In this study, a trigeneration system in a large scale out of grid consumption is analyzed and a technical-economic feasibility is elaborated. The case study is based on an isolated tropical island. For the baseline scenario, two traditional energy production systems that does not contain energy recovery in the engines are assumed to be implemented. For the improved scenario, a trigeneration system absorption chiller is analyzed. An economic analysis of this project was given the indicators obtained, it was possible to conclude that the use of a trigeneration system on an isolated large scale out of grid energy consumption system, is feasible and preferable.","PeriodicalId":43245,"journal":{"name":"International Journal of Energy Optimization and Engineering","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42929317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Jaiswal, Ibrahim Abdulhamid Datti, Mustapha Muhammad Saidu, K. J. Chitra
The major aim of DG optimal placement is obtaining the best DGs units sizes and locations so as to have optimum operation and planning of the distribution network system while considering DG capacity constraint. This paper addresses the issues related to the improvement of voltage profile and power loss reduction by integrating DG units. The technique was applied to optimally placed optimum DG unit size in distribution systems for the improvement of candidate bus voltage and reduction of power loss in the system. The technique proposed was simulated on IEEE-10 bus and IEEE-13 bus standard test system, and the obtained results show that the proposed method is strong and effective for optimal placement of DG units.
{"title":"Optimal Placement of Micro Distribution Generator in Micro-Grid for Loss Minimization Using PSO","authors":"S. Jaiswal, Ibrahim Abdulhamid Datti, Mustapha Muhammad Saidu, K. J. Chitra","doi":"10.4018/ijeoe.309418","DOIUrl":"https://doi.org/10.4018/ijeoe.309418","url":null,"abstract":"The major aim of DG optimal placement is obtaining the best DGs units sizes and locations so as to have optimum operation and planning of the distribution network system while considering DG capacity constraint. This paper addresses the issues related to the improvement of voltage profile and power loss reduction by integrating DG units. The technique was applied to optimally placed optimum DG unit size in distribution systems for the improvement of candidate bus voltage and reduction of power loss in the system. The technique proposed was simulated on IEEE-10 bus and IEEE-13 bus standard test system, and the obtained results show that the proposed method is strong and effective for optimal placement of DG units.","PeriodicalId":43245,"journal":{"name":"International Journal of Energy Optimization and Engineering","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43424417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abdelouadoud Loukriz, D. Saigaa, Abdelhammid Kherbachi, Mustapha Koriker, Ahmed Bendib, M. Drif
To ensure the safe and stable operation of solar photovoltaic system-based power systems, it is essential to predict the PV module output performance under varying operating conditions. In this paper, the interest is to develop an accurate model of a PV module in order to predict its electrical characteristics. For this purpose, an artificial neural network (ANN) based on the backpropagation algorithm is proposed for the performance prediction of a photovoltaic module. In this modeling approach, the temperature and illumination are taken as inputs and the current of the mathematical model as output for the learning of the ANN-PV-Panel. Simulation results showing the performance of the ANN model in obtaining the electrical properties of the chosen PV panel, including I–V curves and P–V curves, in comparison with the mathematical model performance are presented and discussed. The given results show that the error of the maximum power is very small while the current error is about 10-8, which means that the obtained model is able to predict accurately the outputs of the PV panel.
{"title":"Prediction of Photovoltaic Panels Output Performance Using Artificial Neural Network","authors":"Abdelouadoud Loukriz, D. Saigaa, Abdelhammid Kherbachi, Mustapha Koriker, Ahmed Bendib, M. Drif","doi":"10.4018/ijeoe.309417","DOIUrl":"https://doi.org/10.4018/ijeoe.309417","url":null,"abstract":"To ensure the safe and stable operation of solar photovoltaic system-based power systems, it is essential to predict the PV module output performance under varying operating conditions. In this paper, the interest is to develop an accurate model of a PV module in order to predict its electrical characteristics. For this purpose, an artificial neural network (ANN) based on the backpropagation algorithm is proposed for the performance prediction of a photovoltaic module. In this modeling approach, the temperature and illumination are taken as inputs and the current of the mathematical model as output for the learning of the ANN-PV-Panel. Simulation results showing the performance of the ANN model in obtaining the electrical properties of the chosen PV panel, including I–V curves and P–V curves, in comparison with the mathematical model performance are presented and discussed. The given results show that the error of the maximum power is very small while the current error is about 10-8, which means that the obtained model is able to predict accurately the outputs of the PV panel.","PeriodicalId":43245,"journal":{"name":"International Journal of Energy Optimization and Engineering","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49625055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this work, an efficient solution based on the reducing forms approach is presented to extract the five parameters of the single-diode model of PV generators from their I-V curves. Thus, by reducing the number of the five unknown parameters to two unknowns, the analytical expression of the current based on the LambertW function will then depend only on the ideality factor and the series resistance, as the two unknowns to predict numerically using the non-linear least square technique. The three other parameters are calculated as functions of the two predicted parameters using a linear system of three equations. Two sets of experiments are used for the validation of the proposed approach, which first showed its rapidity and high accuracy compared to the best approaches from the literature. Then, the method was applied for the real-time identification of four PV modules operating outdoors during one reference day at Cocoa (Florida).
{"title":"A New Reduced Form for Real-Time Identification of PV Panels Operating Under Arbitrary Conditions","authors":"Kawtar Tifidat, N. Maouhoub, Abdelaaziz Benahmida","doi":"10.4018/ijeoe.309415","DOIUrl":"https://doi.org/10.4018/ijeoe.309415","url":null,"abstract":"In this work, an efficient solution based on the reducing forms approach is presented to extract the five parameters of the single-diode model of PV generators from their I-V curves. Thus, by reducing the number of the five unknown parameters to two unknowns, the analytical expression of the current based on the LambertW function will then depend only on the ideality factor and the series resistance, as the two unknowns to predict numerically using the non-linear least square technique. The three other parameters are calculated as functions of the two predicted parameters using a linear system of three equations. Two sets of experiments are used for the validation of the proposed approach, which first showed its rapidity and high accuracy compared to the best approaches from the literature. Then, the method was applied for the real-time identification of four PV modules operating outdoors during one reference day at Cocoa (Florida).","PeriodicalId":43245,"journal":{"name":"International Journal of Energy Optimization and Engineering","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42572521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Aikhuele, A. Periola, Elijah Aigbedion, Herold U. Nwosu
Wind energy is generated via the use of wind blades, turbines and generators that are deployed over a given area. To achieve a higher energy and system reliability, the wind blade and other units of the system must be designed with suitable materials. In this paper however, a computational intelligent model based on an artificial neutral network has been propose for the evaluation of the reliability of the wind turbine blade designed with the FRP material. The simulation results show that there was a reduction in the training mean square error, testing (re–training) mean square error and validation mean square error, when the number of training epochs is increased by 50% such that the minimum mean square error and maximum mean square error were 0.0011 and 0.0061, respectively. The low validation mean square error in the simulation results implies that the developed artificial neural network has a good accuracy when determining the reliability and the failure probability of the wind turbine blade.
{"title":"Intelligent and Data-Driven Reliability Evaluation Model for Wind Turbine Blades","authors":"D. Aikhuele, A. Periola, Elijah Aigbedion, Herold U. Nwosu","doi":"10.4018/ijeoe.298694","DOIUrl":"https://doi.org/10.4018/ijeoe.298694","url":null,"abstract":"Wind energy is generated via the use of wind blades, turbines and generators that are deployed over a given area. To achieve a higher energy and system reliability, the wind blade and other units of the system must be designed with suitable materials. In this paper however, a computational intelligent model based on an artificial neutral network has been propose for the evaluation of the reliability of the wind turbine blade designed with the FRP material. The simulation results show that there was a reduction in the training mean square error, testing (re–training) mean square error and validation mean square error, when the number of training epochs is increased by 50% such that the minimum mean square error and maximum mean square error were 0.0011 and 0.0061, respectively. The low validation mean square error in the simulation results implies that the developed artificial neural network has a good accuracy when determining the reliability and the failure probability of the wind turbine blade.","PeriodicalId":43245,"journal":{"name":"International Journal of Energy Optimization and Engineering","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48028210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, a novel cascade control technique is proposed in order to identify the parameters of cascade controllers in a grid-connected photovoltaic (PV) system. Here, tuning of the inner and outer loop controllers is done simultaneously by means of an optimized genetic algorithm-based fractional order PID (GA-FOPID) control. Simulations are conducted using Matlab/Simulink software under different operating conditions, namely under fast-changing weather conditions, sudden parametric variations, and voltage dip, for the purpose of verifying the effectiveness of the proposed control strategy. By comparing the results with recently published optimization techniques such as particle swarm optimization (PSO) and ant colony optimization (ACO), the superiority and effectiveness of the proposed GA-FOPID control have been proven.
{"title":"Metaheuristic-Based Control for Three-Phase Grid-Connected Solar Photovoltaic Systems","authors":"Afef Badis, Mohamed Habib Boujmil, M. Mansouri","doi":"10.4018/ijeoe.310003","DOIUrl":"https://doi.org/10.4018/ijeoe.310003","url":null,"abstract":"In this paper, a novel cascade control technique is proposed in order to identify the parameters of cascade controllers in a grid-connected photovoltaic (PV) system. Here, tuning of the inner and outer loop controllers is done simultaneously by means of an optimized genetic algorithm-based fractional order PID (GA-FOPID) control. Simulations are conducted using Matlab/Simulink software under different operating conditions, namely under fast-changing weather conditions, sudden parametric variations, and voltage dip, for the purpose of verifying the effectiveness of the proposed control strategy. By comparing the results with recently published optimization techniques such as particle swarm optimization (PSO) and ant colony optimization (ACO), the superiority and effectiveness of the proposed GA-FOPID control have been proven.","PeriodicalId":43245,"journal":{"name":"International Journal of Energy Optimization and Engineering","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43167535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Preliminary preparation of waste for anaerobic digestion at thermophilic temperature conditions is the most energy-intensive stage of the process of anaerobic bioconversion of production and consumption waste organic matter, therefore, the search for ways to reduce energy consumption at this stage remains an urgent task. The article proposes a technological solution to maintain the temperature regime of the digester operation due to the utilization of existing waste low-grade energy sources using a compression heat pump. The flow diagram of the experimental biogas plant is shown and a description of its operation is given. The dependences of the absolute and specific rates of heating of the influent and cooling of the effluent on the initial temperature of the effluent are given. The principal possibility of maintaining the temperature regime in the digester is shown by using the heat recovery of the effluent using a compression heat pump.
{"title":"Heat Recovery of Low-Grade Energy Sources in the System of Preparation of Biogas Plant Substrates","authors":"A. Kovalev","doi":"10.4018/ijeoe.298693","DOIUrl":"https://doi.org/10.4018/ijeoe.298693","url":null,"abstract":"Preliminary preparation of waste for anaerobic digestion at thermophilic temperature conditions is the most energy-intensive stage of the process of anaerobic bioconversion of production and consumption waste organic matter, therefore, the search for ways to reduce energy consumption at this stage remains an urgent task. The article proposes a technological solution to maintain the temperature regime of the digester operation due to the utilization of existing waste low-grade energy sources using a compression heat pump. The flow diagram of the experimental biogas plant is shown and a description of its operation is given. The dependences of the absolute and specific rates of heating of the influent and cooling of the effluent on the initial temperature of the effluent are given. The principal possibility of maintaining the temperature regime in the digester is shown by using the heat recovery of the effluent using a compression heat pump.","PeriodicalId":43245,"journal":{"name":"International Journal of Energy Optimization and Engineering","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45639858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The renewable economic emission transmit is a significant and new assignment in the modern power system. This article develops oppositional grasshopper optimization algorithm (OGOA) which depends on the social dealings of the grasshopper in nature, to solve renewable energy based economic emission dispatch (EED) considering uncertainty in wind power availability and a carbon tax on emission from the thermal unit. To speed up the convergence speed and advance the simulation results, opposition based learning (OBL) is integrated with the fundamental GOA in OGOA algorithm. To show the nonlinearity of wind power availability the Weibull distribution is used. A standard system, containing of two wind farms and six thermal units is used for testing the dispatch model for three different loads. The statistical outcomes of the applied OGOA technique are compared with basic GOA and quantum-inspired particle swarm optimization (QPSO) optimization. It is observed OGOA is more skillful than basic GOA technique for significantly reducing the computation time and developing hopeful outcomes.
{"title":"Oppositional GOA applied on Renewable Energy based multi-objective Economic Emission Dispatch","authors":"S. Hazra","doi":"10.4018/ijeoe.295983","DOIUrl":"https://doi.org/10.4018/ijeoe.295983","url":null,"abstract":"The renewable economic emission transmit is a significant and new assignment in the modern power system. This article develops oppositional grasshopper optimization algorithm (OGOA) which depends on the social dealings of the grasshopper in nature, to solve renewable energy based economic emission dispatch (EED) considering uncertainty in wind power availability and a carbon tax on emission from the thermal unit. To speed up the convergence speed and advance the simulation results, opposition based learning (OBL) is integrated with the fundamental GOA in OGOA algorithm. To show the nonlinearity of wind power availability the Weibull distribution is used. A standard system, containing of two wind farms and six thermal units is used for testing the dispatch model for three different loads. The statistical outcomes of the applied OGOA technique are compared with basic GOA and quantum-inspired particle swarm optimization (QPSO) optimization. It is observed OGOA is more skillful than basic GOA technique for significantly reducing the computation time and developing hopeful outcomes.","PeriodicalId":43245,"journal":{"name":"International Journal of Energy Optimization and Engineering","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47436636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Researchers are increasingly using algorithms that are influenced by nature because of its ease and versatility, the key components of nature-inspired metaheuristic algorithms are investigated, involving divergence and adoption, investigation and utilization, and dissemination techniques. Grey Wolf Optimizer (GWO), a relatively recent algorithm influenced by the dominance structure and poaching deportment of grey wolves, is a very popular technique for solving realistic mechanical and optical technical challenges. Half of the recurrence in the GWO are committed to the exploration and the other half to exploitation, ignoring the importance of maintaining the correct equilibrium to ensure a precise estimate of the global optimum. To address this flaw, a Multi-tiered GWO (MGWO) is formulated, that further accomplishes an appropriate equivalence among exploration and exploitation, resulting in optimal algorithm efficiency. In comparison to familiar optimization methods, simulations relying on benchmark functions exhibit the efficacy, performance, and stabilization of MGWO.
{"title":"Opposition-Based Multi-tiered Grey Wolf Optimizer for Stochastic Global Optimization Paradigms","authors":"Vasudha Bahl","doi":"10.4018/ijeoe.295982","DOIUrl":"https://doi.org/10.4018/ijeoe.295982","url":null,"abstract":"Researchers are increasingly using algorithms that are influenced by nature because of its ease and versatility, the key components of nature-inspired metaheuristic algorithms are investigated, involving divergence and adoption, investigation and utilization, and dissemination techniques. Grey Wolf Optimizer (GWO), a relatively recent algorithm influenced by the dominance structure and poaching deportment of grey wolves, is a very popular technique for solving realistic mechanical and optical technical challenges. Half of the recurrence in the GWO are committed to the exploration and the other half to exploitation, ignoring the importance of maintaining the correct equilibrium to ensure a precise estimate of the global optimum. To address this flaw, a Multi-tiered GWO (MGWO) is formulated, that further accomplishes an appropriate equivalence among exploration and exploitation, resulting in optimal algorithm efficiency. In comparison to familiar optimization methods, simulations relying on benchmark functions exhibit the efficacy, performance, and stabilization of MGWO.","PeriodicalId":43245,"journal":{"name":"International Journal of Energy Optimization and Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42557309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-01DOI: 10.4018/ijeoe.2021100104
M. Nedaei
In the current analysis, a novel hybrid energy system operating on the basis of wind and hydrogen energy is designed. The simulation-based optimization has indicated the stochastic nature of wind power technology in comparison with hydrogen power specially when being integrated with the transportation network. The multi-criteria decision-making approach in the current analysis has also suggested that, among the examined cases, the most appropriate configuration of the hybrid energy system is leading to optimum levels of wind energy production, fuel flow rate, oxygen, hydrogen utilization, and stack consumption (including air and fuel) with the equivalents of 1,700 kW, 84 lpm, 75%, 717.37 kg/m3, 140 lpm, and 48 lpm, respectively. The maximum net revenues of the entire hybrid system are estimated to be €4,470 per month. It has been concluded that a transportation network fueled by wind and hydrogen systems can lead to a reduced level of environmental footprints.
{"title":"Technical Analysis of a Novel Wind-Powered Hydrogen System for Sustainable Development","authors":"M. Nedaei","doi":"10.4018/ijeoe.2021100104","DOIUrl":"https://doi.org/10.4018/ijeoe.2021100104","url":null,"abstract":"In the current analysis, a novel hybrid energy system operating on the basis of wind and hydrogen energy is designed. The simulation-based optimization has indicated the stochastic nature of wind power technology in comparison with hydrogen power specially when being integrated with the transportation network. The multi-criteria decision-making approach in the current analysis has also suggested that, among the examined cases, the most appropriate configuration of the hybrid energy system is leading to optimum levels of wind energy production, fuel flow rate, oxygen, hydrogen utilization, and stack consumption (including air and fuel) with the equivalents of 1,700 kW, 84 lpm, 75%, 717.37 kg/m3, 140 lpm, and 48 lpm, respectively. The maximum net revenues of the entire hybrid system are estimated to be €4,470 per month. It has been concluded that a transportation network fueled by wind and hydrogen systems can lead to a reduced level of environmental footprints.","PeriodicalId":43245,"journal":{"name":"International Journal of Energy Optimization and Engineering","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46071148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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