Pub Date : 2015-10-01DOI: 10.1109/EPEC.2015.7379929
Mohamed A. Abdelwahed, E. Elsaadany
Power sharing control and voltage regulation are considered as significant challenges in the development of large MT VSC-HVDC transmission grids, besides fault ride through and automatic restoration aspects. The main contribution of the work presented in this research is the proposal of a generic power sharing control algorithm. This algorithm is based on sharing the imported active power to the MT HVDC network among different AC grids based on desired sharing ratios, to fulfil active power requirements of the connected grids in order to achieve their own objectives, such as supporting the energy adequacy, increasing wind energy penetration and loss minimization. This algorithm is used as a supervisory control algorithm to integrate a number of offshore wind farms into various onshore AC grids.
{"title":"Adaptive droop based power sharing control algorithm for offshore multi-terminal VSC-HVDC transmission","authors":"Mohamed A. Abdelwahed, E. Elsaadany","doi":"10.1109/EPEC.2015.7379929","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379929","url":null,"abstract":"Power sharing control and voltage regulation are considered as significant challenges in the development of large MT VSC-HVDC transmission grids, besides fault ride through and automatic restoration aspects. The main contribution of the work presented in this research is the proposal of a generic power sharing control algorithm. This algorithm is based on sharing the imported active power to the MT HVDC network among different AC grids based on desired sharing ratios, to fulfil active power requirements of the connected grids in order to achieve their own objectives, such as supporting the energy adequacy, increasing wind energy penetration and loss minimization. This algorithm is used as a supervisory control algorithm to integrate a number of offshore wind farms into various onshore AC grids.","PeriodicalId":231255,"journal":{"name":"2015 IEEE Electrical Power and Energy Conference (EPEC)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126316019","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 : 2015-10-01DOI: 10.1109/EPEC.2015.7379961
Shady A. El-Batawy, W. Morsi
This paper investigates the effect of increasing the penetration of rooftop solar photovoltaic on the distribution transformer's loss of life. Markov Chain Monte Carlo (MCMC) is used to probabilistically estimate the hourly loading on the distribution transformer while the loss of life is estimated based on the distribution transformer' s thermal model. The results have shown that minimum impact on the distribution transformer's insulation life may be achieved only at 60% penetration of rooftop solar photovoltaic which can be considered as the maximum permissible PV penetration.
{"title":"Reducing distribution transformer's loss of life through determining the maximum permissible penetration of rooftop solar photovoltaic","authors":"Shady A. El-Batawy, W. Morsi","doi":"10.1109/EPEC.2015.7379961","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379961","url":null,"abstract":"This paper investigates the effect of increasing the penetration of rooftop solar photovoltaic on the distribution transformer's loss of life. Markov Chain Monte Carlo (MCMC) is used to probabilistically estimate the hourly loading on the distribution transformer while the loss of life is estimated based on the distribution transformer' s thermal model. The results have shown that minimum impact on the distribution transformer's insulation life may be achieved only at 60% penetration of rooftop solar photovoltaic which can be considered as the maximum permissible PV penetration.","PeriodicalId":231255,"journal":{"name":"2015 IEEE Electrical Power and Energy Conference (EPEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130231222","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 : 2015-10-01DOI: 10.1109/EPEC.2015.7379934
Xiangsheng Lai, Z. Yang, Guangyi Liu, Shuang Gao, Dan Wang, Jia Tang, Zhaoyu Chen, H. Jia
A Volt-VAR control (VVC) strategy by using voltage regulators and reactive power compensators in the modern distribution grid for renewable energy integration is presented in this paper. Currently, the VVC techniques are gaining renewed interest and attention due to the emergence of active distribution grid, which refers to the distribution grid with advanced capability of computation, control and communication. The mathematical model of the distribution systems contains the detailed modeling of various distributed generators, in particular renewable energy sources such as wind and solar power generators, and the varying load over the continuous time period. The coordinated VVC control strategy adjust the value of the voltage regulator and the reactive power injection to minimize the voltage deviation and the overall power loss. A VVC control algorithm is developed to mitigate the voltage sag or swell associated with the intermittent renewable power output and load variation. The proposed VVC control strategy is implemented in the simulation environment of Matlab and GridLAB-D featured by detailed distributed generation and load models. The simulation results validate the effectiveness of the proposed VVC control strategy in terms of voltage flattening and power loss reduction. The load voltage and line losses can be limited within the allowed regulation range as a large scale renewable energy is integrated into the test multi-level distribution systems.
{"title":"Coordinated Volt-VAR control in active distribution systems for renewable energy integration","authors":"Xiangsheng Lai, Z. Yang, Guangyi Liu, Shuang Gao, Dan Wang, Jia Tang, Zhaoyu Chen, H. Jia","doi":"10.1109/EPEC.2015.7379934","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379934","url":null,"abstract":"A Volt-VAR control (VVC) strategy by using voltage regulators and reactive power compensators in the modern distribution grid for renewable energy integration is presented in this paper. Currently, the VVC techniques are gaining renewed interest and attention due to the emergence of active distribution grid, which refers to the distribution grid with advanced capability of computation, control and communication. The mathematical model of the distribution systems contains the detailed modeling of various distributed generators, in particular renewable energy sources such as wind and solar power generators, and the varying load over the continuous time period. The coordinated VVC control strategy adjust the value of the voltage regulator and the reactive power injection to minimize the voltage deviation and the overall power loss. A VVC control algorithm is developed to mitigate the voltage sag or swell associated with the intermittent renewable power output and load variation. The proposed VVC control strategy is implemented in the simulation environment of Matlab and GridLAB-D featured by detailed distributed generation and load models. The simulation results validate the effectiveness of the proposed VVC control strategy in terms of voltage flattening and power loss reduction. The load voltage and line losses can be limited within the allowed regulation range as a large scale renewable energy is integrated into the test multi-level distribution systems.","PeriodicalId":231255,"journal":{"name":"2015 IEEE Electrical Power and Energy Conference (EPEC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122294921","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 : 2015-10-01DOI: 10.1109/EPEC.2015.7379997
K. Nigim, J. McQueen, M. Persohn-Costa
The proposed operating modes for hydrogen production from renewable energy sources are presented in this work. The designed system is put together to support the investigation of energy requirements in a preliminary focus on residential application. The sensory components of the controller observe, in real time, the incoming energy changes and compare it with the system demand and level of stored energy. The controller output command selects the most economical and energy efficient mode for effective dispatchable system operation. Instantaneous short term requirements of power are exchanged with the hosting grid to mitigate instantaneous intermittency. The modular concept of the built infrastructure enables researchers to test different modes of operation such as a micro grid functionality under various energy supply and load demands. Moreover, the system is designed for use as a testing facility of hydrogen generating units as well as newly designed fuel cells.
{"title":"Operational modes of hydrogen energy storage in a micro grid system","authors":"K. Nigim, J. McQueen, M. Persohn-Costa","doi":"10.1109/EPEC.2015.7379997","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379997","url":null,"abstract":"The proposed operating modes for hydrogen production from renewable energy sources are presented in this work. The designed system is put together to support the investigation of energy requirements in a preliminary focus on residential application. The sensory components of the controller observe, in real time, the incoming energy changes and compare it with the system demand and level of stored energy. The controller output command selects the most economical and energy efficient mode for effective dispatchable system operation. Instantaneous short term requirements of power are exchanged with the hosting grid to mitigate instantaneous intermittency. The modular concept of the built infrastructure enables researchers to test different modes of operation such as a micro grid functionality under various energy supply and load demands. Moreover, the system is designed for use as a testing facility of hydrogen generating units as well as newly designed fuel cells.","PeriodicalId":231255,"journal":{"name":"2015 IEEE Electrical Power and Energy Conference (EPEC)","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132459941","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 : 2015-10-01DOI: 10.1109/EPEC.2015.7379936
N. Hajia, B. Venkatesh
Next generation Smart Grids are expected to integrate energy storage systems to improve performance, operational efficiency, reliability, increased asset utilization, renewable integration, etc. Energy storage systems using Lithium-ion batteries show a promise for power system applications due to characteristics such as high energy density, efficiency, number of cycles, depth of discharge, etc. In order to best integrate modern energy storage systems, it is imperative that reliable and adequate technical models are developed, validated and incorporated with power system analysis and optimization methods. A State of Charge (SOC) model of Lithium-Ion batteries is presented in this paper and a test protocol was developed to determine the model's parameter. In addition, a general procedure to estimate this SOC model of Li-Ion batteries using laboratory tests is presented. Thereafter, a chosen Li-Ion battery is tested for various conditions and the corresponding SOC model is to simulate those test conditions. A comparison between test and simulation results shows the accuracy of the proposed method. The model is temperature sensitive and practical.
{"title":"SOC model of high power Lithium-Ion battery","authors":"N. Hajia, B. Venkatesh","doi":"10.1109/EPEC.2015.7379936","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379936","url":null,"abstract":"Next generation Smart Grids are expected to integrate energy storage systems to improve performance, operational efficiency, reliability, increased asset utilization, renewable integration, etc. Energy storage systems using Lithium-ion batteries show a promise for power system applications due to characteristics such as high energy density, efficiency, number of cycles, depth of discharge, etc. In order to best integrate modern energy storage systems, it is imperative that reliable and adequate technical models are developed, validated and incorporated with power system analysis and optimization methods. A State of Charge (SOC) model of Lithium-Ion batteries is presented in this paper and a test protocol was developed to determine the model's parameter. In addition, a general procedure to estimate this SOC model of Li-Ion batteries using laboratory tests is presented. Thereafter, a chosen Li-Ion battery is tested for various conditions and the corresponding SOC model is to simulate those test conditions. A comparison between test and simulation results shows the accuracy of the proposed method. The model is temperature sensitive and practical.","PeriodicalId":231255,"journal":{"name":"2015 IEEE Electrical Power and Energy Conference (EPEC)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125614845","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 : 2015-10-01DOI: 10.1109/EPEC.2015.7379946
T. El-Fouly, A. B. Eltantawy, M. Salama
Remote communities mainly rely on diesel for electricity generation. Costs of electricity generation could reach up to 10 times compared to the main electric grid because of the cost of fuel transportation and delivery. With the revolution of smart grid technology, it is possible to quantify the full potential of integrating renewables and smart grid applications to bring real cost savings to these communities. This paper presents details for the Microsoft Excel-based, optimal performance assessment tool for remote grids that has been developed by CanmetENERGY to assess the performance of the electricity grid for remote microgrids and provide a guide for remote microgrid planning.
{"title":"Performance assessment tool for remote electrical microgrids (PATREM)","authors":"T. El-Fouly, A. B. Eltantawy, M. Salama","doi":"10.1109/EPEC.2015.7379946","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379946","url":null,"abstract":"Remote communities mainly rely on diesel for electricity generation. Costs of electricity generation could reach up to 10 times compared to the main electric grid because of the cost of fuel transportation and delivery. With the revolution of smart grid technology, it is possible to quantify the full potential of integrating renewables and smart grid applications to bring real cost savings to these communities. This paper presents details for the Microsoft Excel-based, optimal performance assessment tool for remote grids that has been developed by CanmetENERGY to assess the performance of the electricity grid for remote microgrids and provide a guide for remote microgrid planning.","PeriodicalId":231255,"journal":{"name":"2015 IEEE Electrical Power and Energy Conference (EPEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129171675","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 : 2015-10-01DOI: 10.1109/EPEC.2015.7379932
M. Rashwan, M. Duhoux
The work described in this paper focusses on energy performance and is part of an on-going POE (Post Occupancy Evaluation) for seventy two (72) homes built in three Manitoba cities according to LEED (Leadership in Energy and Environmental Design) standards. The POE includes assessments & benchmarking of Indoor Air Quality (IAQ) and Life Cycle Costing (LCC) in addition to the energy consumption. Energy consumption data for the units were retrieved from the billing records provided by the utility company (Manitoba Hydro). Statistical analysis tools were then used to compare the units' consumptions with the levels known for typical homes as well as with design projected values. Using Regression Analysis, linear relations correlating actual monthly consumption ranges of all units and the projected values to average monthly temperatures and HDD (Heating Degree Days) were then developed. Using these relationships, statistical control charts were proposed as means of monitoring and ultimately establishing more realistic benchmarks for energy consumption of LEED homes.
{"title":"Benchmarking energy performance for LEED residential homes in Manitoba","authors":"M. Rashwan, M. Duhoux","doi":"10.1109/EPEC.2015.7379932","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379932","url":null,"abstract":"The work described in this paper focusses on energy performance and is part of an on-going POE (Post Occupancy Evaluation) for seventy two (72) homes built in three Manitoba cities according to LEED (Leadership in Energy and Environmental Design) standards. The POE includes assessments & benchmarking of Indoor Air Quality (IAQ) and Life Cycle Costing (LCC) in addition to the energy consumption. Energy consumption data for the units were retrieved from the billing records provided by the utility company (Manitoba Hydro). Statistical analysis tools were then used to compare the units' consumptions with the levels known for typical homes as well as with design projected values. Using Regression Analysis, linear relations correlating actual monthly consumption ranges of all units and the projected values to average monthly temperatures and HDD (Heating Degree Days) were then developed. Using these relationships, statistical control charts were proposed as means of monitoring and ultimately establishing more realistic benchmarks for energy consumption of LEED homes.","PeriodicalId":231255,"journal":{"name":"2015 IEEE Electrical Power and Energy Conference (EPEC)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115982533","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 : 2015-10-01DOI: 10.1109/EPEC.2015.7379970
M. L. Zegai, M. Bendjebbar, K. Belhadri, M. Doumbia, B. Hamane, P. M. Koumba
This contribution deals with the proposal of direct torque control (DTC) for Induction Motor (IM) with the use of artificial neural networks (ANN) to increase the system's performance. Model Reference Adaptive System (MRAS) method is used for the estimation and regulation of rotor's speed. The whole structure of DTC is designed by Matlab/Simulink. The neural controller is designed using neural Toolbox, and the system's performance is compared with conventional DTC.
{"title":"Direct torque control of Induction Motor based on artificial neural networks speed control using MRAS and neural PID controller","authors":"M. L. Zegai, M. Bendjebbar, K. Belhadri, M. Doumbia, B. Hamane, P. M. Koumba","doi":"10.1109/EPEC.2015.7379970","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379970","url":null,"abstract":"This contribution deals with the proposal of direct torque control (DTC) for Induction Motor (IM) with the use of artificial neural networks (ANN) to increase the system's performance. Model Reference Adaptive System (MRAS) method is used for the estimation and regulation of rotor's speed. The whole structure of DTC is designed by Matlab/Simulink. The neural controller is designed using neural Toolbox, and the system's performance is compared with conventional DTC.","PeriodicalId":231255,"journal":{"name":"2015 IEEE Electrical Power and Energy Conference (EPEC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115509766","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 : 2015-10-01DOI: 10.1109/EPEC.2015.7379942
Omar Alrumayh, Kankar Bhattacharya
Involving end-users in Demand Side Management (DSM) programs with home energy management systems (HEMS) is an important requirement in realizing the smart grid. In smart grids, advanced communication technologies provide an opportunity to communicate with customers expeditiously. Optimizing the demand side consumption yields economical benefits to both the utility and customer. The HEMS helps the customers to optimize their household appliances' operation. This paper presents the application of model predictive control (MPC) on the HEMS model in order to arrive at the optimal operational decisions when the inputs are subject to variations. Reduction in the total customer's energy cost is achieved. Additionally, the results show increase in customers' revenue from selling the generated and stored energy to the utility.
{"title":"Model predictive control based home energy management system in smart grid","authors":"Omar Alrumayh, Kankar Bhattacharya","doi":"10.1109/EPEC.2015.7379942","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379942","url":null,"abstract":"Involving end-users in Demand Side Management (DSM) programs with home energy management systems (HEMS) is an important requirement in realizing the smart grid. In smart grids, advanced communication technologies provide an opportunity to communicate with customers expeditiously. Optimizing the demand side consumption yields economical benefits to both the utility and customer. The HEMS helps the customers to optimize their household appliances' operation. This paper presents the application of model predictive control (MPC) on the HEMS model in order to arrive at the optimal operational decisions when the inputs are subject to variations. Reduction in the total customer's energy cost is achieved. Additionally, the results show increase in customers' revenue from selling the generated and stored energy to the utility.","PeriodicalId":231255,"journal":{"name":"2015 IEEE Electrical Power and Energy Conference (EPEC)","volume":"517 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116197649","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 : 2015-10-01DOI: 10.1109/EPEC.2015.7379953
Andrea Žagar, Katarina Grolinger, Miriam A. M. Capretz, Luke Seewald
Electricity price, consumption, and demand forecasting has been a topic of research interest for a long time. The proliferation of smart meters has created new opportunities in energy prediction. This paper investigates energy cost forecasting in the context of entertainment event-organizing venues, which poses significant difficulty due to fluctuations in energy demand and wholesale electricity prices. The objective is to predict the overall cost of energy consumed during an entertainment event. Predictions are carried out separately for each event category and feature selection is used to select the most effective combination of event attributes for each category. Three machine learning approaches are considered: k-nearest neighbor (KNN) regression, support vector regression (SVR) and neural networks (NN). These approaches are evaluated on a case study involving a large event venue in Southern Ontario. In terms of prediction accuracy, KNN regression achieved the lowest average error. Error rates varied greatly among different event categories.
{"title":"Energy cost forecasting for event venues","authors":"Andrea Žagar, Katarina Grolinger, Miriam A. M. Capretz, Luke Seewald","doi":"10.1109/EPEC.2015.7379953","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379953","url":null,"abstract":"Electricity price, consumption, and demand forecasting has been a topic of research interest for a long time. The proliferation of smart meters has created new opportunities in energy prediction. This paper investigates energy cost forecasting in the context of entertainment event-organizing venues, which poses significant difficulty due to fluctuations in energy demand and wholesale electricity prices. The objective is to predict the overall cost of energy consumed during an entertainment event. Predictions are carried out separately for each event category and feature selection is used to select the most effective combination of event attributes for each category. Three machine learning approaches are considered: k-nearest neighbor (KNN) regression, support vector regression (SVR) and neural networks (NN). These approaches are evaluated on a case study involving a large event venue in Southern Ontario. In terms of prediction accuracy, KNN regression achieved the lowest average error. Error rates varied greatly among different event categories.","PeriodicalId":231255,"journal":{"name":"2015 IEEE Electrical Power and Energy Conference (EPEC)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127078075","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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