Pub Date : 2015-10-01DOI: 10.1109/EPEC.2015.7379925
Zhanle Wang, R. Paranjape
This paper proposes an electric vehicle charging model and an optimal control algorithm to predict and evaluate impacts of electric vehicle penetration on the power system. Electric vehicles have become increasingly popular due to their highly efficient use of energy and their potential to reduce CO2 emissions. The proposed electric vehicle charging model simulates an individual electric vehicle's load profile by capturing various characteristics of a Lithium-Ion battery such as charging demand, the state of charge and potential driving patterns. The optimal control algorithm of scheduling electric vehicle charging is formulated as a convex optimization problem under real-time pricing to minimize the electricity payments of the user. Simulation results show that uncontrolled electric vehicle charging can jeopardize the stability of the power system while scheduled charging has no contribution to the peak demand. Furthermore, scheduled charging dramatically reduces the peak to average power ratio and electricity payment of users. The proposed electric vehicle charging model can be used to study charging patterns in a simulation environment and the optimal control algorithm can be embedded into a home energy management system or a smart charger.
{"title":"Optimal scheduling algorithm for charging electric vehicle in a residential sector under demand response","authors":"Zhanle Wang, R. Paranjape","doi":"10.1109/EPEC.2015.7379925","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379925","url":null,"abstract":"This paper proposes an electric vehicle charging model and an optimal control algorithm to predict and evaluate impacts of electric vehicle penetration on the power system. Electric vehicles have become increasingly popular due to their highly efficient use of energy and their potential to reduce CO2 emissions. The proposed electric vehicle charging model simulates an individual electric vehicle's load profile by capturing various characteristics of a Lithium-Ion battery such as charging demand, the state of charge and potential driving patterns. The optimal control algorithm of scheduling electric vehicle charging is formulated as a convex optimization problem under real-time pricing to minimize the electricity payments of the user. Simulation results show that uncontrolled electric vehicle charging can jeopardize the stability of the power system while scheduled charging has no contribution to the peak demand. Furthermore, scheduled charging dramatically reduces the peak to average power ratio and electricity payment of users. The proposed electric vehicle charging model can be used to study charging patterns in a simulation environment and the optimal control algorithm can be embedded into a home energy management system or a smart charger.","PeriodicalId":231255,"journal":{"name":"2015 IEEE Electrical Power and Energy Conference (EPEC)","volume":"206 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":"116536783","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.2015.7379974
H. Mosbah, M. El-Hawary
State estimation is a vital apparatus in observing the power electric grids. As the measure of the electric power grid keeps on growing, a state estimator must be all the more computationally effective and robust. This paper presents a real time state estimation using a new methodology of multilayer neural networks exhibited in composite topologies, hybrid Cascade and hybrid Parallel topologies in order to improve the estimation performance. The intent is to address the conduct of various composite topologies to contrast the robust performance indices by the maximum relative error, mean absolute percentage error (MAPE), root mean square error, and mean square error (MSE). The performance of distinctive topologies are contrasted with distinguish the best connection structural. The estimation performance of the proposed method is evaluated using real time data from the American Electric Power System in the Midwestern US which is published by the official website of University of Washington.
{"title":"Multilayer artificial neural networks for real time power system state estimation","authors":"H. Mosbah, M. El-Hawary","doi":"10.1109/EPEC.2015.7379974","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379974","url":null,"abstract":"State estimation is a vital apparatus in observing the power electric grids. As the measure of the electric power grid keeps on growing, a state estimator must be all the more computationally effective and robust. This paper presents a real time state estimation using a new methodology of multilayer neural networks exhibited in composite topologies, hybrid Cascade and hybrid Parallel topologies in order to improve the estimation performance. The intent is to address the conduct of various composite topologies to contrast the robust performance indices by the maximum relative error, mean absolute percentage error (MAPE), root mean square error, and mean square error (MSE). The performance of distinctive topologies are contrasted with distinguish the best connection structural. The estimation performance of the proposed method is evaluated using real time data from the American Electric Power System in the Midwestern US which is published by the official website of University of Washington.","PeriodicalId":231255,"journal":{"name":"2015 IEEE Electrical Power and Energy Conference (EPEC)","volume":"4 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":"133091048","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.2015.7379959
M. Abouzeid, V. Sood, M. Youssef
In this paper, fuzzy logic (FL) and fuzzy neural (FN) networks are introduced and implemented as maximum power point tracking (MPPT) algorithms. Using a case study of a photovoltaic cell with a boost converter, the merits and demerits of these techniques are highlighted against traditional MPPT techniques, namely the Perturb and Observe (P&O) and the Incremental Conductance (IC) techniques. The four methods are simulated using the software package EMTP-RV and their performance is compared under various operating conditions. The results of this comparative study are presented to guide the hardware design in the solar industry as a futuristic approach.
{"title":"A comparative study of a PV-MPPT grid-integrated system under different control techniques","authors":"M. Abouzeid, V. Sood, M. Youssef","doi":"10.1109/EPEC.2015.7379959","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379959","url":null,"abstract":"In this paper, fuzzy logic (FL) and fuzzy neural (FN) networks are introduced and implemented as maximum power point tracking (MPPT) algorithms. Using a case study of a photovoltaic cell with a boost converter, the merits and demerits of these techniques are highlighted against traditional MPPT techniques, namely the Perturb and Observe (P&O) and the Incremental Conductance (IC) techniques. The four methods are simulated using the software package EMTP-RV and their performance is compared under various operating conditions. The results of this comparative study are presented to guide the hardware design in the solar industry as a futuristic approach.","PeriodicalId":231255,"journal":{"name":"2015 IEEE Electrical Power and Energy Conference (EPEC)","volume":"59 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":"134601868","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.2015.7379921
H. Karmaker, E. Chen
Design concepts for a superconducting wind generator have been developed for offshore wind turbine applications. Electromagnetic, mechanical and thermal modeling and analyses are performed by taking into account the characteristic properties of the superconducting and non-superconducting materials. The investigations use new 4X improved YBCO (Yttrium Barium Copper Oxide) second generation (2G) high temperature superconducting (HTS) wire developed in a research program sponsored by the U.S. Department of Energy.
{"title":"Design concepts for a direct drive wind generator using new superconductors","authors":"H. Karmaker, E. Chen","doi":"10.1109/EPEC.2015.7379921","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379921","url":null,"abstract":"Design concepts for a superconducting wind generator have been developed for offshore wind turbine applications. Electromagnetic, mechanical and thermal modeling and analyses are performed by taking into account the characteristic properties of the superconducting and non-superconducting materials. The investigations use new 4X improved YBCO (Yttrium Barium Copper Oxide) second generation (2G) high temperature superconducting (HTS) wire developed in a research program sponsored by the U.S. Department of Energy.","PeriodicalId":231255,"journal":{"name":"2015 IEEE Electrical Power and Energy Conference (EPEC)","volume":"51 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":"128250229","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.2015.7379926
K. Kumagai, T. Fujita, M. Nakahira, Y. Mizuguchi, H. Sonoda
To reduce the environmental impact of the DC power system of the East Japan Railway Company (JR-EAST), it is important to have effective regenerative energy transfer from one train to another. In this paper, simultaneous measurements between the Yamanote Line Series E231 trains and the adjacent substations were conducted. From these measurements, the correlation between squeezing control of regenerative power in the trains and behavior of the substations was confirmed. Also, to consider minimizing the total squeezing control of regenerative power and maximizing the regenerative ratio, we studied the total of squeezing control of regenerative power and regenerative ratio on the trains from the data at the substations.
{"title":"Study on train operation energy between commuter train and traction substations in a Japanese urban Railway","authors":"K. Kumagai, T. Fujita, M. Nakahira, Y. Mizuguchi, H. Sonoda","doi":"10.1109/EPEC.2015.7379926","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379926","url":null,"abstract":"To reduce the environmental impact of the DC power system of the East Japan Railway Company (JR-EAST), it is important to have effective regenerative energy transfer from one train to another. In this paper, simultaneous measurements between the Yamanote Line Series E231 trains and the adjacent substations were conducted. From these measurements, the correlation between squeezing control of regenerative power in the trains and behavior of the substations was confirmed. Also, to consider minimizing the total squeezing control of regenerative power and maximizing the regenerative ratio, we studied the total of squeezing control of regenerative power and regenerative ratio on the trains from the data at the substations.","PeriodicalId":231255,"journal":{"name":"2015 IEEE Electrical Power and Energy Conference (EPEC)","volume":"215 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":"115510198","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.2015.7379986
Amamihe Onwuachumba, M. Musavi
This paper presents an alternative approach to multiarea state estimation. The proposed approach utilizes a fewer number of measurements than conventional state estimators and is unaffected by errors in system models. The measurements used are identified using principal component analysis, while artificial neural networks are used to implement the state estimation function. The performance of the proposed technique is demonstrated on the IEEE 118-bus and Polish 2383-bus systems.
{"title":"Reduced model state estimation for Wide-Area Monitoring Systems","authors":"Amamihe Onwuachumba, M. Musavi","doi":"10.1109/EPEC.2015.7379986","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379986","url":null,"abstract":"This paper presents an alternative approach to multiarea state estimation. The proposed approach utilizes a fewer number of measurements than conventional state estimators and is unaffected by errors in system models. The measurements used are identified using principal component analysis, while artificial neural networks are used to implement the state estimation function. The performance of the proposed technique is demonstrated on the IEEE 118-bus and Polish 2383-bus systems.","PeriodicalId":231255,"journal":{"name":"2015 IEEE Electrical Power and Energy Conference (EPEC)","volume":"24 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":"127886238","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.2015.7379993
S. Kandil, H. Farag
This paper investigates the impacts of binding constraints of the planning algorithms on the optimal allocation and sizing of renewable based distributed generation (DG) units in distribution networks. The planning algorithm under study depends on developing multi-state probabilistic models for system components and combining these models in one comprehensive model that describes all possible system states. Several technical constraints are taken into consideration, including maximum reverse power at the substation, maximum number of renewable DG connections, voltage technical limits, thermal limits of cables and overhead lines, and voltage unbalance. In this work, the renewable DG allocation binding constraints are studied, where the effect of these constraints on the objective function, also known as shadow price, is investigated. The 123-bus IEEE test system has been utilized in a case study to show the effectiveness of the proposed algorithm. The renewable DG allocation problem is formulated as a nonlinear mixed-integer programming and solved in GAMS environment.
{"title":"Impacts of binding constraints on the planning process of renewable DG in distribution systems","authors":"S. Kandil, H. Farag","doi":"10.1109/EPEC.2015.7379993","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379993","url":null,"abstract":"This paper investigates the impacts of binding constraints of the planning algorithms on the optimal allocation and sizing of renewable based distributed generation (DG) units in distribution networks. The planning algorithm under study depends on developing multi-state probabilistic models for system components and combining these models in one comprehensive model that describes all possible system states. Several technical constraints are taken into consideration, including maximum reverse power at the substation, maximum number of renewable DG connections, voltage technical limits, thermal limits of cables and overhead lines, and voltage unbalance. In this work, the renewable DG allocation binding constraints are studied, where the effect of these constraints on the objective function, also known as shadow price, is investigated. The 123-bus IEEE test system has been utilized in a case study to show the effectiveness of the proposed algorithm. The renewable DG allocation problem is formulated as a nonlinear mixed-integer programming and solved in GAMS environment.","PeriodicalId":231255,"journal":{"name":"2015 IEEE Electrical Power and Energy Conference (EPEC)","volume":"72 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":"127337088","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.2015.7379954
Hengyi Wang, Steven Liu
This paper deals with the harmonic detection which is decoupled from the operation of active power filter. Kalman filter for harmonic detection based on a stochastic state-space model is proposed. However, it is a challenging task in large time varying system to know the process and noise covariance matrices Q and R. In this active power filter application, the current sensor TLC277CD and ADC LTC1403A which introduce load current measurement inaccuracies are analyzed to decide a rough R. Based on that R is exactly known, two adaptive Kalman filter algorithms to scale Q are proposed. One of the adaptive Kalman methods switches two basic Q matrices depending on the system in transient- or steady-state. The other Kalman algorithm tunes an optimal Q at each step by using the information of innovations sequence. The simulation results show that both adaptive Kalman filters have better dynamic performance than the regular Kalman filter.
{"title":"Adaptive Kalman filter for harmonic detection in active power filter application","authors":"Hengyi Wang, Steven Liu","doi":"10.1109/EPEC.2015.7379954","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379954","url":null,"abstract":"This paper deals with the harmonic detection which is decoupled from the operation of active power filter. Kalman filter for harmonic detection based on a stochastic state-space model is proposed. However, it is a challenging task in large time varying system to know the process and noise covariance matrices Q and R. In this active power filter application, the current sensor TLC277CD and ADC LTC1403A which introduce load current measurement inaccuracies are analyzed to decide a rough R. Based on that R is exactly known, two adaptive Kalman filter algorithms to scale Q are proposed. One of the adaptive Kalman methods switches two basic Q matrices depending on the system in transient- or steady-state. The other Kalman algorithm tunes an optimal Q at each step by using the information of innovations sequence. The simulation results show that both adaptive Kalman filters have better dynamic performance than the regular Kalman filter.","PeriodicalId":231255,"journal":{"name":"2015 IEEE Electrical Power and Energy Conference (EPEC)","volume":"42 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":"126735332","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.2015.7379935
A. Dekka, R. Ghaffari, B. Venkatesh, Bin Wu
The renewable energy sources are become an alternative for conventional power generating stations. Currently, in Canada 16.9% of total primary energy supply is met by the renewable energy sources. However, there is an increasing concern over renewable energy sources in power system due to its highly intermittent nature. This may cause problems such as stability, voltage regulation and other power quality issues. To mitigate the power quality issues, the energy storage systems are widely utilized in power system. This paper presents a brief review on various energy storage systems including mechanical, electrical, electrochemical and thermal storage systems.
{"title":"A survey on energy storage technologies in power systems","authors":"A. Dekka, R. Ghaffari, B. Venkatesh, Bin Wu","doi":"10.1109/EPEC.2015.7379935","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379935","url":null,"abstract":"The renewable energy sources are become an alternative for conventional power generating stations. Currently, in Canada 16.9% of total primary energy supply is met by the renewable energy sources. However, there is an increasing concern over renewable energy sources in power system due to its highly intermittent nature. This may cause problems such as stability, voltage regulation and other power quality issues. To mitigate the power quality issues, the energy storage systems are widely utilized in power system. This paper presents a brief review on various energy storage systems including mechanical, electrical, electrochemical and thermal storage systems.","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":"129921398","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 : 2015-09-26DOI: 10.1109/EPEC.2015.7379972
J. Freytes, F. Gruson, P. Delarue, F. Colas, X. Guillaud
The modular multilevel converter (MMC) is the most promising solution to connect HVDC grids to an HVAC one. The installation of new equipment in the HVDC transmission systems requires an economic study where the power losses play an important role. Since the MMC is composed of a high number of semiconductors elements, the losses estimation becomes complex. This paper proposes a simulation-based method for the losses estimation that combines the MMC averaged and instantaneous model in a modular way. The method brings the possibility to compare performances for different modules technologies as well as different high and low level control techniques. The losses characteristics within the MMC are also discussed. The passive losses are taken into account for the first time.
{"title":"Losses estimation method by simulation for the modular multilevel converter","authors":"J. Freytes, F. Gruson, P. Delarue, F. Colas, X. Guillaud","doi":"10.1109/EPEC.2015.7379972","DOIUrl":"https://doi.org/10.1109/EPEC.2015.7379972","url":null,"abstract":"The modular multilevel converter (MMC) is the most promising solution to connect HVDC grids to an HVAC one. The installation of new equipment in the HVDC transmission systems requires an economic study where the power losses play an important role. Since the MMC is composed of a high number of semiconductors elements, the losses estimation becomes complex. This paper proposes a simulation-based method for the losses estimation that combines the MMC averaged and instantaneous model in a modular way. The method brings the possibility to compare performances for different modules technologies as well as different high and low level control techniques. The losses characteristics within the MMC are also discussed. The passive losses are taken into account for the first time.","PeriodicalId":231255,"journal":{"name":"2015 IEEE Electrical Power and Energy Conference (EPEC)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124138746","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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