Pub Date : 2023-03-11DOI: 10.1109/GlobConHT56829.2023.10087812
Andrea Altomonte, A. Bracale, P. Caramia, P. De Falco, G. Di Ilio, L. D. di Noia, E. Jannelli, R. Rizzo
The implementation of cleaner technology in the propulsion of heavy-duty vehicles can contribute reducing the environmental impact of the port-logistic industry. This paper provides an analysis and a time-domain simulation of the power unit in a hybrid fuel cell/battery truck equipped with an electric motor for propulsion. The energy management strategy that rules the powertrain energy flows is implemented by means of a numerical simulation and within the time-domain simulator, that allows evaluating not only the energy variables but also the time behavior of several electric variables that are of particular concern in the real-world development of the truck. The assessment of the experimental results evidences a substantial agreement between the numerical and the time-domain simulations. Moreover, the strategy and/or the control systems may be further refined based on the mitigation of the fluctuations of the electric variables.
{"title":"Time-Domain Modeling and Simulation of a Fuel Cell Hybrid Truck Powertrain Operating in Port Logistics","authors":"Andrea Altomonte, A. Bracale, P. Caramia, P. De Falco, G. Di Ilio, L. D. di Noia, E. Jannelli, R. Rizzo","doi":"10.1109/GlobConHT56829.2023.10087812","DOIUrl":"https://doi.org/10.1109/GlobConHT56829.2023.10087812","url":null,"abstract":"The implementation of cleaner technology in the propulsion of heavy-duty vehicles can contribute reducing the environmental impact of the port-logistic industry. This paper provides an analysis and a time-domain simulation of the power unit in a hybrid fuel cell/battery truck equipped with an electric motor for propulsion. The energy management strategy that rules the powertrain energy flows is implemented by means of a numerical simulation and within the time-domain simulator, that allows evaluating not only the energy variables but also the time behavior of several electric variables that are of particular concern in the real-world development of the truck. The assessment of the experimental results evidences a substantial agreement between the numerical and the time-domain simulations. Moreover, the strategy and/or the control systems may be further refined based on the mitigation of the fluctuations of the electric variables.","PeriodicalId":355921,"journal":{"name":"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122373668","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 : 2023-03-11DOI: 10.1109/GlobConHT56829.2023.10087684
Muhammad Adil, M. P. Mahmud, A. Kouzani, S. Khoo
Integration of electric vehicles (EVs) to address environmental concerns in recent years has motivated system operators to introduce EV s energy trading platforms. In these platforms, different stakeholders participate in energy trade to maximize their utilities. However, it can be challenging to find optimal strategies for EV s' energy demand, charging station (CS) operation, and retailer profit at the same time without impacting the social welfare of the energy trading platform. This article proposes a multilevel energy trading platform for EV s interaction with CS, and a retailer, which is integrated with distributed energy resources. This platform is modeled using a non-cooperative Stackelberg game, with the retailer acting as a leader at the upper level to maximize profit”. However, the CS and EV s act as followers at the lower level trying to minimize their energy costs. We introduced a penalty function to enhance the platform's social welfare. Our price distribution at various ends of the day will motivate more EVs and CS energy trading interactions. The proposed model is a constrained nonlinear optimization problem, programmed in MATLAB R2022a and solved using FMINCON solver.
{"title":"Optimal Energy Trade in Retailer, Charging Station, and Electric Vehicles using a Stackelberg Game","authors":"Muhammad Adil, M. P. Mahmud, A. Kouzani, S. Khoo","doi":"10.1109/GlobConHT56829.2023.10087684","DOIUrl":"https://doi.org/10.1109/GlobConHT56829.2023.10087684","url":null,"abstract":"Integration of electric vehicles (EVs) to address environmental concerns in recent years has motivated system operators to introduce EV s energy trading platforms. In these platforms, different stakeholders participate in energy trade to maximize their utilities. However, it can be challenging to find optimal strategies for EV s' energy demand, charging station (CS) operation, and retailer profit at the same time without impacting the social welfare of the energy trading platform. This article proposes a multilevel energy trading platform for EV s interaction with CS, and a retailer, which is integrated with distributed energy resources. This platform is modeled using a non-cooperative Stackelberg game, with the retailer acting as a leader at the upper level to maximize profit”. However, the CS and EV s act as followers at the lower level trying to minimize their energy costs. We introduced a penalty function to enhance the platform's social welfare. Our price distribution at various ends of the day will motivate more EVs and CS energy trading interactions. The proposed model is a constrained nonlinear optimization problem, programmed in MATLAB R2022a and solved using FMINCON solver.","PeriodicalId":355921,"journal":{"name":"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129222906","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 : 2023-03-11DOI: 10.1109/GlobConHT56829.2023.10087880
D. Rashmi, S. Sivasubramani
Plug-in electric vehicles (PEVs) will significantly impact the power system due to their interactions with the grid. Grid to Vehicle (G2V) and Vehicle to Grid (V2G) transactions can happen between PEVs and the grid. In order to overcome the impact of charging and discharging of PEV s,’ an intelligent scheduling scheme is essential. This work proposes two optimum scheduling techniques for PEV G2V and V2G transactions, namely, a locally optimum scheduling strategy as well as an equitable distribution strategy. An effective scheduling strategy is developed by first formulating a local scheduling optimization issue, which intends to reduce the overall cost of the EVs in the current EV fleet of the local group. The particle swarm optimization (PSO) algorithm is used to solve the optimization problem. The locally optimal scheduling scheme is not only able to handle a large number of EVs but also to handle random arrivals of EVs. In addition, an approach for equitable distribution strategy is suggested for comparison with a locally optimal scheduling. It is found that the equitable distribution method efficiently handles an enormous fleet of PEVs. Furthermore, the equitable distribution technique is observed to work well in handling multiple PEVs. Simulated outcome verify the efficacy of the proposed scheme.
{"title":"An Efficient Scheduling Scheme for Plug-In Electric Vehicles","authors":"D. Rashmi, S. Sivasubramani","doi":"10.1109/GlobConHT56829.2023.10087880","DOIUrl":"https://doi.org/10.1109/GlobConHT56829.2023.10087880","url":null,"abstract":"Plug-in electric vehicles (PEVs) will significantly impact the power system due to their interactions with the grid. Grid to Vehicle (G2V) and Vehicle to Grid (V2G) transactions can happen between PEVs and the grid. In order to overcome the impact of charging and discharging of PEV s,’ an intelligent scheduling scheme is essential. This work proposes two optimum scheduling techniques for PEV G2V and V2G transactions, namely, a locally optimum scheduling strategy as well as an equitable distribution strategy. An effective scheduling strategy is developed by first formulating a local scheduling optimization issue, which intends to reduce the overall cost of the EVs in the current EV fleet of the local group. The particle swarm optimization (PSO) algorithm is used to solve the optimization problem. The locally optimal scheduling scheme is not only able to handle a large number of EVs but also to handle random arrivals of EVs. In addition, an approach for equitable distribution strategy is suggested for comparison with a locally optimal scheduling. It is found that the equitable distribution method efficiently handles an enormous fleet of PEVs. Furthermore, the equitable distribution technique is observed to work well in handling multiple PEVs. Simulated outcome verify the efficacy of the proposed scheme.","PeriodicalId":355921,"journal":{"name":"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122970256","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 : 2023-03-11DOI: 10.1109/GlobConHT56829.2023.10087723
Shakti Vashisth, P. Agrawal, N. Gupta, K.R. Naizi, A. Swarnkar
Electric vehicles (EVs) pertain substantial potential to develop current transportation systems with low carbon impression. The integration of a large number of EVs will impose challenges to distribution system operations owing to a significant increase in peak demand on account of home charging. This necessitates the integration of capital-intensive distributed energy resources (DERs). This paper proposes a suitable strategy for EV home charging (EHC) to relieve stressed operating conditions of distribution systems in order to defer investment in DERs. The strategy employs an EV Energy Management System (EEMS) that coordinates home EV charging with real-time pricing (RTP) of electricity. More realistic scenarios are created by the normal distribution of arrival times of EVs, initial state of charge (SOC) levels, and capacities of EV batteries. The simulation results on the standard 33-bus distribution system reveal that the proposed strategy curtails increased peak demand, improves node voltage profile, reduces power losses, and provides financial gains to EV owners.
{"title":"A Novel Strategy for Electric Vehicle Home Charging to Defer Investment on Distributed Energy Resources","authors":"Shakti Vashisth, P. Agrawal, N. Gupta, K.R. Naizi, A. Swarnkar","doi":"10.1109/GlobConHT56829.2023.10087723","DOIUrl":"https://doi.org/10.1109/GlobConHT56829.2023.10087723","url":null,"abstract":"Electric vehicles (EVs) pertain substantial potential to develop current transportation systems with low carbon impression. The integration of a large number of EVs will impose challenges to distribution system operations owing to a significant increase in peak demand on account of home charging. This necessitates the integration of capital-intensive distributed energy resources (DERs). This paper proposes a suitable strategy for EV home charging (EHC) to relieve stressed operating conditions of distribution systems in order to defer investment in DERs. The strategy employs an EV Energy Management System (EEMS) that coordinates home EV charging with real-time pricing (RTP) of electricity. More realistic scenarios are created by the normal distribution of arrival times of EVs, initial state of charge (SOC) levels, and capacities of EV batteries. The simulation results on the standard 33-bus distribution system reveal that the proposed strategy curtails increased peak demand, improves node voltage profile, reduces power losses, and provides financial gains to EV owners.","PeriodicalId":355921,"journal":{"name":"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122662644","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 : 2023-03-11DOI: 10.1109/GlobConHT56829.2023.10087733
Ashish Patel, Sisir Kumar Yadav, H. Mathur
Single-phase inverters integrating battery storage and renewable energy sources are becoming popular among resi-dential electricity consumers because of the need for reliable and quality power, pollution reduction, and savings in electricity costs. Gird-connected inverters have a multi-mode operation and are preferable over isolated ones, but their high complexity and cost are a concern. Battery integration with such inverters requires a high-voltage battery bank, which increases the cost further. Also, most single-phase grid-tied inverters don't support power quality compensation. This paper proposes an integrated power converter system forming a single-phase home grid, addressing the above-mentioned issues. The proposed approach integrates a low-voltage battery (48V) at the DC link of the grid-tied inverter using a high-gain bidirectional converter. It also enhances the capability of the single-phase grid-tied inverter to compensate for the power quality issues such as reactive power and non-linear current of the load. The proposed system is validated using MATLAB/Simulink simulation.
{"title":"A Single-Phase Grid-Tied Converter System Integrating Solar PV, Battery and Compensating Power Quality","authors":"Ashish Patel, Sisir Kumar Yadav, H. Mathur","doi":"10.1109/GlobConHT56829.2023.10087733","DOIUrl":"https://doi.org/10.1109/GlobConHT56829.2023.10087733","url":null,"abstract":"Single-phase inverters integrating battery storage and renewable energy sources are becoming popular among resi-dential electricity consumers because of the need for reliable and quality power, pollution reduction, and savings in electricity costs. Gird-connected inverters have a multi-mode operation and are preferable over isolated ones, but their high complexity and cost are a concern. Battery integration with such inverters requires a high-voltage battery bank, which increases the cost further. Also, most single-phase grid-tied inverters don't support power quality compensation. This paper proposes an integrated power converter system forming a single-phase home grid, addressing the above-mentioned issues. The proposed approach integrates a low-voltage battery (48V) at the DC link of the grid-tied inverter using a high-gain bidirectional converter. It also enhances the capability of the single-phase grid-tied inverter to compensate for the power quality issues such as reactive power and non-linear current of the load. The proposed system is validated using MATLAB/Simulink simulation.","PeriodicalId":355921,"journal":{"name":"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)","volume":"152 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122931438","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 : 2023-03-11DOI: 10.1109/GlobConHT56829.2023.10087774
Rishiraj K. Thakur, R. Pindoriya, Rajeev Kumar, B. Rajpurohit
EVs and HEVs with complex power transmission mechanisms from the source (PMSM) to the load (live wheels) include coupled shafts of varied functionalities along with step-up and step-down gears, pulleys, couplers, and other intermediate elements based upon torque to speed gain requirement at the load. Due to the power electronics converter circuit, and stator winding, the driving techniques for Permanent Magnet Synchronous Motor (PMSM) have unavoidable torque ripples, and these fluctuations lead to mechanical anomalies like vibration, which become havoc at resonance. In the present study, a novel Random Band Hysteresis Current Control (RBHCC) is illustrated and its torsional vibrational signatures using an advanced Modal Participation Factor (MPF) based optimized lumped model technique is presented and also compared with the standard SPWM technique. The analytical and experimental results show a reduction in total vibration by 34% with an 18.75% reduction in mechanical vibration and a 39% reduction in Acoustic Noise in the proposed RBHCC technique compared to the SPWM technique, which has a positive mark on system reliability and power transmission efficiency. Analytical and experimental studies were performed on 1.07- kW, 4-poles, 36-slots, and 3-phase PMSM drive coupled with a 2.5 kW load DC generator.
{"title":"An MPF method-based Torsional Vibration Analysis of RBHCC-driven PMSM Coupled System in comparison with SPWM Technique for EVs and HEVs Transmission","authors":"Rishiraj K. Thakur, R. Pindoriya, Rajeev Kumar, B. Rajpurohit","doi":"10.1109/GlobConHT56829.2023.10087774","DOIUrl":"https://doi.org/10.1109/GlobConHT56829.2023.10087774","url":null,"abstract":"EVs and HEVs with complex power transmission mechanisms from the source (PMSM) to the load (live wheels) include coupled shafts of varied functionalities along with step-up and step-down gears, pulleys, couplers, and other intermediate elements based upon torque to speed gain requirement at the load. Due to the power electronics converter circuit, and stator winding, the driving techniques for Permanent Magnet Synchronous Motor (PMSM) have unavoidable torque ripples, and these fluctuations lead to mechanical anomalies like vibration, which become havoc at resonance. In the present study, a novel Random Band Hysteresis Current Control (RBHCC) is illustrated and its torsional vibrational signatures using an advanced Modal Participation Factor (MPF) based optimized lumped model technique is presented and also compared with the standard SPWM technique. The analytical and experimental results show a reduction in total vibration by 34% with an 18.75% reduction in mechanical vibration and a 39% reduction in Acoustic Noise in the proposed RBHCC technique compared to the SPWM technique, which has a positive mark on system reliability and power transmission efficiency. Analytical and experimental studies were performed on 1.07- kW, 4-poles, 36-slots, and 3-phase PMSM drive coupled with a 2.5 kW load DC generator.","PeriodicalId":355921,"journal":{"name":"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131460116","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 : 2023-03-11DOI: 10.1109/GlobConHT56829.2023.10087872
Bala Naga Lingaiah Ande, N. Tummuru
This paper proposes a zero phase angle error (ZPE) based frequency control approach to realize soft switching in inductive power transfer (IPT) charging of energy storage system applications. IPT is influenced by many parameters, such as the coupling coefficient between the transmitting and receiving coils and the load power requirement. This introduces new challenges, such as hard switching of the power converters in the system, which increases the power losses and degrades the power conversion efficiency. Furthermore, the switching devices need to be selected with higher ratings which increases the cost of the converters. To address these issues, an optimal frequency operation of the converter is proposed to achieve soft switching and transmit the maximum power to the load. The optimal frequency control is developed by minimizing the ZPE between the excitation voltage and current from the transmitting side. This makes the controller not require information on the IPT system's receiver side voltages and currents to achieve the aforementioned goals. Furthermore, the performance of the proposed control algorithm is validated using digital simulations. Finally, the IPT system is developed and tested for a maximum power of $1.7text{kW}$ under open loop conditions, with experimental results presented in this paper.
{"title":"A ZPE Based Frequency Control Approach to Realize Soft Switching in Contactless Power Transfer of Energy Storage System Applications","authors":"Bala Naga Lingaiah Ande, N. Tummuru","doi":"10.1109/GlobConHT56829.2023.10087872","DOIUrl":"https://doi.org/10.1109/GlobConHT56829.2023.10087872","url":null,"abstract":"This paper proposes a zero phase angle error (ZPE) based frequency control approach to realize soft switching in inductive power transfer (IPT) charging of energy storage system applications. IPT is influenced by many parameters, such as the coupling coefficient between the transmitting and receiving coils and the load power requirement. This introduces new challenges, such as hard switching of the power converters in the system, which increases the power losses and degrades the power conversion efficiency. Furthermore, the switching devices need to be selected with higher ratings which increases the cost of the converters. To address these issues, an optimal frequency operation of the converter is proposed to achieve soft switching and transmit the maximum power to the load. The optimal frequency control is developed by minimizing the ZPE between the excitation voltage and current from the transmitting side. This makes the controller not require information on the IPT system's receiver side voltages and currents to achieve the aforementioned goals. Furthermore, the performance of the proposed control algorithm is validated using digital simulations. Finally, the IPT system is developed and tested for a maximum power of $1.7text{kW}$ under open loop conditions, with experimental results presented in this paper.","PeriodicalId":355921,"journal":{"name":"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)","volume":"562 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116519863","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 : 2023-03-11DOI: 10.1109/GlobConHT56829.2023.10087365
Bhavya Dhingra, Abhilasha Saini, A. Tomar
A smart grid is an automated electric grid that frequently monitors the working of a power system to control it and one of the most essential parts of a smart grid is a transmission line, which is used to carry a large amount of generated power in the power system. However, due to their exposure to the environment, these lines may experience a flow of anomalous electric current or faulty current, which can disrupt the regular operation of the power system and cause equipment failure. using machine learning, this research provides a novel automated framework for identifying which type of fault is occurring in the system without having to visit the actual fault location. With an area under the curve (AUC) score of 99.95 % and an accuracy of 99.15 %, the suggested model combines quadratic discriminant analysis coupled with pre-processing techniques like feature engineering to detect if the system has defects and the type of faults. The suggested model generates all of these results in less than 0.015 seconds. Knowing which type of problem is occurring in the power system using voltage and current data can improve power system cost savings by lowering the use of relays and creating effective ways to automate fault handling for smart grids.
{"title":"A Machine Learning based Fault Identification Framework for Smart Grid Automation","authors":"Bhavya Dhingra, Abhilasha Saini, A. Tomar","doi":"10.1109/GlobConHT56829.2023.10087365","DOIUrl":"https://doi.org/10.1109/GlobConHT56829.2023.10087365","url":null,"abstract":"A smart grid is an automated electric grid that frequently monitors the working of a power system to control it and one of the most essential parts of a smart grid is a transmission line, which is used to carry a large amount of generated power in the power system. However, due to their exposure to the environment, these lines may experience a flow of anomalous electric current or faulty current, which can disrupt the regular operation of the power system and cause equipment failure. using machine learning, this research provides a novel automated framework for identifying which type of fault is occurring in the system without having to visit the actual fault location. With an area under the curve (AUC) score of 99.95 % and an accuracy of 99.15 %, the suggested model combines quadratic discriminant analysis coupled with pre-processing techniques like feature engineering to detect if the system has defects and the type of faults. The suggested model generates all of these results in less than 0.015 seconds. Knowing which type of problem is occurring in the power system using voltage and current data can improve power system cost savings by lowering the use of relays and creating effective ways to automate fault handling for smart grids.","PeriodicalId":355921,"journal":{"name":"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)","volume":"210 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132230599","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 : 2023-03-11DOI: 10.1109/GlobConHT56829.2023.10087542
Giacomo Basile, Sara Leccese, A. Petrillo, R. Rizzo, S. Santini
This paper addresses the path-tracking control problem for Connected Autonomous Electric Vehicles (CAEVs) moving in a smart Cooperative Connected Automated Mobility (CCAM) environment, where a smart infrastructure suggests the reference behaviour to achieve. To solve this problem, a novel energy-efficient Deep Deterministic Policy Gradient-based (DDPG) Algorithm, able to minimize its energy consumption while guaranteeing the optimal tracking of the suggested path, is proposed. Specifically, in order to improve the power autonomy and the battery state of charge (SOC), a Comprehensive Power-based Electric Vehicle Consumption Model (CPEM) is exploited for the training of the DDPG agent. The training process confirms the capability of DDPG agent into learning the safe eco-driving policy, while a case of study proves the advantages and the performance of the overall closed-loop of the proposed control strategy.
{"title":"Sustainable DDPG-based Path Tracking For Connected Autonomous Electric Vehicles in extra-urban scenarios","authors":"Giacomo Basile, Sara Leccese, A. Petrillo, R. Rizzo, S. Santini","doi":"10.1109/GlobConHT56829.2023.10087542","DOIUrl":"https://doi.org/10.1109/GlobConHT56829.2023.10087542","url":null,"abstract":"This paper addresses the path-tracking control problem for Connected Autonomous Electric Vehicles (CAEVs) moving in a smart Cooperative Connected Automated Mobility (CCAM) environment, where a smart infrastructure suggests the reference behaviour to achieve. To solve this problem, a novel energy-efficient Deep Deterministic Policy Gradient-based (DDPG) Algorithm, able to minimize its energy consumption while guaranteeing the optimal tracking of the suggested path, is proposed. Specifically, in order to improve the power autonomy and the battery state of charge (SOC), a Comprehensive Power-based Electric Vehicle Consumption Model (CPEM) is exploited for the training of the DDPG agent. The training process confirms the capability of DDPG agent into learning the safe eco-driving policy, while a case of study proves the advantages and the performance of the overall closed-loop of the proposed control strategy.","PeriodicalId":355921,"journal":{"name":"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134303639","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 : 2023-03-11DOI: 10.1109/GlobConHT56829.2023.10087483
Vinay Kumar Singh, N. Padhy, Y. V. Hote
In this article a novel power control architecture is proposed to control a three-phase voltage source converter (VSC) operating under complex conditions. VSC output is coupled with LCL filter; which filters out unwanted harmonic components. Based on the obtained model from the fractional characteristic of the passive elements a model-based controller is designed. The proposed control structure is adaptive; capable of rejecting disturbances, reducing power, voltage & frequency oscillations from the system; eventually results in desired performance Indices as per the grid codes. The proposed power control structure is validated using MATLAB/Simulink followed by laboratory-based experimentation using a hardware test-bed consisting of OPAL-RT controller and RTDS simulator for BESS integration into local distribution network.
{"title":"Simplified Modelling and Control of Voltage Source Converter Integrated to Renewable Energy Resources","authors":"Vinay Kumar Singh, N. Padhy, Y. V. Hote","doi":"10.1109/GlobConHT56829.2023.10087483","DOIUrl":"https://doi.org/10.1109/GlobConHT56829.2023.10087483","url":null,"abstract":"In this article a novel power control architecture is proposed to control a three-phase voltage source converter (VSC) operating under complex conditions. VSC output is coupled with LCL filter; which filters out unwanted harmonic components. Based on the obtained model from the fractional characteristic of the passive elements a model-based controller is designed. The proposed control structure is adaptive; capable of rejecting disturbances, reducing power, voltage & frequency oscillations from the system; eventually results in desired performance Indices as per the grid codes. The proposed power control structure is validated using MATLAB/Simulink followed by laboratory-based experimentation using a hardware test-bed consisting of OPAL-RT controller and RTDS simulator for BESS integration into local distribution network.","PeriodicalId":355921,"journal":{"name":"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115188862","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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