EPE Association: EPE 2022 - DS2r: Smart Charging and Vehicle to Grid Interaction

EPE 2022 - DS2r: Smart Charging and Vehicle to Grid Interaction
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 2022 ECCE Europe - Conference > EPE 2022 - Topic 08: Electric Vehicle Propulsion Systems and their Energy Storage > EPE 2022 - DS2r: Smart Charging and Vehicle to Grid Interaction

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   Optimization of electric vehicle charge scheduling with consideration of battery degradation
By Raka JOVANOVIC [View]
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Abstract: In this work, we explore the potential of exploiting the demand-flexibility of electric vehicles (EVs) for flattening the electricity duck curve that emerge as a result of growing solar power production. The focus is on vehicle-to-grid technology in which smart charging allows bidirectional energy flow between EVs and the utility grid. The main objective of this study is to evaluate the impact of V2G technologies on battery degradation. To do that a mathematical model is developed in the form of a mixed integer linear program (MILP). In the MILP the battery degradation is modeled based on charge/discharge cycles using the rising edge method for which appropriate constraints are provided. The proposed method is used to asses the relation between battery degradation and the level of flattening of the duck curve that can be achieved in V2G systems at park and ride facilities. The conducted computational experiments, based on real world data, show that the additional degradation caused by battery discharge in such systems can be substantial and can reach close to 9\\% of battery degradation in standard V2G systems.

   Smart Charging Strategy for Electric Vehicles Using an Optimized FuzzyLogic System
By Mehrdad GHOLAMI [View]
[Download]

Abstract: The increasing growth of electric vehicles (EVs) may arise as a challenge of increasing the load. Therefore, energy management in microgrids, including renewable energy resources such as PV systems,would be essential. Moreover, providing a smart charging pattern can optimize the overall cost of energy in a microgrid. In this paper, a genetic algorithm-based optimized fuzzy technique is developed,which has simple implementation such as rule-based methods and provides the optimal operation. Theproposed scheme is simulated in MATLAB/Simulink environment for a case study. Results show theeffectiveness of the proposed approach in comparison to conventional models.

EPE 2022 - DS2r: Smart Charging and Vehicle to Grid Interaction
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 2022 ECCE Europe - Conference > EPE 2022 - Topic 08: Electric Vehicle Propulsion Systems and their Energy Storage > EPE 2022 - DS2r: Smart Charging and Vehicle to Grid Interaction
	[return to parent folder]

	Optimization of electric vehicle charge scheduling with consideration of battery degradation By Raka JOVANOVIC	[View] [Download]
Abstract: In this work, we explore the potential of exploiting the demand-flexibility of electric vehicles (EVs) for flattening the electricity duck curve that emerge as a result of growing solar power production. The focus is on vehicle-to-grid technology in which smart charging allows bidirectional energy flow between EVs and the utility grid. The main objective of this study is to evaluate the impact of V2G technologies on battery degradation. To do that a mathematical model is developed in the form of a mixed integer linear program (MILP). In the MILP the battery degradation is modeled based on charge/discharge cycles using the rising edge method for which appropriate constraints are provided. The proposed method is used to asses the relation between battery degradation and the level of flattening of the duck curve that can be achieved in V2G systems at park and ride facilities. The conducted computational experiments, based on real world data, show that the additional degradation caused by battery discharge in such systems can be substantial and can reach close to 9\\% of battery degradation in standard V2G systems.

	Smart Charging Strategy for Electric Vehicles Using an Optimized FuzzyLogic System By Mehrdad GHOLAMI	[View] [Download]
Abstract: The increasing growth of electric vehicles (EVs) may arise as a challenge of increasing the load. Therefore, energy management in microgrids, including renewable energy resources such as PV systems,would be essential. Moreover, providing a smart charging pattern can optimize the overall cost of energy in a microgrid. In this paper, a genetic algorithm-based optimized fuzzy technique is developed,which has simple implementation such as rule-based methods and provides the optimal operation. Theproposed scheme is simulated in MATLAB/Simulink environment for a case study. Results show theeffectiveness of the proposed approach in comparison to conventional models.