Charging a renewable future: The impact of electric vehicle charging intelligence on energy storage requirements to meet renewable portfolio standards

2016 ◽  
Vol 336 ◽  
pp. 63-74 ◽  
Author(s):  
Kate E. Forrest ◽  
Brian Tarroja ◽  
Li Zhang ◽  
Brendan Shaffer ◽  
Scott Samuelsen
Keyword(s):  
Energy Storage ◽  
Electric Vehicle ◽  
Renewable Portfolio Standards ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
The Impact

scholarly journals Optimized Strategic Planning of Future Norwegian Low-Voltage Networks with a Genetic Algorithm Applying Empirical Electric Vehicle Charging Data

Electricity ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 91-109
Author(s):  
Julian Wruk ◽  
Kevin Cibis ◽  
Matthias Resch ◽  
Hanne Sæle ◽  
Markus Zdrallek
Keyword(s):  
Genetic Algorithm ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Low Voltage ◽  
Network Planning ◽  
Voltage Regulation ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
The Impact

This article outlines methods to facilitate the assessment of the impact of electric vehicle charging on distribution networks at planning stage and applies them to a case study. As network planning is becoming a more complex task, an approach to automated network planning that yields the optimal reinforcement strategy is outlined. Different reinforcement measures are weighted against each other in terms of technical feasibility and costs by applying a genetic algorithm. Traditional reinforcements as well as novel solutions including voltage regulation are considered. To account for electric vehicle charging, a method to determine the uptake in equivalent load is presented. For this, measured data of households and statistical data of electric vehicles are combined in a stochastic analysis to determine the simultaneity factors of household load including electric vehicle charging. The developed methods are applied to an exemplary case study with Norwegian low-voltage networks. Different penetration rates of electric vehicles on a development path until 2040 are considered.

scholarly journals DC Nanogrids for Integration of Demand Response and Electric Vehicle Charging Infrastructures: Appraisal, Optimal Scheduling and Analysis

Electronics ◽  
2021 ◽  
Vol 10 (20) ◽  
pp. 2484
Author(s):  
Salwan Ali Habeeb ◽  
Marcos Tostado-Véliz ◽  
Hany M. Hasanien ◽  
Rania A. Turky ◽  
Wisam Kaream Meteab ◽  
...  
Keyword(s):  
Energy Storage ◽  
Electric Vehicle ◽  
Demand Response ◽  
Smart Grids ◽  
Optimal Scheduling ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Battery Energy ◽  
Storage Demand ◽  
Demand Response Programs

With the development of electronic infrastructures and communication technologies and protocols, electric grids have evolved towards the concept of Smart Grids, which enable the communication of the different agents involved in their operation, thus notably increasing their efficiency. In this context, microgrids and nanogrids have emerged as invaluable frameworks for optimal integration of renewable sources, electric mobility, energy storage facilities and demand response programs. This paper discusses a DC isolated nanogrid layout for the integration of renewable generators, battery energy storage, demand response activities and electric vehicle charging infrastructures. Moreover, a stochastic optimal scheduling tool is developed for the studied nanogrid, suitable for operators integrated into local service entities along with the energy retailer. A stochastic model is developed for fast charging stations in particular. A case study serves to validate the developed tool and analyze the economical and operational implications of demand response programs and charging infrastructures. Results evidence the importance of demand response initiatives in the economic profit of the retailer.

scholarly journals Comparison and Analysis of GPS Measured Electric Vehicle Charging Demand: The Case of Western Sweden and Seattle

2021 ◽  
Vol 9 ◽  
Author(s):  
Elias Hartvigsson ◽  
Niklas Jakobsson ◽  
Maria Taljegard ◽  
Mikael Odenberger
Keyword(s):  
United States ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
The United States ◽  
Power Demand ◽  
Driving Patterns ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
The Impact ◽  
Charging Demand

Electrification of transportation using electric vehicles has a large potential to reduce transport related emissions but could potentially cause issues in generation and distribution of electricity. This study uses GPS measured driving patterns from conventional gasoline and diesel cars in western Sweden and Seattle, United States, to estimate and analyze expected charging coincidence assuming these driving patterns were the same for electric vehicles. The results show that the electric vehicle charging power demand in western Sweden and Seattle is 50–183% higher compared to studies that were relying on national household travel surveys in Sweden and United States. The after-coincidence charging power demand from GPS measured driving behavior converges at 1.8 kW or lower for Sweden and at 2.1 kW or lower for the United States The results show that nominal charging power has the largest impact on after-coincidence charging power demand, followed by the vehicle’s electricity consumption and lastly the charging location. We also find that the reduction in charging demand, when charging is moved in time, is largest for few vehicles and reduces as the number of vehicles increase. Our results are important when analyzing the impact from large scale introduction of electric vehicles on electricity distribution and generation.

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