scholarly journals Modeling the Impact of Electric Vehicle Charging Infrastructure on Regional Energy Systems: Fields of Action for an Improved e-Mobility Integration

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 7992
Author(s):  
Dominik Husarek ◽  
Vjekoslav Salapic ◽  
Simon Paulus ◽  
Michael Metzger ◽  
Stefan Niessen
Keyword(s):  
Peak Reduction ◽  
Charging Infrastructure ◽  
Infrastructure Networks ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Economic Framework ◽  
Infrastructure Investments ◽  
Grid Operators ◽  
The Impact ◽  
Charging Demand

Since e-Mobility is on the rise worldwide, large charging infrastructure networks are required to satisfy the upcoming charging demand. Planning these networks not only involves different objectives from grid operators, drivers and Charging Station (CS) operators alike but it also underlies spatial and temporal uncertainties of the upcoming charging demand. Here, we aim at showing these uncertainties and assess different levers to enable the integration of e-Mobility. Therefore, we introduce an Agent-based model assessing regional charging demand and infrastructure networks with the interactions between charging infrastructure and electric vehicles. A global sensitivity analysis is applied to derive general guidelines for integrating e-Mobility effectively within a region by considering the grid impact, the economic viability and the Service Quality of the deployed Charging Infrastructure (SQCI). We show that an improved macro-economic framework should enable infrastructure investments across different types of locations such as public, highway and work to utilize cross-locational charging peak reduction effects. Since the height of the residential charging peak depends up to 18% on public charger availability, supporting public charging infrastructure investments especially in highly utilized power grid regions is recommended.

scholarly journals Modeling Charging Infrastructure Requirements to Achieve a Holistic E-Mobility Integration in Regional Energy Systems

2021 ◽  
Author(s):  
Dominik Husarek ◽  
Simon Paulus ◽  
Michael Metzger ◽  
Vjekoslav Salapic ◽  
Stefan Niessen
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Mobility Model ◽  
Residential Areas ◽  
Charging Infrastructure ◽  
Charging System ◽  
Charging Station ◽  
Grid Operators ◽  
Regional Energy Systems ◽  
The Impact

Since E-Mobility is on the rise worldwide, large Charging Infrastructure (CI) networks are required to satisfy the upcoming Charging Demand (CD). Understanding this CD with its spatial and temporal uncertainties is important for grid operators to quantify the grid impact of Electric Vehicle integration and for Charging Station (CS) operators to assess long-term CI investments. Hence, we introduce an Agent-based E-Mobility Model assessing regional CI systems with their multi-directional interactions between CSs and vehicles. A Global Sensitivity Analysis (GSA) is applied to quantify the impact of 11 technical levers on 17 relevant charging system outputs. The GSA evaluates the E-Mobility integration in terms of grid impact, economic viability of CSs and Service Quality of the deployed Charging Infrastructure (SQCI). Based on this impact assessment we derive general guidelines for E-Mobility integration into regional systems. We found, inter alia, that CI policies should aim at allocating CSs across different types of locations to utilize cross-locational effects such as CSs at public locations affecting the charging peak in residential areas by up to 18%. Additionally, while improving the highway charging network is an effective lever to increase the SQCI in urban areas, public charging is an even stronger lever in rural areas.

scholarly journals Modeling Charging Infrastructure Requirements to Achieve a Holistic E-Mobility Integration in Regional Energy Systems

2021 ◽  
Author(s):  
Dominik Husarek ◽  
Simon Paulus ◽  
Michael Metzger ◽  
Vjekoslav Salapic ◽  
Stefan Niessen
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Mobility Model ◽  
Residential Areas ◽  
Charging Infrastructure ◽  
Charging System ◽  
Charging Station ◽  
Grid Operators ◽  
Regional Energy Systems ◽  
The Impact

Since E-Mobility is on the rise worldwide, large Charging Infrastructure (CI) networks are required to satisfy the upcoming Charging Demand (CD). Understanding this CD with its spatial and temporal uncertainties is important for grid operators to quantify the grid impact of Electric Vehicle integration and for Charging Station (CS) operators to assess long-term CI investments. Hence, we introduce an Agent-based E-Mobility Model assessing regional CI systems with their multi-directional interactions between CSs and vehicles. A Global Sensitivity Analysis (GSA) is applied to quantify the impact of 11 technical levers on 17 relevant charging system outputs. The GSA evaluates the E-Mobility integration in terms of grid impact, economic viability of CSs and Service Quality of the deployed Charging Infrastructure (SQCI). Based on this impact assessment we derive general guidelines for E-Mobility integration into regional systems. We found, inter alia, that CI policies should aim at allocating CSs across different types of locations to utilize cross-locational effects such as CSs at public locations affecting the charging peak in residential areas by up to 18%. Additionally, while improving the highway charging network is an effective lever to increase the SQCI in urban areas, public charging is an even stronger lever in rural areas.

scholarly journals Modular Approach to Ultra-fast Charging Stations

2021 ◽  
Author(s):  
Carola Leone ◽  
Michela Longo
Keyword(s):  
Impact Analysis ◽  
Road Transport ◽  
Modular Approach ◽  
Long Distance ◽  
Charging Infrastructure ◽  
Charging Station ◽  
Fast Charging ◽  
Modular Architectures ◽  
The Impact ◽  
Fast Charging Station

AbstractRoad transport electrification is essential for meeting the European Union's goals of decarbonization and climate change. In this context, an Ultra-Fast Charging (UFC) system is deemed necessary to facilitate the massive penetration of Electric Vehicles (EVs) on the market; particularly as medium-long distance travels are concerned. Anyway, an ultra-fast charging infrastructure represents the most critical point as regards hardware technology, grid-related issues, and financial sustainability. Thus far, this paper presents an impact analysis of a fast-charging station on the grid in terms of power consumption, obtained by the Monte Carlo simulation. Simulation results show that it is not economical convenient size the assumed ultra-fast charging station for the maximum possible power also considering its high impact on the grid. In view of the results obtained from the impact analysis, the last part of the paper focuses on finding a method to reduce the power installed for the DC/DC stage while keeping the possibility for the electric vehicle to charge at their maximum power. To achieve this goal a modular approach is proposed. Finally, two different modular architectures are presented and compared. In both the solutions, the probability of having EVs charging at limited power is less than 5%.

A Tale of Two Entities

2021 ◽  
Vol 2 (2) ◽  
pp. 1-21
Author(s):  
Hossam ElHussini ◽  
Chadi Assi ◽  
Bassam Moussa ◽  
Ribal Atallah ◽  
Ali Ghrayeb
Keyword(s):  
Power Flow ◽  
Power Grid ◽  
Communication Protocols ◽  
Charging Infrastructure ◽  
Electric Vehicle Charging ◽  
Public Data ◽  
Simulation Based ◽  
Charging Stations ◽  
The Impact ◽  
Ev Charging

With the growing market of Electric Vehicles (EV), the procurement of their charging infrastructure plays a crucial role in their adoption. Within the revolution of Internet of Things, the EV charging infrastructure is getting on board with the introduction of smart Electric Vehicle Charging Stations (EVCS), a myriad set of communication protocols, and different entities. We provide in this article an overview of this infrastructure detailing the participating entities and the communication protocols. Further, we contextualize the current deployment of EVCSs through the use of available public data. In the light of such a survey, we identify two key concerns, the lack of standardization and multiple points of failures, which renders the current deployment of EV charging infrastructure vulnerable to an array of different attacks. Moreover, we propose a novel attack scenario that exploits the unique characteristics of the EVCSs and their protocol (such as high power wattage and support for reverse power flow) to cause disturbances to the power grid. We investigate three different attack variations; sudden surge in power demand, sudden surge in power supply, and a switching attack. To support our claims, we showcase using a real-world example how an adversary can compromise an EVCS and create a traffic bottleneck by tampering with the charging schedules of EVs. Further, we perform a simulation-based study of the impact of our proposed attack variations on the WSCC 9 bus system. Our simulations show that an adversary can cause devastating effects on the power grid, which might result in blackout and cascading failure by comprising a small number of EVCSs.

scholarly journals Electric Charging Demand Location Model—A User- and Destination-Based Locating Approach for Electric Vehicle Charging Stations

2019 ◽  
Vol 11 (8) ◽  
pp. 2301 ◽  
Author(s):  
Raphaela Pagany ◽  
Anna Marquardt ◽  
Roland Zink
Keyword(s):  
Neighborhood Effects ◽  
Energy Demand ◽  
Electric Energy ◽  
Transportation Systems ◽  
Walking Distance ◽  
Vehicle Ownership ◽  
Charging Infrastructure ◽  
Electric Vehicle Charging ◽  
Charging Stations ◽  
Charging Demand

In recent years, with the increased focus on climate protection, electric vehicles (EVs) have become a relevant alternative to conventional motorized vehicles. Even though the market share of EVs is still comparatively low, there are ongoing considerations for integrating EVs in transportation systems. Along with pushing EV sales numbers, the installation of charging infrastructure is necessary. This paper presents a user- and destination-based approach for locating charging stations (CSs) for EVs—the electric charging demand location (ECDL) model. With regard to the daily activities of potential EV users, potential positions for CSs are derived on a micro-location level in public and semipublic spaces using geographic information systems (GIS). Depending on the vehicle users’ dwell times and visiting frequencies at potential points of interest (POIs), the charging demand at such locations is calculated. The model is mainly based on a survey analyzing the average time spent per daily activity, regional data about driver and vehicle ownership numbers, and the georeferenced localization of regularly visited POIs. Optimal sites for parking and charging EVs within the POIs neighborhood are selected based on walking distance calculations, including spatial neighborhood effects, such as the density of POIs. In a case study in southeastern Germany, the model identifies concrete places with the highest overall demand for CSs, resulting in an extensive coverage of the electric energy demand while considering as many destinations within the acceptable walking distance threshold as possible.

scholarly journals Optimal Distribution Grid Operation Using DLMP-Based Pricing for Electric Vehicle Charging Infrastructure in a Smart City

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 686 ◽  
Author(s):  
Bruno Canizes ◽  
João Soares ◽  
Zita Vale ◽  
Juan Corchado
Keyword(s):  
Dynamic Pricing ◽  
Distribution System ◽  
Smart City ◽  
User Behavior ◽  
Distribution Grid ◽  
Charging Infrastructure ◽  
Energy Pricing ◽  
Electric Vehicle Charging ◽  
The Impact ◽  
Ev Charging

The use of electric vehicles (EVs) is growing in popularity each year, and as a result, considerable demand increase is expected in the distribution network (DN). Additionally, the uncertainty of EV user behavior is high, making it urgent to understand its impact on the network. Thus, this paper proposes an EV user behavior simulator, which operates in conjunction with an innovative smart distribution locational marginal pricing based on operation/reconfiguration, for the purpose of understanding the impact of the dynamic energy pricing on both sides: the grid and the user. The main goal, besides the distribution system operator (DSO) expenditure minimization, is to understand how and to what extent dynamic pricing of energy for EV charging can positively affect the operation of the smart grid and the EV charging cost. A smart city with a 13-bus DN and a high penetration of distributed energy resources is used to demonstrate the application of the proposed models. The results demonstrate that dynamic energy pricing for EV charging is an efficient approach that increases monetary savings considerably for both the DSO and EV users.

scholarly journals Demand Calculation Method for Electric Vehicle Charging Station Locating and Deployment

2019 ◽  
Author(s):  
Csaba Csiszár
Keyword(s):  
Electric Vehicle ◽  
Calculation Method ◽  
Energy Demand ◽  
Charging Infrastructure ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Territorial Unit ◽  
Mobility System ◽  
Potential Demand ◽  
Vehicle Charging

To develop, plan, implement and operate the electric road mobility system, especially the charging infrastructure, the existing and potential demand must be revealed for several time horizons. Accordingly, the aim of the research was to elaborate a calculation method for electric vehicle charging demand and to determine the public charging infrastructure locating principles. The research questions were: how many and what kind of vehicles will be used; where, when and how long they will be charged; what aspects and how influence the charging station deployment. The number of charging points to be installed, the energy demand and capacity management parameters can be also determined using the revealed correlations. The calculation method is adaptable to any territorial unit and any time horizon. It is the basis of charging station locating methods, which is demonstrated through two novel geoinformatics applications.

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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