scholarly journals Indicator-Based Methodology for Assessing EV Charging Infrastructure Using Exploratory Data Analysis

Energies ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 1869 ◽  
Author(s):  
Alexandre Lucas ◽  
Giuseppe Prettico ◽  
Marco Flammini ◽  
Evangelos Kotsakis ◽  
Gianluca Fulli ◽  
...  
Keyword(s):  
Urban Areas ◽  
Energy Demand ◽  
Energy Use ◽  
Spatial Density ◽  
Carbon Intensity ◽  
Impact Indicator ◽  
Charging Infrastructure ◽  
Smart Charging ◽  
The Impact ◽  
Ev Charging

Electric vehicle (EV) charging infrastructure rollout is well under way in several power systems, namely North America, Japan, Europe, and China. In order to support EV charging infrastructures design and operation, little attempt has been made to develop indicator-based methods characterising such networks across different regions. This study defines an assessment methodology, composed by eight indicators, allowing a comparison among EV public charging infrastructures. The proposed indicators capture the following: energy demand from EVs, energy use intensity, charger’s intensity distribution, the use time ratios, energy use ratios, the nearest neighbour distance between chargers and availability, the total service ratio, and the carbon intensity as an environmental impact indicator. We apply the methodology to a dataset from ElaadNL, a reference smart charging provider in The Netherlands, using open source geographic information system (GIS) and R software. The dataset reveals higher energy intensity in six urban areas and that 50% of energy supplied comes from 19.6% of chargers. Correlations of spatial density are strong and nearest neighbouring distances range from 1101 to 9462 m. Use time and energy use ratios are 11.21% and 3.56%. The average carbon intensity is 4.44 gCO2eq/MJ. Finally, the indicators are used to assess the impact of relevant public policies on the EV charging infrastructure use and roll-out.

scholarly journals Impact of Electric Vehicle Charging Strategy on the Long-Term Planning of an Isolated Microgrid

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3455
Author(s):  
Jean-Michel Clairand ◽  
Carlos Álvarez-Bel ◽  
Javier Rodríguez-García ◽  
Guillermo Escrivá-Escrivá
Keyword(s):  
Renewable Energy ◽  
Fossil Fuels ◽  
Energy Use ◽  
Environmental Benefits ◽  
Electric Vehicle Charging ◽  
Power Generation Planning ◽  
Smart Charging ◽  
The Impact ◽  
Ev Charging ◽  
Charging Strategy

Isolated microgrids, such as islands, rely on fossil fuels for electricity generation and include vehicle fleets, which poses significant environmental challenges. To address this, distributed energy resources based on renewable energy and electric vehicles (EVs) have been deployed in several places. However, they present operational and planning concerns. Hence, the aim of this paper is to propose a two-level microgrid problem. The first problem considers an EV charging strategy that minimizes charging costs and maximizes the renewable energy use. The second level evaluates the impact of this charging strategy on the power generation planning of Santa Cruz Island, Galapagos, Ecuador. This planning model is simulated in HOMER Energy. The results demonstrate the economic and environmental benefits of investing in additional photovoltaic (PV) generation and in the EV charging strategy. Investing in PV and smart charging for EVs could reduce the N P C by 13.58%, but a reduction in the N P C of the EV charging strategy would result in up to 3.12%.

scholarly journals In-Company Smart Charging: Development of a Simulation Model to Facilitate a Smart EV Charging System

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6723
Author(s):  
Mike F. Voss ◽  
Steven P. Haveman ◽  
Gerrit Maarten Bonnema
Keyword(s):  
Co2 Emissions ◽  
Travel Behaviour ◽  
Daily Basis ◽  
Charging Infrastructure ◽  
Charging System ◽  
Smart Charging ◽  
Future Version ◽  
The Impact ◽  
Ev Charging ◽  
System Designs

Current electric vehicle (EV) charging systems have limited smart functionality, and most research focuses on load-balancing the national or regional grid. In this article, we focus on supporting the early design of a smart charging system that can effectively and efficiently charge a company’s EV fleet, maximizing the use of self-generated Photo-Voltaic energy. The support takes place in the form of the Vehicle Charging Simulation (VeCS) model. System performance is determined by operational costs, CO2 emissions and employee satisfaction. Two impactful smart charging functions concern adaptive charging speeds and charging point management. Simulation algorithms for these functions are developed. The VeCS model is developed to simulate implementation of a smart charging system incorporating both charging infrastructure and local Photo-Voltaics input, using a company’s travel and energy data, prior to having the EVs in place. The model takes into account travel behaviour, energy input and energy consumption on a daily basis. The model shows the number of charged vehicles, whether incomplete charges occur, and energy flow during the day. The model also facilitates simulation of an entire year to determine overall cost and emission benefits. It also estimates charging costs and CO2 emissions that can be compared to the non-EV situation. With the VeCS model, the impact of various system design and implementation choices can be explored before EVs are used. Two system designs are proposed for the case company; a short-term version with current technology and a future version with various smart functionalities. Overall, the model can contribute to substantiated advice for a company regarding implementation of charging infrastructure.

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 Sustainable Electric Vehicle Transportation

2021 ◽  
Vol 13 (22) ◽  
pp. 12379
Author(s):  
Raymond Kene ◽  
Thomas Olwal ◽  
Barend J. van Wyk
Keyword(s):  
Electric Vehicle ◽  
Energy Demand ◽  
Large Scale ◽  
Common Knowledge ◽  
Distribution Network ◽  
Electricity Grid ◽  
Current State ◽  
The World ◽  
The Impact ◽  
Ev Charging

The future direction of electric vehicle (EV) transportation in relation to the energy demand for charging EVs needs a more sustainable roadmap, compared to the current reliance on the centralised electricity grid system. It is common knowledge that the current state of electricity grids in the biggest economies of the world today suffer a perennial problem of power losses; and were not designed for the uptake and integration of the growing number of large-scale EV charging power demands from the grids. To promote sustainable EV transportation, this study aims to review the current state of research and development around this field. This study is significant to the effect that it accomplishes four major objectives. (1) First, the implication of large-scale EV integration to the electricity grid is assessed by looking at the impact on the distribution network. (2) Secondly, it provides energy management strategies for optimizing plug-in EVs load demand on the electricity distribution network. (3) It provides a clear direction and an overview on sustainable EV charging infrastructure, which is highlighted as one of the key factors that enables the promotion and sustainability of the EV market and transportation sector, re-engineered to support the United Nations Climate Change Agenda. Finally, a conclusion is made with some policy recommendations provided for the promotion of the electric vehicle market and widespread adoption in any economy of the world.

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 Impacts of Microclimate Conditions on the Energy Performance of Buildings in Urban Areas

Buildings ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 189 ◽  
Author(s):  
Javanroodi ◽  
M.Nik
Keyword(s):  
Urban Areas ◽  
Energy Demand ◽  
Weather Conditions ◽  
Energy Performance ◽  
Urban Morphology ◽  
Weather Data ◽  
Architectural Form ◽  
Energy Performance Of Buildings ◽  
Microclimate Conditions ◽  
The Impact

Urbanization trends have changed the morphology of cities in the past decades. Complex urban areas with wide variations in built density, layout typology, and architectural form have resulted in more complicated microclimate conditions. Microclimate conditions affect the energy performance of buildings and bioclimatic design strategies as well as a high number of engineering applications. However, commercial energy simulation engines that utilize widely-available mesoscale weather data tend to underestimate these impacts. These weather files, which represent typical weather conditions at a location, are mostly based on long-term metrological observations and fail to consider extreme conditions in their calculation. This paper aims to evaluate the impacts of hourly microclimate data in typical and extreme climate conditions on the energy performance of an office building in two different urban areas. Results showed that the urban morphology can reduce the wind speed by 27% and amplify air temperature by more than 14%. Using microclimate data, the calculated outside surface temperature, operating temperature and total energy demand of buildings were notably different to those obtained using typical regional climate model (RCM)–climate data or available weather files (Typical Meteorological Year or TMY), i.e., by 61%, 7%, and 21%, respectively. The difference in the hourly peak demand during extreme weather conditions was around 13%. The impact of urban density and the final height of buildings on the results are discussed at the end of the paper.

scholarly journals Modeling Thermal Interactions between Buildings in an Urban Context

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2382
Author(s):  
Xuan Luo ◽  
Tianzhen Hong ◽  
Yu-Hang Tang
Keyword(s):  
Energy Demand ◽  
Energy Use ◽  
Longwave Radiation ◽  
Radiant Heat ◽  
Urban Context ◽  
Exterior Surface ◽  
Radiation Exchange ◽  
Urban Planning And Design ◽  
New Feature ◽  
The Impact

Thermal interactions through longwave radiation exchange between buildings, especially in a dense urban environment, can strongly influence a building’s energy use and environmental impact. However, these interactions are either neglected or oversimplified in urban building energy modeling. We developed a new feature in EnergyPlus to explicitly consider this term in the surface heat balance calculations and developed an algorithm to batch calculating the surrounding surfaces’ view factors using a ray-tracing technique. We conducted a case study with a district in the Chicago downtown area to evaluate the longwave radiant heat exchange effects between urban buildings. Results show that the impact of the longwave radiant effects on annual energy use ranges from 0.1% to 3.3% increase for cooling and 0.3% to 3.6% decrease for heating, varying among individual buildings. At the district level, the total energy demand increases by 1.39% for cooling and decreases 0.45% for heating. We also observe the longwave radiation can increase the exterior surface temperature by up to 10 °C for certain exterior surfaces. These findings justify a detailed and accurate way to consider the thermal interactions between buildings in an urban context to inform urban planning and design.

scholarly journals Controllability Evaluation of EV Charging Infrastructure Transformed from Gas Stations in Distribution Networks with Renewables

Energies ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 1577
Author(s):  
Shuang Gao ◽  
Jianzhong Wu ◽  
Bin Xu
Keyword(s):  
Power Distribution ◽  
Queuing Theory ◽  
Distribution Networks ◽  
Temporal And Spatial Distribution ◽  
Charging Infrastructure ◽  
Optimal Dispatch ◽  
Gas Stations ◽  
Charging Stations ◽  
The Impact ◽  
Ev Charging

A considerable market share of electric vehicles (EVs) is expected in the near future, which leads to a transformation from gas stations to EV charging infrastructure for automobiles. EV charging stations will be integrated with the power grid to replace the fuel consumption at the gas stations for the same mobile needs. In order to evaluate the impact on distribution networks and the controllability of the charging load, the temporal and spatial distribution of the charging power is calculated by establishing mapping the relation between gas stations and charging facilities. Firstly, the arrival and parking period is quantified by applying queuing theory and defining membership function between EVs to parking lots. Secondly, the operational model of charging stations connected to the power distribution network is formulated, and the control variables and their boundaries are identified. Thirdly, an optimal control algorithm is proposed, which combines the configuration of charging stations and charging power regulation during the parking period of each individual EV. A two-stage hybrid optimization algorithm is developed to solve the reliability constrained optimal dispatch problem for EVs, with an EV aggregator installed at each charging station. Simulation results validate the proposed method in evaluating the controllability of EV charging infrastructure and the synergy effects between EV and renewable integration.

scholarly journals Optimal Charging of Plug-In Electric Vehicle: Considering Travel Behavior Uncertainties and Battery Degradation

2019 ◽  
Vol 9 (16) ◽  
pp. 3420 ◽  
Author(s):  
Tayarani ◽  
Jahangir ◽  
Nadafianshahamabadi ◽  
Golkar ◽  
Ahmadian ◽  
...  
Keyword(s):  
Travel Behavior ◽  
Energy Demand ◽  
Energy Use ◽  
Distribution Network ◽  
Sample Distribution ◽  
Smart Charging ◽  
Reliable Source ◽  
Network Operation ◽  
Battery Degradation ◽  
Charging Mode

The negative environmental impacts of using fossil fuel-powered vehicles underlined the need for inventing an alternative eco-friendly transportation fleet. Plug-in electrical vehicles (PEVs) are introduced to cut the continuing increase in energy use and carbon emission of the urban mobility. However, the increased demand for mobility, and therefore energy, can create constraints on the power network which can reduce the benefits of electrification as a certain and reliable source. Thus, the rise in the use of electric vehicles needs electric grids to be able to feed the increased energy demand while the current infrastructure supports it. In this paper, we introduce a methodological framework for scheduling smart PEVs charging by considering the uncertainties and battery degradation. This framework includes an economic model for charging and discharging of PEVs which has been implemented in a 21-node sample distribution network with a wind turbine as a distributed generation (DG) unit. Our proposed approach indicates that the optimal charging of the PEVs has a high impact on the distribution network operation, particularly under the high market penetration of PEVs. Thus, the smart grid to vehicle (G2V) charging mode is a potential solution to maximize the PEV’s owner profit, while considering the battery degradation cost of the PEVs. The simulation result indicates that smart charging effectuation is economical.

scholarly journals Driving Forces of Energy-Related CO2 Emissions Based on Expanded IPAT Decomposition Analysis: Evidence from ASEAN and Four Selected Countries

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 764 ◽  
Author(s):  
Jaruwan Chontanawat
Keyword(s):  
Population Growth ◽  
Co2 Emissions ◽  
Energy Demand ◽  
Energy Use ◽  
Driving Forces ◽  
Global Climate ◽  
Decomposition Analysis ◽  
Driving Factors ◽  
Carbon Intensity ◽  
Rapid Urbanization

ASEAN is a dynamic and diverse region which has experienced rapid urbanization and population growth. Their energy demand grew by 60% in the last 15 years. In 2013, about 3.6% of global greenhouse-gas emissions was emitted from this region and the share is expected to rise substantially. Hence, a better understanding of driving forces of the changes in CO2 emissions is important to tackle global climate change and develop appropriate policies. Using IPAT combined with variance analysis, this study aims to identify the main driving factors of CO2 emissions for ASEAN and four selected countries (Indonesia, Malaysia, Philippines and Thailand) during 1971–2013. The results show that population growth and economic growth were the main driving factors for increasing CO2 emissions for most of the countries. Fossil fuels play an important role in increasing CO2 emissions, however the growth in emissions was compensated by improved energy efficiency and carbon intensity of fossil energy. The results imply that to decouple energy use from high levels of emissions is important. Proper energy management through fuel substitution and decreasing emission intensity through technological upgrades have considerable potential to cut emissions.

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