scholarly journals Data for Heuristic Optimization of Electric Vehicles’ Charging Configuration Based on Loading Parameters

Data ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. 102 ◽  
Author(s):  
Sajjad Haider ◽  
Peter Schegner
Keyword(s):  
Electric Vehicles ◽  
Low Voltage ◽  
Learning Algorithm ◽  
Agent Based Modeling ◽  
Worst Case ◽  
Agent Based ◽  
Voltage Drops ◽  
Electricity Use ◽  
Test Grid ◽  
Ev Charging

This dataset includes multiple files related to optimization of electric vehicles to minimize overloading in low voltage grids by varying the locations available to charge the EVs. The data include lognormally sampled hourly sorted scenarios across 11 charging locations for a stochastics-based Monte Carlo simulation. This simulation runs through 2 million scenarios based on actual probabilities to incorporate most possible situations. It also includes samples from normally distributed household electricity use scenarios based on agent-based modeling. The article includes the test grid parameters for simulation, which were used to create a benchmark grid in DigSilent Powerfactory software, as well as intermediate outputs defining worst case scenarios when electric vehicles were charged and results from three different optimization approaches involving a reduction in voltage drops, cable overloading and total line losses. The outputs from the benchmark grid were used to train a machine learning algorithm, the weights and codes for which are also attached. This trained network acted as the grid for subsequent iterative optimization procedures. Outputs are presented as a comparison between pre-optimization and post-optimization scenarios. The above dataset and procedure were repeated while varying the number of EVs between 0 and 100 in increments of 20, data for which are also attached. The data article supports a related submission titled “Minimization of Overloading Caused by Electric Vehicle (EV) Charging in Low Voltage Networks”.

scholarly journals Heuristic Optimization of Overloading Due to Electric Vehicles in a Low Voltage Grid

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6069
Author(s):  
Sajjad Haider ◽  
Peter Schegner
Keyword(s):  
Electric Vehicles ◽  
Low Voltage ◽  
Optimization Methods ◽  
Monte Carlo Analysis ◽  
Heuristic Optimization ◽  
Optimization Approach ◽  
Worst Case ◽  
Voltage Drops ◽  
The Individual ◽  
Nodal Voltage

It is important to understand the effect of increasing electric vehicles (EV) penetrations on the existing electricity transmission infrastructure and to find ways to mitigate it. While, the easiest solution is to opt for equipment upgrades, the potential for reducing overloading, in terms of voltage drops, and line loading by way of optimization of the locations at which EVs can charge, is significant. To investigate this, a heuristic optimization approach is proposed to optimize EV charging locations within one feeder, while minimizing nodal voltage drops, cable loading and overall cable losses. The optimization approach is compared to typical unoptimized results of a monte-carlo analysis. The results show a reduction in peak line loading in a typical benchmark 0.4 kV by up to 10%. Further results show an increase in voltage available at different nodes by up to 7 V in the worst case and 1.5 V on average. Optimization for a reduction in transmission losses shows insignificant savings for subsequent simulation. These optimization methods may allow for the introduction of spatial pricing across multiple nodes within a low voltage network, to allow for an electricity price for EVs independent of temporal pricing models already in place, to reflect the individual impact of EVs charging at different nodes across the network.

scholarly journals Agent-Based Modeling Framework for Electric Vehicle Adoption Transition in Indonesia

2021 ◽  
Vol 12 (2) ◽  
pp. 73
Author(s):  
Dita Novizayanti ◽  
Eko Agus Prasetio ◽  
Manahan Siallagan ◽  
Sigit Puji Santosa
Keyword(s):  
Electric Vehicles ◽  
Data Analytics ◽  
Agent Based Modeling ◽  
Analysis Framework ◽  
Modeling Framework ◽  
Agent Based ◽  
Twitter Data ◽  
Decision Making Processes ◽  
Electric Vehicle Adoption ◽  
Technical Features

Currently, the adoption of electric vehicles (EV) draws much attention, as the environmental issue of reducing carbon emission is increasing worldwide. However, different countries face different challenges during this transition, particularly developing countries. This research aims to create a framework for the transition to EV in Indonesia through Agent-Based Modeling (ABM). The framework is used as the conceptual design for ABM to investigate the effect of agents’ decision-making processes at the microlevel into the number of adopted EV at the macrolevel. The cluster analysis is equipped to determine the agents’ characteristics based on the categories of the innovation adopters. There are 11 significant variables and four respondents’ clusters: innovators, early majority, late majority, and the uncategorized one. Moreover, Twitter data analytics are utilized to investigate the information engagement coefficient based on the agents’ location. The agents’ characteristics which emerged from this analysis framework will be used as the fundamental for investigating the effect of agents’ specific characteristics and their interaction through ABM for further research. It is expected that this framework will enable the discovery of which incentive scheme or critical technical features effectively increase the uptake of EV according to the agents’ specific characteristics.

An agent-based modeling approach to predict the evolution of market share of electric vehicles: A case study from Iceland

2012 ◽  
Vol 79 (9) ◽  
pp. 1638-1653 ◽  
Author(s):  
Ehsan Shafiei ◽  
Hedinn Thorkelsson ◽  
Eyjólfur Ingi Ásgeirsson ◽  
Brynhildur Davidsdottir ◽  
Marco Raberto ◽  
...  
Keyword(s):  
Market Share ◽  
Electric Vehicles ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Modeling Approach

Potential Power Quality Benefits of Electric Vehicles

2013 ◽  
Vol PP (99) ◽  
pp. 1-8 ◽  
Keyword(s):  
Real Time ◽  
Power Quality ◽  
Electric Vehicles ◽  
Single Phase ◽  
Low Voltage ◽  
Distribution Grid ◽  
Vehicle To Grid ◽  
Voltage Drops ◽  
Cloudy Weather ◽  
Real Time Digital Simulator

Electric vehicles (EVs) are likely to have a continued presence in the light-vehicle market in the next few decades. As a result, EV charging will put an extra burden on the distribution grid and adjustments need to be made in some cases. On the other hand, EVs have the potential to support the grid as well. This paper presents a single-phase bidirectional charger topology which pairs up a photovoltaic (PV) source with an EV charger resulting in production cost reduction. The presented topology is then used for vehicle-to-grid (V2G) services. The main focus of this paper is on power quality services which only slightly discharge the battery. Among these services, it studies the possibility of local reactive injection of EVs connected to the grid through a single-phase charger to compensate for voltage drops caused by motor startup or inductive loads. It also studies the possibility of active power injection of EVs for short time periods during PV transients in cloudy weather to keep the system stable. It also studies the potential of EVs to help during low voltage ride-through of the PV sources. The studies are performed using Simulink simulations and a real-time implementation in Real Time Digital Simulator (RTDS). The results demonstrate the effectiveness of power quality V2G services with small wear on the EV battery.

Agent-Based Modeling and Simulation for Systematic Operations of Shared Automated Electric Vehicles

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Fugen Yao ◽  
Xiqun (Michael) Chen ◽  
Panagiotis Angeloudis ◽  
Wenwen Zhang
Keyword(s):  
Modeling And Simulation ◽  
Electric Vehicles ◽  
Agent Based Modeling ◽  
Agent Based

Dynamic Co-simulation of agent-based controlled charging electric vehicles and their impacts on low-voltage networks

2013 ◽  
Author(s):  
Daniel Burnier de Castro ◽  
Stefan Ubermasser ◽  
Sawsan Henein ◽  
Matthias Stifter ◽  
Johannes Stockl ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Low Voltage ◽  
Agent Based

scholarly journals A Fuzzy Energy Management Strategy for the Coordination of Electric Vehicle Charging in Low Voltage Distribution Grids

Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3709 ◽  
Author(s):  
Vasileios Boglou ◽  
Christos-Spyridon Karavas ◽  
Konstantinos Arvanitis ◽  
Athanasios Karlis
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Management Strategy ◽  
Low Voltage ◽  
State Of Charge ◽  
Voltage Distribution ◽  
Energy Management Strategy ◽  
Fuzzy Energy ◽  
Ev Charging

Electric vehicles (EVs) have become widespread during the last decade because of the distinct advantages they offer compared to the conventional ones. However, the increased penetration of EVs in the global transportation market has led increased electricity demands, which is expected to affect the operation of energy distribution systems. In the present paper, a demonstration about the effects of uncontrolled EVs charging in a case study low voltage (LV) network is demonstrated and a fuzzy energy management strategy for the coordination of EV charging in LV networks is presented, by including the distance of the EVs from the transformers in the fuzzy management systems for the first time. The Institute of Electrical and Electronics Engineers (IEEE) European Test Feeder is used as a case study low voltage distribution grid. In particular, the developed system configuration takes into consideration the architecture of the grid, the ampacities of the lines and the voltages at the system’s buses. Moreover, electric vehicles are considered as agent-based models, which are characterized by the model of each EV, the state-of-charge of their batteries and the charging power. In particular, an investigation into the effects of uncontrolled charging is performed, in which two approaches are examined. The first approach investigates the maximum number of chargeable EVs in the case study network and how it is influenced by the grid’s household loads. The second approach examines the number of network undervoltages and lines ampacity violations in a set of simulation scenarios. The results of the first approach show that the distance of the EVs from the networks substation affects the maximum number of chargeable EVs in a significant manner. Based on the observed results of the two approaches, a fuzzy management system is designed for the coordination of EV changing, which takes into account the distance from the EV charging points to the feeder substation, the state-of-charge of the EVs’ batteries and the EVs’ charging delay time.

scholarly journals Numerical Analysis of the Cooling Performance in a 7.2 kW Integrated Bidirectional OBC/LDC Module

2019 ◽  
Vol 10 (1) ◽  
pp. 270
Author(s):  
Jung-Hun Noh ◽  
Seong-il Song ◽  
Deog-Jae Hur
Keyword(s):  
Numerical Analysis ◽  
Power Loss ◽  
Low Voltage ◽  
Flow Characteristics ◽  
Operating Mode ◽  
Internal Cooling ◽  
Battery Charger ◽  
Worst Case ◽  
Operating Modes ◽  
Ev Charging

To satisfy increasing demands for ecofriendly vehicles, researchers are now studying electric vehicle (EV)-related technologies. In particular, integrated bidirectional onboard battery charger (OBC)/low-voltage DC–DC converter (LDC) modules are being researched to improve the efficiency of onboard chargers for EV charging applications. In this study, a numerical analysis method is proposed that considers the power loss and heat flow characteristics in the design of a 7.2 kW integrated bidirectional OBC/LDC module. The developed module supports four operating modes depending on the service situation: OBC and LDC single operation, OBC/LDC simultaneous operation, and LDC operation. The mode is selected based on the power system flow. The characteristics of the circuit were analyzed in each of the four modes to compute the heat loss from the major heating elements. The results of a numerical analysis of the internal cooling characteristics showed that the internal temperature was higher in the OBC single operating mode than in the OBC and LDC simultaneous operating mode in which the power loss was the highest. The results emphasize the importance of ensuring that cooling designs consider the characteristics of various modes as well as the worst-case power loss.

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