Electric power resource provisioning for large scale public EV charging facilities

2013 ◽  
Author(s):  
I. Safak Bayram ◽  
George Michailidis ◽  
Michael Devetsikiotis
Keyword(s):  
Electric Power ◽  
Large Scale ◽  
Resource Provisioning ◽  
Power Resource ◽  
Ev Charging

scholarly journals Uncontrolled Electric Vehicle Charging Impacts on Distribution Electric Power Systems with Primarily Residential, Commercial or Industrial Loads

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1688 ◽  
Author(s):  
C. Birk Jones ◽  
Matthew Lave ◽  
William Vining ◽  
Brooke Marshall Garcia
Keyword(s):  
Power Systems ◽  
Electric Power ◽  
Low Voltage ◽  
Peak Load ◽  
Electric Power Systems ◽  
Primary System ◽  
Maximum Increase ◽  
Actual Distribution ◽  
The Impact ◽  
Ev Charging

An increase in Electric Vehicles (EV) will result in higher demands on the distribution electric power systems (EPS) which may result in thermal line overloading and low voltage violations. To understand the impact, this work simulates two EV charging scenarios (home- and work-dominant) under potential 2030 EV adoption levels on 10 actual distribution feeders that support residential, commercial, and industrial loads. The simulations include actual driving patterns of existing (non-EV) vehicles taken from global positioning system (GPS) data. The GPS driving behaviors, which explain the spatial and temporal EV charging demands, provide information on each vehicles travel distance, dwell locations, and dwell durations. Then, the EPS simulations incorporate the EV charging demands to calculate the power flow across the feeder. Simulation results show that voltage impacts are modest (less than 0.01 p.u.), likely due to robust feeder designs and the models only represent the high-voltage (“primary”) system components. Line loading impacts are more noticeable, with a maximum increase of about 15%. Additionally, the feeder peak load times experience a slight shift for residential and mixed feeders (≈1 h), not at all for the industrial, and 8 h for the commercial feeder.

scholarly journals A Novel Methodology for Adaptive Coordination of Multiple Controllers in Electrical Grids

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1474
Author(s):  
Ruben Tapia-Olvera ◽  
Francisco Beltran-Carbajal ◽  
Antonio Valderrabano-Gonzalez ◽  
Omar Aguilar-Mejia
Keyword(s):  
Power Systems ◽  
Power System ◽  
Electric Power ◽  
Large Scale ◽  
Short Circuit ◽  
Dynamic Performance ◽  
Low Frequency ◽  
Electric Power System ◽  
Design Stage ◽  
Positive Interaction

This proposal is aimed to overcome the problem that arises when diverse regulation devices and controlling strategies are involved in electric power systems regulation design. When new devices are included in electric power system after the topology and regulation goals were defined, a new design stage is generally needed to obtain the desired outputs. Moreover, if the initial design is based on a linearized model around an equilibrium point, the new conditions might degrade the whole performance of the system. Our proposal demonstrates that the power system performance can be guaranteed with one design stage when an adequate adaptive scheme is updating some critic controllers’ gains. For large-scale power systems, this feature is illustrated with the use of time domain simulations, showing the dynamic behavior of the significant variables. The transient response is enhanced in terms of maximum overshoot and settling time. This is demonstrated using the deviation between the behavior of some important variables with StatCom, but without or with PSS. A B-Spline neural networks algorithm is used to define the best controllers’ gains to efficiently attenuate low frequency oscillations when a short circuit event is presented. This strategy avoids the parameters and power system model dependency; only a dataset of typical variable measurements is required to achieve the expected behavior. The inclusion of PSS and StatCom with positive interaction, enhances the dynamic performance of the system while illustrating the ability of the strategy in adding different controllers in only one design stage.

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 Beyond HEP: Photon and accelerator science computing infrastructure at DESY

2020 ◽  
Vol 245 ◽  
pp. 07036
Author(s):  
Christoph Beyer ◽  
Stefan Bujack ◽  
Stefan Dietrich ◽  
Thomas Finnern ◽  
Martin Flemming ◽  
...  
Keyword(s):  
High Performance ◽  
Large Scale ◽  
High Energy Physics ◽  
High Energy ◽  
Resource Provisioning ◽  
Small Scale ◽  
Online Processing ◽  
Offline Processing ◽  
National Analysis ◽  
Energy Physics

DESY is one of the largest accelerator laboratories in Europe. It develops and operates state of the art accelerators for fundamental science in the areas of high energy physics, photon science and accelerator development. While for decades high energy physics (HEP) has been the most prominent user of the DESY compute, storage and network infrastructure, various scientific areas as science with photons and accelerator development have caught up and are now dominating the demands on the DESY infrastructure resources, with significant consequences for the IT resource provisioning. In this contribution, we will present an overview of the computational, storage and network resources covering the various physics communities on site. Ranging from high-throughput computing (HTC) batch-like offline processing in the Grid and the interactive user analyses resources in the National Analysis Factory (NAF) for the HEP community, to the computing needs of accelerator development or of photon sciences such as PETRA III or the European XFEL. Since DESY is involved in these experiments and their data taking, their requirements include fast low-latency online processing for data taking and calibration as well as offline processing, thus high-performance computing (HPC) workloads, that are run on the dedicated Maxwell HPC cluster. As all communities face significant challenges due to changing environments and increasing data rates in the following years, we will discuss how this will reflect in necessary changes to the computing and storage infrastructures. We will present DESY compute cloud and container orchestration plans as a basis for infrastructure and platform services. We will show examples of Jupyter notebooks for small scale interactive analysis, as well as its integration into large scale resources such as batch systems or Spark clusters. To overcome the fragmentation of the various resources for all scientific communities at DESY, we explore how to integrate them into a seamless user experience in an Interdisciplinary Data Analysis Facility.

Load Forecasting of Charging and Swapping in Large-Scale Electric Vehicle

2014 ◽  
Vol 568-570 ◽  
pp. 1969-1977 ◽  
Author(s):  
Jian Cheng Ye ◽  
Yu Ling Li ◽  
Dong Liang Zhang ◽  
Xiang Jing Zhu ◽  
Jin Da Zhu
Keyword(s):  
Electric Vehicle ◽  
Large Scale ◽  
Access Network ◽  
Calculation Model ◽  
Simulation Algorithm ◽  
Charging Time ◽  
Load Calculation ◽  
Other Information ◽  
Charging Mode ◽  
Ev Charging

This article combs the charging mode of electric vehicle,and analyzes different charging ways for buses,taxis and sedans,thereby drawing their appropriate charging time and characteristics of the interaction with grid. The paper establishes the load calculation model for the charging and swapping in Evs respectively. The load calculation model divides one day into 1440 minutes, and use the Monte Carlo simulation algorithm to extract the initial SOC, the initial charging time and other information for load calculation and analyze the EV charging load. The results show that the charging load of electric vehicle has obvious difference between peak and vally,and provide reference for the management and policy oriented electric vhicle access network.

scholarly journals Stochastic Bilevel Program for Optimal Coordinated Energy Trading of an EV Aggregator

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3813 ◽  
Author(s):  
Yelena Vardanyan ◽  
Henrik Madsen
Keyword(s):  
Large Scale ◽  
Stackelberg Game ◽  
Strong Duality ◽  
Bilevel Optimization ◽  
Transport Sector ◽  
Global Optimality ◽  
Complementary Slackness ◽  
Bilevel Program ◽  
Ev Charging ◽  
Stochastic Bilevel Program

Gradually replacing fossil-fueled vehicles in the transport sector with Electric Vehicles (EVs) may help ensure a sustainable future. With regard to the charging electric load of EVs, optimal scheduling of EV batteries, controlled by an aggregating agent, may provide flexibility and increase system efficiency. This work proposes a stochastic bilevel optimization problem based on the Stackelberg game to create price incentives that generate optimal trading plans for an EV aggregator in day-ahead, intra-day and real-time markets. The upper level represents the profit maximizer EV aggregator who participates in three sequential markets and is called a Stackelberg leader, while the second level represents the EV owner who aims at minimizing the EV charging cost, and who is called a Stackelberg follower. This formulation determines endogenously the profit-maximizing price levels constraint by cost-minimizing EV charging plans. To solve the proposed stochastic bilevel program, the second level is replaced by its optimality conditions. The strong duality theorem is deployed to substitute the complementary slackness condition. The final model is a stochastic convex problem which can be solved efficiently to determine the global optimality. Illustrative results are reported based on a small case with two vehicles. The numerical results rely on applying the proposed methodology to a large scale fleet of 100, 500, 1000 vehicles, which provides insights into the computational tractability of the current formulation.

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