Impact of Residential and Public Charging Stations of Electric Vehicles on Distribution System by Stochastic Simulation

2015 ◽  
Vol 1092-1093 ◽  
pp. 375-380
Author(s):  
Suthida Ruayariyasub ◽  
Sompon Sirisumrannukul ◽  
Suksan Wangsatitwong
Keyword(s):  
Monte Carlo ◽  
Electric Vehicles ◽  
Distribution System ◽  
Stochastic Approach ◽  
Local Distribution ◽  
Battery Charging ◽  
Proposed Model ◽  
Charging Stations ◽  
The Impact

This paper investigates the impact of electric vehicles battery charging on the distribution system load if electric vehicles (EVs) are widespread used on roads. Stochastic approach based on a Monte Carlo method is developed in this study to simulate EVs charging load in two cases: 1) normal charge service at home, and 2) quick charge service at public charging stations. To demonstrate the model, a 22-kV distribution system of Pattaya City operated by Provincial Electricity Authority of Thailand (PEA) is employed in the case study. The results indicate the capability of the proposed model to exhibit the impact of EVs charging load on the local distribution system.

scholarly journals Demand contracting strategy for charging stations based on load forecasting

2020 ◽  
Vol 194 ◽  
pp. 03024
Author(s):  
Fang Chen ◽  
Liu Zeyu ◽  
Wang Haojing ◽  
Zhao Yi ◽  
Shi Shanshan ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Electric Vehicles ◽  
Analytic Solution ◽  
Load Forecasting ◽  
Stochastic Parameter ◽  
Forecasting Method ◽  
Charging Stations ◽  
High Possibility ◽  
Demand Charge

Since the stochasticity of the charging of electric vehicles (EVs) may bring impact to the grid, there is a high possibility that the demand charge will be applied to charging stations. Therefore, a load-forecasting-based demand contracting strategy is proposed for charge stations in this paper. A stochastic optimization model is established by regarding the maximal demand as a stochastic parameter, and the object of the model is to minimize the expectation of demand charge, and the analytic solution is derived. To obtain the distribution of actual maximal demand, a Monte-Carlo-based charge load forecasting method is proposed. It gives the distribution of the daily maximal demand, based on which the distribution of monthly maximal demand is also derived. The case study illustrates the feasibility and the validity of the proposed strategy.

scholarly journals Charging Station and Power Network Planning for Integrated Electric Vehicles (EVs)

Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2595 ◽  
Author(s):  
Guozhong Liu ◽  
Li Kang ◽  
Zeyu Luan ◽  
Jing Qiu ◽  
Fenglei Zheng
Keyword(s):  
Case Studies ◽  
Traffic Flow ◽  
Electric Vehicles ◽  
Distribution System ◽  
Large Scale ◽  
Distribution Networks ◽  
Fuzzy Membership Function ◽  
Multi Objective ◽  
Charging Stations ◽  
The Impact

The optimal location and size of charging stations are important considerations in relation to the large-scale application of electric vehicles (EVs). In this context, considering that charging stations are both traffic service facilities and common electric facilities, a multi-objective model is built, with the objectives of maximizing the captured traffic flow in traffic networks and minimizing the power loss in distribution networks. There are two kinds of charging stations that are considered in this paper, and the planning of EV charge stations and distribution networks is jointly modelled. The formulated multi-objective optimization problem is handled by a fuzzy membership function. The genetic algorithm (GA) is used to solve the objective function. In case studies, a 33-node distribution system and a 25-node traffic network are used to verify the effectiveness of the proposed model. The location and capacity of two kinds of charging stations are designed in the case studies, after which the impact of the battery on the captured traffic flow is analyzed as well.

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 Electric Vehicles in Jordan: Challenges and Limitations

2021 ◽  
Vol 13 (6) ◽  
pp. 3199
Author(s):  
Laith Shalalfeh ◽  
Ashraf AlShalalfeh ◽  
Khaled Alkaradsheh ◽  
Mahmoud Alhamarneh ◽  
Ahmad Bashaireh
Keyword(s):  
Electric Vehicles ◽  
Distribution System ◽  
Distribution Systems ◽  
Environmental Benefits ◽  
System Stability ◽  
Loading Conditions ◽  
Stability Margins ◽  
High Penetration ◽  
Node Distribution ◽  
The Impact

An increasing number of electric vehicles (EVs) are replacing gasoline vehicles in the automobile market due to the economic and environmental benefits. The high penetration of EVs is one of the main challenges in the future smart grid. As a result of EV charging, an excessive overloading is expected in different elements of the power system, especially at the distribution level. In this paper, we evaluate the impact of EVs on the distribution system under three loading conditions (light, intermediate, and full). For each case, we estimate the maximum number of EVs that can be charged simultaneously before reaching different system limitations, including the undervoltage, overcurrent, and transformer capacity limit. Finally, we use the 19-node distribution system to study these limitations under different loading conditions. The 19-node system is one of the typical distribution systems in Jordan. Our work estimates the upper limit of the possible EV penetration before reaching the system stability margins.

scholarly journals Optimal Pricing Strategy of Electric Vehicle Charging Station for Promoting Green Behavior Based on Time and Space Dimensions

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Xiaomin Xu ◽  
Dongxiao Niu ◽  
Yan Li ◽  
Lijie Sun
Keyword(s):  
Electric Vehicles ◽  
Optimization Problems ◽  
Power Grid ◽  
Economic Benefits ◽  
Pricing Strategy ◽  
Optimal Pricing ◽  
Electricity Pricing ◽  
Optimal Pricing Strategy ◽  
Charging Stations ◽  
The Impact

Considering that the charging behaviors of users of electric vehicles (EVs) (including charging time and charging location) are random and uncertain and that the disorderly charging of EVs brings new challenges to the power grid, this paper proposes an optimal electricity pricing strategy for EVs based on region division and time division. Firstly, by comparing the number of EVs and charging stations in different districts of a city, the demand ratio of charging stations per unit is calculated. Secondly, according to the demand price function and the principle of profit maximization, the charging price between different districts of a city is optimized to guide users to charge in districts with more abundant charging stations. Then, based on the results of the zonal pricing strategy, the time-of-use (TOU) pricing strategy in different districts is discussed. In the TOU pricing model, consumer satisfaction, the profit of power grid enterprises, and the load variance of the power grid are considered comprehensively. Taking the optimization of the comprehensive index as the objective function, the TOU pricing optimization model of EVs is constructed. Finally, the nondominated sorting genetic algorithm (NSGA-II) is introduced to solve the above optimization problems. The specific data of EVs in a municipality directly under the Central Government are taken as examples for this analysis. The empirical results demonstrate that the peak-to-valley ratio of a certain day in the city is reduced from 56.8% to 43% by using the optimal pricing strategy, which further smooth the load curve and alleviates the impact of load fluctuation. To a certain extent, the problem caused by the uneven distribution of electric vehicles and charging stations has been optimized. An orderly and reasonable electricity pricing strategy can guide users to adjust charging habits, to ensure grid security, and to ensure the economic benefits of all parties.

scholarly journals Joint Optimal Policy for Subsidy on Electric Vehicles and Infrastructure Construction in Highway Network

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2479 ◽  
Author(s):  
Yue Wang ◽  
Zhong Liu ◽  
Jianmai Shi ◽  
Guohua Wu ◽  
Rui Wang
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Optimal Policy ◽  
Practical Case ◽  
Battery Electric Vehicle ◽  
Battery Electric Vehicles ◽  
Endurance Range ◽  
Highway Network ◽  
Charging Stations ◽  
The Impact

The promotion of the battery electric vehicle has become a worldwide problem for governments due to its short endurance range and slow charging rate. Besides an appropriate network of charging facilities, a subsidy has proved to be an effective way to increase the market share of battery electric vehicles. In this paper, we investigate the joint optimal policy for a subsidy on electric vehicles and infrastructure construction in a highway network, where the impact of siting and sizing of fast charging stations and the impact of subsidy on the potential electric vehicle flows is considered. A new specified local search (LS)-based algorithm is developed to maximize the overall number of available battery electric vehicles in the network, which can get provide better solutions in most situations when compared with existed algorithms. Moreover, we firstly combined the existing algorithms to establish a multi-stage optimization method, which can obtain better solutions than all existed algorithms. A practical case from the highway network in Hunan, China, is studied to analyze the factors that impact the choice of subsidy and the deployment of charging stations. The results prove that the joint policy for subsidy and infrastructure construction can be effectively improved with the optimization model and the algorithms we developed. The managerial analysis indicates that the improvement on the capacity of charging facility can increase the proportion of construction fees in the total budget, while the improvement in the endurance range of battery electric vehicles is more efficient in expanding battery electric vehicle adoption in the highway network. A more detailed formulation of the battery electric vehicle flow demand and equilibrium situation will be studied in the future.

An Integrated Methodology for Evaluation of Electric Vehicles Under Sustainable Automotive Environment

2019 ◽  
pp. 41-62 ◽  
Author(s):  
Tapas Kumar Biswas ◽  
Željko Stević ◽  
Prasenjit Chatterjee ◽  
Morteza Yazdani
Keyword(s):  
Electric Vehicles ◽  
Sustainability Assessment ◽  
Model Performance ◽  
Compromise Solution ◽  
Holistic Model ◽  
Proposed Model ◽  
Criteria Importance ◽  
Assessment Problems ◽  
Selection Of

In this chapter, a holistic model based on a newly developed combined compromise solution (CoCoSo) and criteria importance through intercriteria correlation (CRITIC) method for selection of battery-operated electric vehicles (BEVs) has been propounded. A sensitivity analysis has been performed to verify the robustness of the proposed model. Performance of the proposed model has also been compared with some of the popular MCDM methods. It is observed that the model has the competency of precisely ranking the BEV alternatives for the considered case study and can be applied to other sustainability assessment problems.

scholarly journals Coordinated Dispatch of Integrated Energy Systems Considering the Differences of Multiple Functional Areas

2019 ◽  
Vol 9 (10) ◽  
pp. 2103 ◽  
Author(s):  
Liusong Li ◽  
Weichao Jin ◽  
Meiyan Shen ◽  
Li Yang ◽  
Fei Chen ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Electric Vehicles ◽  
Transmission Lines ◽  
Distribution System ◽  
Energy Systems ◽  
Actual Distribution ◽  
Integrated Energy Systems ◽  
Transmission Distance ◽  
Proposed Model ◽  
Functional Areas

A large amount of wind turbine power and photovoltaic power is abandoned in many areas with abundant renewable energy due to thermal-electric coupling, inadequate local consumption capacity, and limited capacity of transmission lines, etc. To solve the above problems, a coordinated dispatching method for integrated energy systems is proposed in this paper. Firstly, the spatiotemporal characteristics of diversified loads in multiple functional areas are introduced, including the inertia and elasticity of heating/cooling loads, the spatiotemporal distribution of electric vehicles, and the optimum transmission distance of diversified loads, etc. Secondly, a coordinated dispatching model of integrated energy systems is proposed, which considers the differences of multiple functional areas and various forms of energy systems. Finally, an actual distribution system in Jianshan District, Haining, Zhejiang Province of China is investigated for demonstrating the effectiveness of the proposed model. The results illustrate that the proposed model could effectively improve the consumption rate of renewable energy and reduce the volatility of renewable energy by considering the coordination of electric vehicles, tie lines, and heating/cooling systems in multiple functional areas.

Assessing design process in engineering consultancy firms using lean principles

SIMULATION ◽  
2012 ◽  
Vol 88 (12) ◽  
pp. 1522-1536 ◽  
Author(s):  
M Marzouk ◽  
I Bakry ◽  
M El-Said
Keyword(s):  
Design Process ◽  
Comprehensive Model ◽  
Output Analysis ◽  
Lean Principles ◽  
Proposed Model ◽  
Client Request ◽  
Using Data ◽  
Consultancy Firm ◽  
The Impact

The aim of this research is to provide a tool for assessing the impact of applying lean principles to the design process at construction consultancy firms. Through several interviews, a comprehensive model was built to simulate the design process, using data from a leading consultancy firm in Egypt. The model contains the main processes and activities that form different phases of the design process and depicts the interconnectivity of processes and activities needed to create a complete design package upon client request. The research describes how the five main lean principles are integrated in the model. A case study is considered to demonstrate the effect of using the proposed model on the design process and to illustrate how the design process performs differently when lean principles are introduced. Case study output analysis reveals 40% improvement in the lean process performance measured in terms of activity utilization rates.

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