scholarly journals Orderly Discharging Strategy for Electric Vehicles at Workplace Based on Time-of-Use Price

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Lixing Chen ◽  
Hong Zhang
Keyword(s):  
Electric Vehicles ◽  
Power Supply System ◽  
Optimal Solution ◽  
Supply System ◽  
Penalty Function Methods ◽  
Artificial Fish Swarm Algorithm ◽  
Charging Station ◽  
Scheduling Model ◽  
Artificial Fish Swarm ◽  
Simulation Results

According to the parking features of electric vehicles (EVs) and load of production unit, a power supply system including EVs charging station was established, and an orderly discharging strategy for EVs was proposed as well to reduce the basic tariff of producer and improve the total benefits of EV discharging. Based on the target of maximizing the annual income of producer, considering the total benefits of EV discharging, the electric vehicle aggregator (EVA) and time-of-use (TOU) price were introduced to establish the optimization scheduling model of EVs discharging. Furthermore, an improved artificial fish swarm algorithm (IAFSA) combined with the penalty function methods was applied to solve the model. It can be shown from the simulation results that the optimal solution obtained by IAFSA is regarded as the orderly discharging strategy for EVs, which could reduce the basic tariff of producer and improve the total benefits of EV discharging.

scholarly journals Optimal Decision-Making to Charge Electric Vehicles in Heterogeneous Networks: Stackelberg Game Approach

Energies ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 325 ◽  
Author(s):  
Shijun Chen ◽  
Huwei Chen ◽  
Shanhe Jiang
Keyword(s):  
Electric Vehicles ◽  
Heterogeneous Networks ◽  
Demand Uncertainty ◽  
Stackelberg Game ◽  
Optimal Solution ◽  
Stackelberg Equilibrium ◽  
Optimal Decision ◽  
Charging Station ◽  
Simulation Results ◽  
Grid Operators

Electric vehicles (EVs) are designed to improve the efficiency of energy and prevent the environment from being polluted, when they are widely and reasonably used in the transport system. However, due to the feature of EV’s batteries, the charging problem plays an important role in the application of EVs. Fortunately, with the help of advanced technologies, charging stations powered by smart grid operators (SGOs) can easily and conveniently solve the problems and supply charging service to EV users. In this paper, we consider that EVs will be charged by charging station operators (CSOs) in heterogeneous networks (Hetnet), through which they can exchange the information with each other. Considering the trading relationship among EV users, CSOs, and SGOs, we design their own utility functions in Hetnet, where the demand uncertainty is taken into account. In order to maximize the profits, we formulate this charging problem as a four-stage Stackelberg game, through which the optimal strategy is studied and analyzed. In the Stackelberg game model, we theoretically prove and discuss the existence and uniqueness of the Stackelberg equilibrium (SE). Using the proposed iterative algorithm, the optimal solution can be obtained in the optimization problem. The performance of the strategy is shown in the simulation results. It is shown that the simulation results confirm the efficiency of the model in Hetnet.

scholarly journals Technical and Economic Analysis of One-Stop Charging Stations for Battery and Fuel Cell EV with Renewable Energy Sources

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2855 ◽  
Author(s):  
Saumya Bansal ◽  
Yi Zong ◽  
Shi You ◽  
Lucian Mihet-Popa ◽  
Jinsheng Xiao
Keyword(s):  
Electric Vehicles ◽  
Fossil Fuels ◽  
Renewable Energy Sources ◽  
Optimal Solution ◽  
Production Volume ◽  
Electrical Load ◽  
Charging Station ◽  
Technical And Economic Analysis ◽  
One Stop ◽  
The One

Currently, most of the vehicles make use of fossil fuels for operations, resulting in one of the largest sources of carbon dioxide emissions. The need to cut our dependency on these fossil fuels has led to an increased use of renewable energy sources (RESs) for mobility purposes. A technical and economic analysis of a one-stop charging station for battery electric vehicles (BEV) and fuel cell electric vehicles (FCEV) is investigated in this paper. The hybrid optimization model for electric renewables (HOMER) software and the heavy-duty refueling station analysis model (HDRSAM) are used to conduct the case study for a one-stop charging station at Technical University of Denmark (DTU)-Risø campus. Using HOMER, a total of 42 charging station scenarios are analyzed by considering two systems (a grid-connected system and an off-grid connected system). For each system three different charging station designs (design A-hydrogen load; design B-an electrical load, and design C-an integrated system consisting of both hydrogen and electrical load) are set up for analysis. Furthermore, seven potential wind turbines with different capacity are selected from HOMER database for each system. Using HDRSAM, a total 18 scenarios are analyzed with variation in hydrogen delivery option, production volume, hydrogen dispensing option and hydrogen dispensing option. The optimal solution from HOMER for a lifespan of twenty-five years is integrated into design C with the grid-connected system whose cost was $986,065. For HDRSAM, the optimal solution design consists of tube trailer as hydrogen delivery with cascade dispensing option at 350 bar together with high production volume and the cost of the system was $452,148. The results from the two simulation tools are integrated and the overall cost of the one-stop charging station is achieved which was $2,833,465. The analysis demonstrated that the one-stop charging station with a grid connection is able to fulfil the charging demand cost-effectively and environmentally friendly for an integrated energy system with RESs in the investigated locations.

Artificial Fish Swarm Algorithm Based on Fast Image Matching

2011 ◽  
Vol 271-273 ◽  
pp. 297-302
Author(s):  
Miao Ma ◽  
Jiao He ◽  
Min Guo
Keyword(s):  
Image Matching ◽  
Feature Matching ◽  
Fitness Function ◽  
Optimal Solution ◽  
Fast Method ◽  
Artificial Fish Swarm Algorithm ◽  
Template Image ◽  
Artificial Fish Swarm ◽  
Swarm Algorithm ◽  
Exclusive Or

Due to the large amount of calculation and high time-consuming in traditional grayscale matching, this paper combines artificial fish algorithm of swarm intelligence with edge detection and the operation of bitwise exclusive or, and presents a fast method on feature matching. The method regards the problem of image matching as a process of searching the optimal solution. In order to provide artificial fish swarm algorithm with an appropriate fitness function, the operation of bitwise exclusive or and addition is employed to deal with the edge information extracted from the template image and the searching image. Then the best matching position is gradually approaching by swarming, following and other behaviors of artificial fish. Experimental results show that the proposed method not only significantly shortens the matching time and guarantees the matching accuracy, but also is robust to noise disturbance.

Optimal Quick Charging Station Placement for Electric Vehicles

2015 ◽  
Vol 785 ◽  
pp. 697-701 ◽  
Author(s):  
Md. Mainul Islam ◽  
Hussein Shareef ◽  
Azah Mohamed
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Optimal Solution ◽  
Optimization Method ◽  
Road Transport ◽  
Optimal Placement ◽  
Charging Station ◽  
Weighted Sum Method ◽  
Driving Range ◽  
Integrated Cost

Environmental concerns, dependency on imported petroleum and lower cost alternative to gasoline always motivated policymakers worldwide to introduce electric vehicles in road transport system as a solution of those problems. The key issue in this system is recharging the electric vehicle batteries before they are exhausted. Thus, the charging station should be carefully located to make sure the vehicle users can access the charging station within its driving range. This paper therefore proposes a multi-objective optimization method for optimal placement of quick charging station. It intends to minimize the integrated cost of grid energy loss and travelling of vehicle to quick charging station. Due to contrary objectives, weighted sum method is assigned to generate reference Pareto optimal front and optimized the overture by genetic algorithm. The results show that the proposed method can find the optimal solution of quick charging station placement that can benefit electric vehicle users and power grid.

The Parameters Matching and Simulation of Pure Electric Vehicle Composite Power Supply Based on CRUISE

2014 ◽  
Vol 602-605 ◽  
pp. 2836-2839 ◽  
Author(s):  
Mei Lan Zhou ◽  
Lin Wei ◽  
Jia Bin Wen
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Power Supply ◽  
Lithium Battery ◽  
Power Supply System ◽  
Supply System ◽  
Power Performance ◽  
System Parameters ◽  
The World ◽  
Ultra Capacitor

Pure electric vehicles develop rapidly all over the world. According to building the model of pure electric vehicle in the CRUISE software, first the power supply system parameters are designed and simulated, and then the power performance and feasibility of the model are verified. The design of CPS (composite power supply) which combined UC (ultra capacitor) with Li-B (lithium battery) can extend the life of the Li-B, and protect the Li-B in some way. Under the NEDC operating condition, the simulations of the SPS (single power supply) and the CPS are taken. The result shows that the variation of the Li-B SOC decrease by 8%, compared the CPS system with the SPS system, the comprehensive energy consumption economy is 6.25%.

scholarly journals Evaluation of Electric Vehicle Charging Station Network Planning via a Co-Evolution Approach

Energies ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 25 ◽  
Author(s):  
Hassan S. Hayajneh ◽  
Xuewei Zhang
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Optimization Problems ◽  
Optimal Solution ◽  
Optimal Planning ◽  
Modeling Framework ◽  
Charging Infrastructure ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Vehicle Charging

The optimal planning of electric vehicle charging infrastructure has attracted extensive research interest in recent years. Most of the optimization problems were formulated by assuming that the configurations will be fixed at the optimal solution while overlooking the fact that the charging stations and the electric vehicles are “evolving” over time and have mutual impacts. On the other hand, little attention has been paid to evaluate the performance of the solutions in such a dynamic environment. Motivated by these gaps, this work develops a simulation model that captures the interactions between charging station configurations and electric vehicle population (and the preference of electric vehicles when choosing charging station). This modeling framework is then implemented to evaluate the performance of planned charging infrastructure in providing services to electric vehicles. Two indicators are calculated, i.e., usage rate and rejection rate. The former measures the “waste” due to abundant facilities installed; the latter measures the inadequacy of planned facilities, especially when the electric vehicle population is larger. The simulation results presented in this work validate the model and show the potential of the model not only to evaluate designs but also to be used for optimal planning in subsequent works.

scholarly journals A Hybrid Method for Image Segmentation Based on Artificial Fish Swarm Algorithm and Fuzzyc-Means Clustering

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Li Ma ◽  
Yang Li ◽  
Suohai Fan ◽  
Runzhu Fan
Keyword(s):  
Image Segmentation ◽  
Medical Image ◽  
Clustering Algorithms ◽  
Optimal Solution ◽  
Medical Image Segmentation ◽  
Superior Result ◽  
Artificial Fish Swarm Algorithm ◽  
Artificial Fish Swarm ◽  
Fcm Clustering ◽  
Swarm Algorithm

Image segmentation plays an important role in medical image processing. Fuzzyc-means (FCM) clustering is one of the popular clustering algorithms for medical image segmentation. However, FCM has the problems of depending on initial clustering centers, falling into local optimal solution easily, and sensitivity to noise disturbance. To solve these problems, this paper proposes a hybrid artificial fish swarm algorithm (HAFSA). The proposed algorithm combines artificial fish swarm algorithm (AFSA) with FCM whose advantages of global optimization searching and parallel computing ability of AFSA are utilized to find a superior result. Meanwhile, Metropolis criterion and noise reduction mechanism are introduced to AFSA for enhancing the convergence rate and antinoise ability. The artificial grid graph and Magnetic Resonance Imaging (MRI) are used in the experiments, and the experimental results show that the proposed algorithm has stronger antinoise ability and higher precision. A number of evaluation indicators also demonstrate that the effect of HAFSA is more excellent than FCM and suppressed FCM (SFCM).

scholarly journals Research on Power Supply Scheme of Electrical Submersible Pump Fed by Inverter Based on Long Cable

2019 ◽  
Vol 260 ◽  
pp. 02007
Author(s):  
Yonghong Deng ◽  
Zhishan Liang
Keyword(s):  
Power Supply ◽  
Control Algorithm ◽  
Power Supply System ◽  
Functional Relationship ◽  
Frequency Converter ◽  
Supply System ◽  
Submersible Pump ◽  
Smart Power ◽  
Electrical Submersible Pump ◽  
Simulation Results

Electrical submersible pump (ESP) require remote operation of inverter via a long cable. The conventional control algorithm of inverter does not operate effectively. In this paper, a new power supply scheme is proposed, namely: Inverter - Motor - Generator - Transformer – Long Cable - ESP power supply program, referred to as IMGEESP power supply system. Based on the analysis of the IMGEESP, the model of the long cable was established, the functional relationship between inverter and smart power of the IMGEESP was deduced, so that the voltage model is constructed. The frequency converter and the intelligent power supply of IMGEESP are coordinated and controlled according to the speed command of the ESP and the cable length. Simulation results verifies the correctness and effectiveness of the proposed IMGEESP.

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