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 Optimal Game-Based Energy Management with Renewable Energy for Secure Electric Vehicles Charging in Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Huwei Chen ◽  
Shijun Chen ◽  
Shanhe Jiang
Keyword(s):  
Renewable Energy ◽  
Internet Of Things ◽  
Electric Vehicles ◽  
Energy Demand ◽  
Stackelberg Game ◽  
Scheduling Algorithm ◽  
Optimal Solution ◽  
Stackelberg Equilibrium ◽  
Charging System ◽  
Game Theoretic

The integration of smart grid and Internet of Things (IoT) has been facilitated with the proliferation of electric vehicles (EVs). However, due to EVs’ random mobility and different interests of energy demand, there exists a significant challenge to optimally schedule energy supply in IoT. In this paper, we propose a secure game theoretic scheme for charging EVs supplied by mobile charging stations (MCSs) in IoT, considering the dynamic renewable energy source. Firstly, the charging system composed of MCSs is developed to implement the charging service. Secondly, when the secure charging scheme of EV users is designed, the utility function of each entity in the charging system is formulated to express the trading relationship between EV users and MCSs. Moreover, with consideration of the competition and cooperation, we propose a Stackelberg game framework with sub-noncooperative optimization. Thirdly, the existence and uniqueness of both Stackelberg equilibrium (SE) and Nash equilibrium (NE) are theoretically analyzed and proved. Through the presented distributed energy scheduling algorithm, we can achieve the optimal solution. Finally, numerical results demonstrate the effectiveness and efficiency of our proposal through comparison with other existing schemes.

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 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.

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.

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 Computing Offloading Game for Mobile Devices and Edge Cloud Servers

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Meiwen Li ◽  
Qingtao Wu ◽  
Junlong Zhu ◽  
Ruijuan Zheng ◽  
Mingchuan Zhang
Keyword(s):  
Response Time ◽  
Mobile Devices ◽  
Resource Constraints ◽  
Stackelberg Equilibrium ◽  
Optimal Decision ◽  
Local Resource ◽  
Computing Resource ◽  
Delay Sensitive ◽  
Simulation Results ◽  
Cloud Servers

Computing offloading of mobile devices (MDs) through cloud is a greatly effective way to solve the problem of local resource constraints. However, cloud servers are usually located far away from MDs leading to a long response time. To this end, edge cloud servers (ECSs) provide a shorter response time due to being closer to MDs. In this paper, we propose a computing offloading game for MDs and ECSs. We prove the existence of a Stackelberg equilibrium in the game. In addition, we propose two algorithms, F-SGA and C-SGA, for delay-sensitive and compute-intensive applications, respectively. Moreover, the response time is reduced by F-SGA, which makes decisions quickly. An optimal decision is obtained by C-SGA, which achieves the equilibrium. Both algorithms above proposed can adjust the computing resource and utility of system users according to parameters control in computing offloading. The simulation results show that the game significantly saves the computing resources and response time of both the MD and the ECSs during the computing offloading process.

scholarly journals Design of optimal quantity discounts for multi-period bilevel production planning under uncertain demands

2020 ◽  
Vol 12 (2) ◽  
pp. 168781402090232
Author(s):  
Okihiro Yoshida ◽  
Tatsushi Nishi ◽  
Guoqing Zhang ◽  
Jun Wu
Keyword(s):  
Supply Chain ◽  
Production Planning ◽  
Demand Uncertainty ◽  
Optimal Solution ◽  
Stackelberg Equilibrium ◽  
Quantity Discounts ◽  
Planning Models ◽  
Proposed Model ◽  
Production Quantity ◽  
Optimal Quantity

The analysis of the quantity discount of the decentralized supply chain has been studied only for single-period planning models. This article presents the design of an optimal quantity discounts for multi-period bilevel production planning for two-echelon supply chains under demand uncertainty. In order to derive an optimal contract for multi-period production planning, the cumulative order quantity and production quantity are introduced. From our proposed model, a Stackelberg equilibrium is analytically derived for the supply chain when the supplier is the leader and the retailer is the follower. An optimal discount contract is analytically designed through the optimal solution of the centralized problem. Computational results show the effectiveness of the proposed discount contract under demand uncertainty.

scholarly journals The Architecture Design of Electrical Vehicle Infrastructure Using Viable System Model Approach

Systems ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 19
Author(s):  
Mahdi Boucetta ◽  
Niamat Ullah Ibne Hossain ◽  
Raed Jaradat ◽  
Charles Keating ◽  
Siham Tazzit ◽  
...  
Keyword(s):  
Urban Space ◽  
Electric Vehicles ◽  
Reference Model ◽  
System Model ◽  
Ecosystem Structure ◽  
Viable System Model ◽  
Charging Station ◽  
Viable System ◽  
Station Location ◽  
Ev Charging

Exponential technological-based growth in industrialization and urbanization, and the ease of mobility that modern motorization offers have significantly transformed social structures and living standards. As a result, electric vehicles (EVs) have gained widespread popularity as a mode of sustainable transport. The increasing demand for of electric vehicles (EVs) has reduced the some of the environmental issues and urban space requirements for parking and road usage. The current body of EV literature is replete with different optimization and empirical approaches pertaining to the design and analysis of the EV ecosystem; however, probing the EV ecosystem from a management perspective has not been analyzed. To address this gap, this paper develops a systems-based framework to offer rigorous design and analysis of the EV ecosystem, with a focus on charging station location problems. The study framework includes: (1) examination of the EV charging station location problem through the lens of a systems perspective; (2) a systems view of EV ecosystem structure; and (3) development of a reference model for EV charging stations by adopting the viable system model. The paper concludes with the methodological implications and utility of the reference model to offer managerial insights for practitioners and stakeholders.

scholarly journals Increasing Electric Vehicles Reliability by Non-Invasive Diagnosis of Motor Winding Faults

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2510
Author(s):  
Konrad Górny ◽  
Piotr Kuwałek ◽  
Wojciech Pietrowski
Keyword(s):  
Electric Vehicles ◽  
Diagnostic Method ◽  
Induction Motors ◽  
Early Stage ◽  
Short Circuit ◽  
Damage Classification ◽  
Non Invasive ◽  
Signal Features ◽  
Empirical Wavelet Transform ◽  
Simulation Results

The article proposes a proprietary approach to the diagnosis of induction motors allowing increasing the reliability of electric vehicles. This approach makes it possible to detect damage in the form of an inter-turn short-circuit at an early stage of its occurrence. The authors of the article describe an effective diagnostic method using the extraction of diagnostic signal features using an Enhanced Empirical Wavelet Transform and an algorithm based on the method of Ensemble Bagged Trees. The article describes in detail the methodology of the carried out research, presents the method of extracting features from the diagnostic signal and describes the conclusions resulting from the research. Phase current waveforms obtained from a real object as well as simulation results based on the field-circuit model of an induction motor were used as a diagnostic signal in the research. In order to determine the accuracy of the damage classification, simple metrics such as accuracy, sensitivity, selectivity, precision as well as complex metrics weight F1 and macro F1 were used.

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