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 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 A Game-Based Scheme for Resource Purchasing and Pricing in MEC for Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yajing Leng ◽  
Ming Wang ◽  
Bowen Ma ◽  
Ying Chen ◽  
Jiwei Huang
Keyword(s):  
Internet Of Things ◽  
Stackelberg Game ◽  
Incentive Compatibility ◽  
Experimental Results ◽  
Stackelberg Equilibrium ◽  
Optimal Solutions ◽  
Challenging Problem ◽  
Simulation Experiments ◽  
Iot Devices ◽  
The Individual

Mobile edge computing (MEC) is emerging as a promising paradigm to support the applications of Internet of Things (IoT). The edge servers bring computing resources to the edge of the network, so as to meet the delay requirements of the IoT devices’ service requests. At the same time, the edge servers can gain profit by leasing computing resources to IoT users and realize the allocation of computing resources. How to determine a reasonable resource leasing price for the edge servers and how to determine the number of resource purchased by users with different needs is a challenging problem. In order to solve the problem, this paper proposes a game-based scheme for resource purchasing and pricing aiming at maximizing user utility and server profit. The interaction between users and the edge servers is modeled based on Stackelberg game theory. The properties of incentive compatibility and envy freeness are theoretically proved, and the existence of Stackelberg equilibrium is also proved. A game-based user resource purchasing algorithm called GURP and a game-based server resource pricing algorithm called GSRP are proposed. It is theoretically proven that solutions of the proposed algorithms satisfy the individual rationality property. Finally, simulation experiments are carried out, and the experimental results show that the GURP algorithm and the GSRP algorithm can quickly converge to the optimal solutions. Comparison experiments with the benchmark algorithms are also carried out, and the experimental results show that the GURP algorithm and the GSRP algorithm can maximize user utility and server profit.

Research on Communication Scheduling Algorithm for Smart Home in Internet of Things Under Cloud Computing

2019 ◽  
Vol 23 (1) ◽  
pp. 124-128 ◽  
Author(s):  
Jie Zhang ◽  
◽  
Mantao Wang
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Internet Of Things ◽  
Objective Function ◽  
Smart Home ◽  
Data Flow ◽  
Scheduling Algorithm ◽  
Optimal Solution ◽  
Low Latency ◽  
Communication Scheduling

The current communication scheduling algorithm for smart home cannot realize low latency in scheduling effect with unreasonable control of communication throughput and large energy consumption. In this paper, a communication scheduling algorithm for smart home in Internet of Things under cloud computing based on particle swarm is proposed. According to the fact that the transmission bandwidth of any data flow is limited by the bandwidth of network card of sending end and receiving end, the bandwidth limits of network card of smart home communication server are used to predict the maximum practicable bandwidth of data flow. Firstly, the initial value of communication scheduling objective function of smart home and particle swarm is set, and the objective function is taken as the fitness function of particle. Then the current optimal solution of objective function is calculated through predicted value and objective function, current position and flight speed of particle should be updated until the iteration conditions are met. Finally, the optimal solution is output, the communication scheduling of smart home is thus realized. Experiments show that this algorithm can realize low latency with small energy consumption, and the throughput is relatively reasonable.

scholarly journals CrowdBox: Crowdsourced Network-in-Box Recruitment for Edge Computing-Enabled Industrial Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Pengfei Wang ◽  
Chi Lin ◽  
Zhen Yu ◽  
Leyou Yang ◽  
Qiang Zhang
Keyword(s):  
Internet Of Things ◽  
Stackelberg Game ◽  
Edge Computing ◽  
Stackelberg Equilibrium ◽  
Smart Devices ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Communication Demands ◽  
Edge Layer ◽  
Optimal Reward

The rapidly increasing number of smart devices deployed in the Industrial Internet of Things (IIoT) environment has been witnessed. To improve communication efficiency, edge computing-enabled Industrial Internet of Things (E-IIoT) has gained attention recently. Nevertheless, E-IIoT still cannot conquer the rapidly increasing communication demands when hundreds of millions of IIoT devices are connected at the same time. Considering the future 6G environment where smart network-in-box (NIB) nodes are everywhere (e.g., deployed in vehicles, buses, backpacks, etc.), we propose a crowdsourcing-based recruitment framework, leveraging the power of the crowd to provide extra communication resources and enhance the communication capabilities. We creatively treat NIB nodes as edge layer devices, and CrowdBox is devised using a Stackelberg game where the E-IIoT system is the leader, and the NIB nodes are the followers. CrowdBox can calculate the optimal reward to reach the unique Stackelberg equilibrium where the utility of E-IIoT can be maximized while none of the NIB nodes can improve its utility by deviating from its strategy. Finally, we evaluate the performance of CrowdBox with extensive simulations with various settings, and it shows that CrowdBox outperforms the compared algorithms in improving system utility and attracting more NIB nodes.

scholarly journals Development of Fast charging system with ZVS integrated with Fuzzy controller-based Hybrid renewable energy source

2021 ◽  
Vol 2070 (1) ◽  
pp. 012117
Author(s):  
Raghunath Niharika ◽  
K M Sai Pavan ◽  
P V Manitha
Keyword(s):  
Renewable Energy ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Fuzzy Controller ◽  
Greenhouse Gas Emission ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Pv System ◽  
Charging System ◽  
On The Road

Abstract Climate change is a growing concern due to greenhouse gas emission and transportation has increased the requirement for various energy sources with limiting and less pollution. But with the establishment of more electric vehicles on the road, charging EV’s will be difficult if the grid is used. When many numbers of electric vehicles are integrated to the grid, it will inevitably have a huge effect on its function and control. Hence, there is a requirement for an effective charging system for electric vehicles using renewable energy sources. Solar energy is renewable and green, but the volatile nature of energy from the Photo-Voltaic (PV) system and dynamic charging requirement of electric vehicles has added new problems to the effective charging of EV from these sources. The Solar powered charging station with battery storage system is a better solution for this problem. The power is transferred from the AC grid to the DC link when there is a depletion of power from solar. This paper deals with DC level 1 fast charger to charge an electric vehicle with phase shifted full bridge converter as a main charging topology which is able to deliver the load of 50KW to charge the electric vehicle. To maintain a constant voltage at the output of the boost converter connected to the solar panel, a fuzzy controller is also developed in the proposed system

scholarly journals Tribrid Renewable Energy Charging System for Electric Cars

2020 ◽  
Vol 8 (5) ◽  
pp. 1151-1154
Keyword(s):  
Renewable Energy ◽  
Electric Power ◽  
Electric Vehicles ◽  
Alternative Fuels ◽  
Energy Utilization ◽  
Peak Oil ◽  
Electric Cars ◽  
Charging System ◽  
The World ◽  
Hybrid Electric

Vehicles which run on fossil fuel are the most polluting grids in the world. Electric vehicles (EVs) are invented to cut greenhouse gas emissions. Hybrid electric cars are considered as clean and green source of driving. Just switching to renewable energy based hybrid electric vehicles for manufacturing would slash emissions by 65 per cent, according to Transport & Environment. Due to integration of various factors, like environmental concerns, very high prices of oil and the potential for peak oil, need to develop much clean alternative fuels and high end power systems for automobile has become a top priority for all governments around the word as well as vehicle manufacturers around the world. Tribrid Renewable Energy charging system for electric vehicles is an idea for the generation of electric power for EVs using integrated photovoltaic cells, micro wind turbines and piezoelectric system to electric power pistons. This Tribrid Renewable Energy charging system for electric vehicles is advanced technologies and efficient uses of them are reviewed in a comparative way and the same are presented in this paper. Along with this the recent trends in research and development for the advancement in technology of optimum energy utilization systems for future security of energy is presented.

Distributed Power Allocation for Multiuser Two-Way Relay Networks Using Stackelberg Game

2014 ◽  
Vol 18 (1) ◽  
pp. 48-55
Author(s):  
Fu Jiang ◽  
◽  
Chaoliang Zhu ◽  
Jun Peng ◽  
Yong He ◽  
...  
Keyword(s):  
Power Allocation ◽  
Stackelberg Game ◽  
Relay Networks ◽  
Energy Utilization ◽  
Stackelberg Equilibrium ◽  
Bandwidth Utilization ◽  
Relay Nodes ◽  
Allocation Algorithm ◽  
Allocation Process ◽  
Game Theoretic

Recently, two-way relay networks have been regarded as a promising technique that can improve bandwidth utilization. In this paper, the power allocation problem for multiuser two-way relay networks with amplifyand-forward protocol is investigated. In order to describe the self-interestedness of nodes in two-way relay networks, a two-level Stackelberg game is introduced to jointly optimize the benefits of the source pair and the relay nodes, where the relay nodes are modeled as leaders and the source pair is modeled as a follower. To facilitate the power allocation process, a distributed game-theoretic power allocation algorithm is proposed. Then, the existence and optimization of the Stackelberg equilibrium for the proposed power allocation algorithm is proven. The convergence of the presented algorithm is also analyzed by proving that price update is a standard function. Simulation results indicate that the proposed power allocation algorithm can improve energy utilization by jointly optimizing the utilities of both source pair and relay nodes.

Blockchain for Effective Renewable Energy Management in the Intelligent Transportation System

2021 ◽  
pp. 2141009
Author(s):  
Jianghua Zhao ◽  
Chuan He ◽  
Changrong Peng ◽  
Xiaodong Zhang
Keyword(s):  
Renewable Energy ◽  
Greenhouse Gas ◽  
Energy Management ◽  
Electric Vehicles ◽  
Energy Demand ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Energy Utilization ◽  
Management Process ◽  
Validation Process

In intelligent transportation systems (ITS), electric vehicles (EVs) play an essential role in reducing environmental pollution and minimizing high fuel costs. The EVs are three times efficient than conventional gasoline-powered vehicles, whereas it depends on the mix of source generation on the grid utilized for charging. However, in most cases, the EVs are resultant in emitting the more substantial greenhouse gas that extends fossil fuels’ lives. Therefore, the ITS contributing to developing the renewable energy management process is incorporated with electric vehicles to reduce greenhouse gas. The EVs are mostly designed to reduce the cost and improve efficiency during the charging infrastructure. Hence, renewable energies are saved exclusively and eliminating wasteful usage. In this work, a blockchain-based effective renewable energy management process should be created to achieve this goal. The blockchain process validates each EV before permitting them to charge their vehicle. The blockchain principle analyzes the energy demand of any EV and validates its demand through vehicle data. The validation process enables the same and original energy use vessel to be identified to remove threats associated activities efficiently. The validating process considering the vehicle information and energy utilization level to verify the EV. The block-based validation process monitoring each vehicle entered into the grid environment, and the ITS process minimizes the fuel wastage and enhances the system’s overall efficiency.

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