An Interactive Strategy of Grid and Electric Vehicles Based on Master-Slaves Game Model

Cheng, Hongyan; Luo, Ting; Chen, Kang; Xin, Jianbo; Wan, Hua; Pei, Feng Lai; Tian, Xu

doi:10.1007/s42835-019-00323-6

Cited by 6 publications

(2 citation statements)

References 19 publications

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“…The initial conditions of the model are set as follows: the initial time is 0, the final time is 12 months, and the time step is 0.0015625 [27]. According to the research [28,29], based on the real situation and the assumptions of the model, the revenue level for the owner-operated charging station is 100 units, the cost of retrofitting to connect the charging station to the platform for network control and unified settlement is 60 units, the revenue increase for the charging station owner's participation in the sharing platform is 20 units, the idle loss for the charging station owner is 150 units, and the social efficiency loss for the idle charging station is 200 units. The government's cost for building the sharing platform is 80 units, the subsidy cost is 20 units, the management fee charged for the charging station operation is 40 units, and the social efficiency gain from the charging station utilization improvement is 150 units.…”

Section: Simulation Results and Sensitivity Analysis For Different Sc...mentioning

confidence: 99%

An Evolutionary Game Analysis of Shared Private Charging Pile Behavior in Low-Carbon Urban Traffic

Zhu

Zhou

et al. 2023

Sustainability

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Choosing new energy vehicles for travel, especially electric vehicles, is an important component of building a low-carbon urban transportation system. However, the charging need of electric vehicle users is still constrained by the unreasonable layout and insufficient supply of public charging piles in cities. Private charging pile sharing, as an alternative policy tool, can play a beneficial role in solving this problem. However, it needs decision-makers in urban transportation to take corresponding measures to promote. This paper constructs an evolutionary game model to study the decision behavior of participants in a private pile-sharing platform. Through numerical simulation analysis, it is found that under most parameter conditions, the government tends to establish a shared charging pile platform based on public interests. Private charging pile owners are influenced by the relationship between the cost of supply modification and revenue, and they tend to join the shared platform when they expect to recover the modification cost. The research conclusions of this paper will provide support for exploring how participants make decisions to maximize overall benefits in the development of low-carbon urban transportation.

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Section: Simulation Results and Sensitivity Analysis For Different Sc...mentioning

confidence: 99%

An Evolutionary Game Analysis of Shared Private Charging Pile Behavior in Low-Carbon Urban Traffic

Zhu

Zhou

et al. 2023

Sustainability

View full text Add to dashboard Cite

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“…Planning of units in the distribution network in the presence of EVs can be connected to the grid in a variety of ways. In [12], the authors have introduced a collaborative model of units in the presence of networkable electric vehicles by using a particle swarm optimization (PSO) algorithm to reduce the operation cost and the environmental emission in a MG. Also, in [13], scheduling DGs and scheduling charging and discharging EVs in a smart grid using the GAMS software was designed to reduce the cost of operating and emission rates. In [14] an energy management system (EMS) is proposed for residential microgrid (MG) with home parking lot based on the mixed integer linear program (MILP) method and for balancing power transactions in MG.…”

Section: Introductionmentioning

confidence: 99%

Distributed Generation Management in Smart Grid with the Participation of Electric Vehicles with Respect to the Vehicle Owners’ Opinion by Using the Imperialist Competitive Algorithm

et al. 2022

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In this paper, a modified version of Imperialist Competitive Algorithm (ICA) is proposed for the optimal energy management of a Microgrid (MG) with Parking Lots (PL) and Distributed Generation (DG) units. A 24-h scheduling for participation in DG units and electric vehicles PLs in two scenarios is done. The PLs are divided into seven group that each group has different trip behavior. Therefore, energy management should be done in such a way as to minimize operating costs according to the charging status of electric vehicles as well as the production capacity of distributed generation sources. Finally, the results of the two scenarios are reviewed separately and compared. The simulation results proved the effectiveness of the proposed method. The MG operation cost is decreased about 63%. Also, the optimization results. The optimization results by the proposed ICA algorithm are compared with the results of genetic algorithm (GA) and particle swarming optimization (PSO) algorithms. The optimization results confirm better performance of the proposed algorithm compared to GA and PSO algorithms.

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An Algorithm to Enhance the Profit Margin of Electric Vehicle Owners and Resilience of Multi-microgrid Using EV

Ali

Hussain

Baek

et al. 2022

J. Electr. Eng. Technol.

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Improvement in the electric vehicles (EVs) area and the expanding number and greatness of catastrophic events have drawn in the consideration of analysts to use the put-away energy in EVs and upgrade the versatility of force frameworks. Microgrids are viewed as a possible source to take care of these issues. Nearby assets accessible in the microgrid are utilized to improve the strength of the system, for example, battery energy storage system. An extra battery energy storage system to improve the resiliency of the system might prompt an expansion in capital expenses. Consequently, in this article, existing EVs in the microgrid parking lot is utilized revenue-driven acquiring and flexibility upgrades with next to no extra capital expense. In the normal operation scenario, using the proposed strategy EV energy is sold to the MGs in the system offering the highest bidding cost, resulting in raise in the profit margin for the EV owners. In the case of contingencies, the proposed scheme supplies energy from grid-connected microgrids to islanded microgrids through accessible EVs. The strategy to supply energy is carried out in three steps. In the first step, required energy and available energy in the EVs is informed to the central energy management system (CEMS). In the second step, CEMS decides the microgrid to supply energy to the islanded microgrid among grid-connected microgrids. Finally, the microgrid chosen by the CEMS to supply energy to islanded microgrid concludes which EV ought to be sent among the accessible EVs. Simulations have been carried out to show the viability of the proposed scheme.

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An Interactive Strategy of Grid and Electric Vehicles Based on Master-Slaves Game Model

Cited by 6 publications

References 19 publications

An Evolutionary Game Analysis of Shared Private Charging Pile Behavior in Low-Carbon Urban Traffic

An Evolutionary Game Analysis of Shared Private Charging Pile Behavior in Low-Carbon Urban Traffic

Distributed Generation Management in Smart Grid with the Participation of Electric Vehicles with Respect to the Vehicle Owners’ Opinion by Using the Imperialist Competitive Algorithm

An Algorithm to Enhance the Profit Margin of Electric Vehicle Owners and Resilience of Multi-microgrid Using EV

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