Collaborative Optimization of Electric Vehicles Based on MultiAgent Variant Roth–Erev Algorithm

With the implementation of the carbon neutral policy, the number of electric vehicles (EVs) is increasing. Thus, it is urgently needed to manage the charging and discharging behavior of EVs scientifically. In this paper, EVs are regarded as agents, and a multiagent cooperative optimization scheduling model based on Roth–Erev (RE) algorithm is proposed. The charging and discharging behaviors of EVs will influence each other. The charging and discharging strategy of one EV owner will affect the choice of others. Therefore, the RE algorithm is selected to obtain the optimal charging and discharging strategy of the EV group, with the utility function of the prospect theory proposed to describe EV owners’ different risk preferences. The utility function of the prospect theory has superior effectiveness in describing consumers’ utility. Finally, in the case of residential electricity, the effectiveness of the proposed method is verified. Compared with that of random charging, this method reduces the total EV group cost of EVs by 52.4%, with the load variance reduced by 26.4%.

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A Power and Load Optimization Scheduling Model based on Flexible Thermal Load Participating in Assisted Peak Regulation

2021 6th Asia Conference on Power and Electrical Engineering (ACPEE) ◽

10.1109/acpee51499.2021.9436863 ◽

2021 ◽

Author(s):

Zidong Liu ◽

Wenying Liu ◽

Yun Zeng ◽

Xiaoqi Han ◽

Changyong Dou ◽

...

Keyword(s):

Thermal Load ◽

Load Optimization ◽

Model Based ◽

Scheduling Model ◽

Optimization Scheduling

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Multi-objective Optimization Scheduling Model Based on NSGA-II Algorithm

2020 IEEE 3rd International Conference on Electronics and Communication Engineering (ICECE) ◽

10.1109/icece51594.2020.9353023 ◽

2020 ◽

Author(s):

Ruifeng Bian ◽

Wenyi Tan ◽

Yilun Li ◽

Yichen Hou

Keyword(s):

Multi Objective Optimization ◽

Nsga Ii ◽

Multi Objective ◽

Model Based ◽

Scheduling Model ◽

Optimization Scheduling

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Distribution Network Hierarchically Partitioned Optimization Considering Electric Vehicle Orderly Charging with Isolated Bidirectional DC-DC Converter Optimal Efficiency Model

Energies ◽

10.3390/en14061614 ◽

2021 ◽

Vol 14 (6) ◽

pp. 1614

Author(s):

Qiushi Zhang ◽

Jian Zhao ◽

Xiaoyu Wang ◽

Li Tong ◽

Hang Jiang ◽

...

Keyword(s):

Load Balancing ◽

Electric Vehicle ◽

Double Layer ◽

Electric Vehicles ◽

Distribution Network ◽

Collaborative Optimization ◽

Voltage Distribution ◽

Medium Voltage ◽

Scheduling Model ◽

Optimal Efficiency

The access of large-scale electric vehicles (EVs) will increase the network loss of medium voltage distribution network, which can be alleviated by adjusting the network structure and orderly charging for EVs. However, it is difficult to accurately evaluate the charging efficiency in the orderly charging of electric vehicle (EV), which will cause the scheduling model to be insufficiently accurate. Therefore, this paper proposes an EV double-layer scheduling model based on the isolated bidirectional DC–DC (IBDC) converter optimal efficiency model, and establishes the hierarchical and partitioned optimization model with feeder–branch–load layer. Firstly, based on the actual topology of medium voltage distribution network, a dynamic reconfiguration model between switching stations is established with the goal of load balancing. Secondly, with the goal of minimizing the branch layer network loss, a dynamic reconstruction model under the switch station is established, and the chaotic niche particle swarm optimization is proposed to improve the global search capability and iteration speed. Finally, the power transmission loss model of IBDC converter is established, and the optimal phase shift parameter is determined to formulate the double-layer collaborative optimization operation strategy of electric vehicles. The example verifies that the above model can improve the system load balancing degree and reduce the operation loss of medium voltage distribution network.

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Optimization scheduling model based on source-load-energy storage coordination in power systems

2016 22nd International Conference on Automation and Computing (ICAC) ◽

10.1109/iconac.2016.7604905 ◽

2016 ◽

Cited By ~ 3

Author(s):

Yaowang Li ◽

Shihong Miao ◽

Xing Luo ◽

Jihong Wang

Keyword(s):

Energy Storage ◽

Power Systems ◽

Model Based ◽

Scheduling Model ◽

Optimization Scheduling

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Based on Prospect Theory Regional Integrated Energy Electric Vehicle Scheduling Model

E3S Web of Conferences ◽

10.1051/e3sconf/202129901015 ◽

2021 ◽

Vol 299 ◽

pp. 01015

Author(s):

Shufeng Li ◽

Qiang Yao ◽

Zhankun Xu ◽

Jianwei Gao ◽

Yu Yang

Keyword(s):

Prospect Theory ◽

Electric Vehicle ◽

Electric Vehicles ◽

Demand Response ◽

Vehicle Scheduling ◽

Regional Energy ◽

Scheduling Model ◽

Load Fluctuation ◽

Price Demand ◽

The Cost

Regional comprehensive energy is the focus of current research, and electric vehicles are an important part of regional energy. The orderly participation of regional EV groups in demand response for optimal scheduling of charge and discharge can not only save the charging cost of EV owners, but also smooth the load fluctuation caused by EV charging. In this paper, an Integrated Energy Electric Vehicle Scheduling Model Based on Prospect Theory is proposed. Firstly, the optimal charging and discharging strategy of each Electric Vehicle is obtained Based on the price demand response Model. Secondly, a decision-making method of participation willingness based on the prospect theory is proposed to consider the risk bias of EV owners. Finally, a case study is provided to verify the effectiveness of the proposed method. Compared with electric vehicles participating in random charging, the optimization model proposed in this paper reduces the cost by 32% and the average hourly load by 67%.

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