Optimal Allocation for Distributed Generation Considering V2G of Electric Vehicle

CHEN Shengkai; YANG Wei; XU Ze; ZHANG Wenqiang

doi:10.14044/j.1674-1757.pcrpc.2021.05.023

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Optimal Allocation for Distributed Generation Considering V2G of Electric Vehicle

更新时间：2024-09-14

- Optimal Allocation for Distributed Generation Considering V2G of Electric Vehicle
- POWER CAPACITOR & REACTIVE POWER COMPENSATION Vol. 42, Issue 5, Pages: 143-149(2021)
- 作者机构：
  
  南京理工大学自动化学院
- 作者简介：
- 基金信息：
- DOI：10.14044/j.1674-1757.pcrpc.2021.05.023
  CLC： TM73;U491.8
- Published：2021，
- 稿件说明：
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CHEN SHENGKAI, YANG WEI, XU ZE, et al. Optimal Allocation for Distributed Generation Considering V2G of Electric Vehicle. [J]. Power capacitor & reactive power compensation, 2021, 42(5): 143-149.
DOI：

CHEN SHENGKAI, YANG WEI, XU ZE, et al. Optimal Allocation for Distributed Generation Considering V2G of Electric Vehicle. [J]. Power capacitor & reactive power compensation, 2021, 42(5): 143-149. DOI： 10.14044/j.1674-1757.pcrpc.2021.05.023.

摘要

电动汽车(electric vehicle

EV)的车网互联(vehicle to grid

V2G)与风光等可再生能源分布式电源(distributed generation

DG)的不稳定出力

给配电网带来不确定性。首先在考虑EV行驶特征随机性的基础上提出以削峰填谷与用户充电费用为目标的有序充放电V2G策略

建立EV充放电功率的概率模型。其次

在考虑风速、光照强度、负荷以及EV充放电功率的随机性以及相关性的基础上

建立了以配电网总成本、环境收益和供电质量为目标函数的多目标DG优化配置模型。然后采用萤火虫算法(firefly algorithm

FA)求解出全局最优配置方案。最后采用实际算例进行仿真

通过分析仿真结果

证明所提出模型与方法的可行性。

Abstract

The unstable output of such distributed generation（DG）of renewable energy as vehicle to grid（V2G）of electric vehicle（EV）and wind as well as solar energy brings uncertainty of the network. First

the strategy of charging and discharging V2G with the peak-load shifting and the user charging cost as objective is proposed on the basis of considering the randomness of EV driving characteristic and probabilistic model of EV charge and discharge power is set up. Then

a multi-objective GD optimal allocation model with the total cost of distribution network

environmental benefits and the power supply quality as the objective function is set up on the basis of considering the randomness and relevance of wind velocity

illumination intensity

load and EV charging and discharging power. After that

the globally optimal allocation planning is solved by using firefly algorithm（FA）. Finally

the simulation is performed by the use of actual calculation example and the feasibility of the proposed model is proved through analysis of the simulation result.

关键词

分布式电源(DG)电动汽车(EV)V2G不确定性萤火虫算法

Keywords

distributed generation（DG）electric vehicle（EV）V2Guncertaintyfirefly algorithm

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