Multi-Objective Optimal Scheduling of Electric Vehicle batteries in Battery Swapping Station

被引：14

作者：

Battapothula, Gurappa ^{[1
]}

Yammani, Chandrasekhar ^{[1
]}

Maheswarapu, Sydulu ^{[1
]}

机构：

[1] Natl Inst Technol, Dept Elect Engn, Warangal, Andhra Pradesh, India

来源：

PROCEEDINGS OF 2019 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES EUROPE (ISGT-EUROPE) | 2019年

关键词：

Battery Swapping Station; Dynamic pricing model; Electric vehicles; Shuffled Frog Leaping Algorithm; MODEL; OPERATION; LOAD;

D O I：

10.1109/isgteurope.2019.8905586

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Due to development of the batteries and it's charging technologies, public incentives and growing criticism on dense air pollution, the electrical vehicles (EVs) gaining more popularity as compared to traditional fuel vehicles. In this paper, the multi-objective optimal scheduling of Electric Vehicle batteries in Battery Swapping Station (BSS) is aimed in order to optimize the number of EV batteries taken from battery stock. Further, degradation cost of batteries and electricity charging cost of batteries also considered for optimal scheduling of EV batteries in BSS. The dynamic electricity pricing model is considered to avoid new peaks of battery charging demand in BSS. EV battery swapping demand in each hour of the day is solved by using a multi-objective Shuffled Frog Leaping Algorithm (SFLA). The simulation results present the effectiveness of multi-objective optimization and dynamic pricing model.

引用

页数：5

共 11 条

[1] Multi-objective optimum charging management of electric vehicles through battery swapping stations [J].