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An optimal dispatch schedule of EVs considering demand response using improved MACD algorithm

delete2023-11-20
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OA
AI
M
Mounir Bouzguenda *
H
Hatatah, Muahmmad
A
Aamir Ali
G
Ghulam Abbas
K
Khan, Aamir
E
Ezzeddine Touti
A
Amr Yousef
S
Sohrab Mirsaeidi
A
Ahmed Alshahir
DOI:10.3389/fenrg.2023.1295476delete
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摘要

摘要

En 中文
The growing popularity of electric vehicles presents a significant challenge to current electric grids since the rising number of these vehicles places additional strain on power systems inside distribution networks. A proposed paradigm is presented for electric vehicles (EVs), which is subsequently partitioned into three distinct dispatching areas to assess its practicality. This study is structured around two primary objectives. The first objective focuses on EV owners aiming to minimize their electricity consumption costs while also receiving compensation for providing services. The second objective involves using an aggregator to establish distinct tariffs for each dispatching area. Additionally, the aggregator aims to shift the charging load demand from peak to off-peak hours and distribute the charging demand to each agent. The authors of this study propose the utilization of a charging and discharging coordination method, specifically the Multi-Agents Charging and Discharging (MACD) algorithm, as a means to successfully tackle the issue of charging demand during peak hours. The objective of the proposed algorithm is to effectively handle the increased charging requirements during peak periods by using vehicle-to-grid (V2G) technologies within the context of Smart Grid systems and electric vehicle (EV) batteries. Importantly, this reduction is achieved without compromising the performance of electric vehicles (EVs) or the convenience experienced by EV owners. The algorithm under consideration demonstrates reduced power charging costs for various sectors. Specifically, it achieves a decrease of 15% for households, 14.6% for corporate buildings, and 14.5% for Industrial Park EV aggregators.
Keyword:
combined aggregator
demand response
electricity market
vehicle-to-grid (V2G)
EVs (electric vehicles)

期刊

Frontiers in Energy Research 封面图
Frontiers in Energy Research
IF:
2.4
论文数:
1.0K
被引数:
1.4W

机构

K
King Faisal University
学者数:
4.4K
论文数: 4.4K
被引数: 5.0K
A
al baha university
学者数:
931
论文数: 1.0K
被引数: 12
U
university of business & technology
学者数:
266
论文数: 298
被引数: 0
B
Beijing Jiaotong University
学者数:
2.2W
论文数: 1.7W
被引数: 1.2W
E
egyptian knowledge bank (ekb)
学者数:
11.6W
论文数: 9.3W
被引数: 84
A
Al Jouf University
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3.4K
论文数: 3.4K
被引数: 2
S
southeast university - china
学者数:
5.3W
论文数: 4.9W
被引数: 57
N
northern border university
学者数:
1.8K
论文数: 2.1K
被引数: 2
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