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Multimicrogrid Load Balancing Through EV Charging Networks
- Source :
- IEEE Internet of Things Journal. 9:5019-5026
- Publication Year :
- 2022
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2022.
-
Abstract
- Energy demand and supply vary from area to area where an unbalanced load may occur and endanger the system security constraints and cause significant differences in the locational marginal price (LMP) in the power system. With the increasing proportion of local renewable energy (RE) sources in microgrids that are connected to the power grid and the growing number of electric vehicle (EV) charging loads, the imbalance will be further magnified. In this paper, we first model the EV charging network as a cyber-physical system (CPS) that is coupled with both the transportation networks and the smart grids. Then we propose an EV charging station recommendation algorithm. With a proper charging scheduling algorithm deployed, the synergy between the transportation network and the smart grid can be created. The EV charging activity will no longer be a burden for power grids, but a load balancing tool that can transfer energy between the unbalanced distribution grids. The proposed system model is validated via simulations. The results show that the proposed algorithms can optimize the EV charging behaviors, reduce charging costs, and effectively balance the regional load profiles of the grids.
- Subjects :
- business.product_category
Computer Networks and Communications
Computer science
business.industry
Load balancing (electrical power)
Flow network
Automotive engineering
Computer Science Applications
System model
Renewable energy
Charging station
Electric power system
Smart grid
Hardware and Architecture
Signal Processing
Electric vehicle
business
Information Systems
Subjects
Details
- ISSN :
- 23722541
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- IEEE Internet of Things Journal
- Accession number :
- edsair.doi...........0d93938f7b21926b51f146a9afd4efe2
- Full Text :
- https://doi.org/10.1109/jiot.2021.3108698