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Multimicrogrid Load Balancing Through EV Charging Networks
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AI
DOI：10.1109/JIOT.2021.3108698.png)
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摘要
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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 article, 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.
Keyword:
Electric vehicle charging
Microgrids
Charging stations
Load modeling
Transportation
Power systems
Scheduling
Demand response (DR)
electric vehicle (EV)
EV charging network
power distribution grid
smart grid
期刊
IF:
8.9
论文数:
1.4W
被引数:
7.8W
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Planning for electric vehicle needs by coupling charging profiles with urban mobility.png)
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