Grid Scheduling Strategy Considering Electric Vehicles Participating in Multi-microgrid Interaction

Yu, Zexu; Dou, Zhenhai; Zhao, Yupei; Xie, Ruishuo; Qiao, Mengmeng; Wang, Yuanyuan; Liu, Lianxin

doi:10.1007/s42835-022-01294-x

Cited by 6 publications

(1 citation statement)

References 24 publications

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“…The authors in [40] proposed genetic-algorithm-based day ahead scheduling of EVs in MMGs in grid-connected and islanded modes. Reference [41] proposed a two-level control of grid-connected MGs based on particle swarm optimization. First, the grid load is optimized, in order to minimize the total cost and maximize the penetration of RESs and the profit.…”

Section: Introductionmentioning

confidence: 99%

A Novel Multi Level Dynamic Decomposition Based Coordinated Control of Electric Vehicles in Multimicrogrids

Aslam,

Kashif,

Gulzar

et al. 2023

Sustainability

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This paper presents a novel tetra-level dynamic decomposition-based control approach for coordinated operation of electric vehicles in multimicrogrids, which is comprehensive, generic, modular, and secure in nature, to maximize the utilization of renewable energy sources, while meeting the load demands with the resources available. There are a number of microgrids that are connected to the grid. Each microgrid consists of a number of renewable energy sources, energy storage systems, non-renewable energy sources, electric vehicles, and loads. Each distributed energy source or load is controlled by a microsource controller. All microsource controllers with a similar nature are controlled by a unit controller, and all the unit controllers in a microgrid are controlled by a microgrid controller. There is a single multimicrogrid controller at the top. The proposed control scheme was verified through simulation-based case studies.

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Section: Introductionmentioning

confidence: 99%