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Efficient and robust power and energy management for large clusters of plug‐in electric vehicles and distribution networks
Author(s) -
Kanellos Fotios D.,
Kalaitzakis Kostas,
Psarras Ioannis,
Katsigiannis Υannis
Publication year - 2022
Publication title -
iet energy systems integration
Language(s) - English
Resource type - Journals
ISSN - 2516-8401
DOI - 10.1049/esi2.12070
Subject(s) - computer science , robustness (evolution) , mathematical optimization , renewable energy , flexibility (engineering) , electricity , electric power system , power (physics) , reliability engineering , engineering , electrical engineering , mathematics , biochemistry , chemistry , statistics , physics , quantum mechanics , gene
In this paper, an efficient and robust power and energy management for large clusters of plug‐in electric vehicles (PEVs) and distribution networks is proposed. The method aims to minimise the charging cost of large clusters of PEVs in real time while ensuring distribution network normal operation and satisfying a large number of constraints from PEV level up to distribution network. The design of the method ensures very low dependence on forecast errors of critical quantities such as electricity price while it can be easily integrated with conventional optimal power flow algorithms. To this end, innovative virtual differential operation costs are assigned to clusters of PEVs. Moreover, an innovative definition of the flexibility of a cluster of PEVs to change its power is introduced while a simple idea based on the principle of the selection of the fittest is used to achieve efficient power dispatch to the PEVs with minimal computational requirements. The efficiency and the robustness of the proposed method are proved by detailed simulations of several operation scenarios of a realistic distribution network with large penetration of PEVs and renewable energy sources.

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