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Coordinated flexible energy and self-healing management according to the multi-agent system-based restoration scheme in active distribution network

Bagherzadeh, Leila; Shayeghi, Hossein; Pirouzi, Sasan; Shafie-khah, Miadreza; Catalão, João P.S. (2021-03-16)

 
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https://doi.org/10.1049/rpg2.12145

Bagherzadeh, Leila
Shayeghi, Hossein
Pirouzi, Sasan
Shafie-khah, Miadreza
Catalão, João P.S.
Wiley Open Access Institution of Engineering and Technology (IET)
16.03.2021
doi:10.1049/rpg2.12145
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2022031623730

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vertaisarvioitu
© 2021 The Authors. IET Renewable Power Generation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
M. Shafie-khah acknowledges FLEXIMAR-project (Novel marketplace for energy flexibility), which has received funding from Business Finland Smart Energy Program, 2017-2021. J.P.S. Catalão acknowledges the support by FEDER through COMPETE 2020 and by FCT, under POCI-01-0145-FEDER-029803 (02/SAICT/2017).
Tiivistelmä
This study presents the optimal model of the coordinated flexible energy and self-healing management (C-FE&SH-M) in the active distribution network (ADN) including renewable energy sources (RESs), electric vehicles (EVs) and demand response program (DRP).The flexible energy management (FEM) is extracted using coordination between the RESs, EVs and DRP. The self-healing method (SHM) is related to multi-agent system-based restoration process (MAS-based RP) that finds the optimal restoration pattern at the fault condition according to the different zone agents (ZAs) distributing along with the network. This method minimizes the difference between energy cost and flexibility benefit related to the FEM part and difference between the number of switching operation and priority loads restored based on the SHM part. Also, this problem subjects to power flow equations, RESs and active loads constraints, restoration process formulation and system operation limits. Stochastic programming is used to model the uncertainty of loads, energy prices, RESs and EVs. Hereupon, the suggested strategy is implemented on the 33-bus radial distribution network and it is solved by the crow search algorithm (CSA). Ultimately, the obtained results imply the high flexibility and security of the operation, incorporating the proposed strategy, and delineate the optimal restoration scheme for the ADN.
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