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IEEE Transactions on Sustainable Energy
Article . 2024 . Peer-reviewed
License: IEEE Copyright
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Local Energy Market Design for Power- and Hydrogen-Based Microgrids Considering a Hybrid Uncertainty Controlling Approach

Authors: Amin Mansour Saatloo; Abbas Mehrabi; Mousa Marzband; Mohammad Amin Mirzaei; Nauman Aslam;

Local Energy Market Design for Power- and Hydrogen-Based Microgrids Considering a Hybrid Uncertainty Controlling Approach

Abstract

Despite the significant merits of plugin electric vehicles (PEVs) and fuel cell electric vehicles (FCEVs), their enormous rise has posed serious challenges in terms of energy supply. This research proposes a sustainable energy platform to integrate PEVs and FCEVs under the concept of microgrid (MG) with power and green hydrogen as energy carriers, so-called integrated power, and hydrogen MG (IPHMG). In addition, a decentralized market clearing model is developed to enable the nearby IPHMG to interact in a local energy market (LEM). The LEM is run by a central manager for both power and hydrogen. To do so, the mobile edge computing (MEC) system is proposed to move the computation from a central cloud server to decentralized edge servers, causing to reducing the computational burden and increasing data security and privacy. Moreover, the fast alternating direction method of multipliers (fast-ADMM) is employed to decompose the problem. Further, this work advances the state-of-the-art in uncertainty management by introducing a tri-level uncertainty controlling approach to fully consider the uncertain parameters. According to the obtained results, the community of IPHMGs could reduce 5.86% of total cost by trading energy in the LEM and the presented hybrid uncertainty management model could protect the community against uncertainties by reducing the total cost by 8.08%.

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hybrid uncertainty, mobile edge computing management, 330, local energy market, plugin electric vehicle, Fuel cell electric vehicle, 620

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Average
Average
Top 10%
Green