Local Energy Market Design for Power-and Hydrogen-Based Microgrids Considering a Hybrid Uncertainty Controlling Approach
Author | Saatloo, Amin Mansour |
Author | Mehrabi, Abbas |
Author | Marzband, Mousa |
Author | Mirzaei, Mohammad Amin |
Author | Aslam, Nauman |
Available date | 2024-08-29T04:47:28Z |
Publication Date | 2024-01-01 |
Publication Name | IEEE Transactions on Sustainable Energy |
Identifier | http://dx.doi.org/10.1109/TSTE.2023.3288745 |
Citation | Saatloo, A. M., Mehrabi, A., Marzband, M., Mirzaei, M. A., & Aslam, N. (2023). Local energy market design for power-and hydrogen-based microgrids considering a hybrid uncertainty controlling approach. IEEE Transactions on Sustainable Energy, 15(1), 398-413. |
ISSN | 19493029 |
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%. |
Language | en |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Subject | Fuel cell electric vehicle hybrid uncertainty local energy market mobile edge computing management plugin electric vehicle |
Type | Article |
Pagination | 398-413 |
Issue Number | 1 |
Volume Number | 15 |
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