 Multiple hydrogen-based hybrid storage systems operation for microgrids: A combined TOPSIS and model predictive control methodologyBei Li, Hongzhi Miao and Jiangchen Li Applied Energy, 2021, vol. 283, issue C, No S0306261920316871 Abstract: Hydrogen-based hybrid storage system has a high energy density, which can operate as the long-term storage system, and play an important role in future smart cities. In the hydrogen storage system, fuel cell, hydrogen tanks, and electrolyzer are often combined together and operating with complex electrochemical reactions. How to efficiently operate the hydrogen storage system and considering the convoluted electrochemical reactions is a problem. In addition, multiple hydrogen storage systems are often grouped together to supply the demands. Thus, cooperating the dispatching of these storage systems is another complicated problem. In this paper, we first present a two-dimension model considering temperature influences for hydrogen-based microgrid, where a regression method is adopted. Moreover, a combined allocating-and-dispatching methodology involving two layers is proposed to cooperate the multiple storage systems. Specifically, both TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) and fuzzy logic are adopted as the first-layer allocating algorithm. Then, the model predictive control (MPC) is utilized as the second-layer dispatching algorithm. Based on the combined method, power is firstly allocated to hybrid storage system considering each hybrid storage system health conditions, and secondly scheduled to battery storage and hydrogen storage based on MPC method. The simulation results showed that with the combined Dematel-TOPSIS and MPC algorithm, the degradation index and operation cost were the smallest among three algorithms, and can further extend the lifetime of hybrid hydrogen storage systems in microgrids. Keywords: Microgrid; Hydrogen storage system; Two-dimension model; TOPSIS; Allocating-and-dispatching; Model predictive control (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:283:y:2021:i:c:s0306261920316871 Ordering information: This journal article can be ordered from DOI: 10.1016/j.apenergy.2020.116303 Access Statistics for this article Applied Energy is currently edited by J. Yan More articles in Applied Energy from Elsevier |
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