Journal of Applied Science and Engineering

Published by Tamkang University Press

1.30

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2.10

CiteScore

Si Chen and Xianda ZhaoThis email address is being protected from spambots. You need JavaScript enabled to view it.

The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China


 

Received: July 1, 2023
Accepted: August 10, 2023
Publication Date: November 4, 2023

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.


Download Citation: ||https://doi.org/10.6180/jase.202407_27(7).0006  


The global energy issue and lack of fossil fuels are obviously difficult concerns, prompting experts to look for other solutions. In this paper, the day-ahead operation of the multi-carrier energy system (MCE) to minimize operational costs, emission polluting and maximizing consumers’ comfort is presented. The optimal energy scheduling of consumption by energy demand curtailment strategy (EDCS) in the peak demand of electrical energy is proposed. Also, the operation of the energy storage via an onsite generation strategy (OGS) for consumers is considered by energy storage systems. The EDCS and OGS are modelled based on Demandside Management (DSM). The fuzzy method is taken into account as an optimization approach and objective functions. Finally, two scenarios using numerical simulation are studied to demonstrate the effectiveness of the approach for energy optimization in MCE. The results of the scenarios are studied based on non-participation and participation of the consumers in the scenarios A and B, respectively. The objective functions such as operation costs and emission polluting in scenario B are minimized by 1.63% and 5.35% than scenario A.


Keywords: Multi-carrier energy system (MCE); Energy demand curtailment strategy (EDCS); onsite generation strategy (OGS); Demand-side Management (DSM); fuzzy method


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