A static robust energy management approach for modelling low emission multi-vectored energy hub including emission markets and power-to-gas units

Tiwari, S., Singh, J.G., & Garg, A. (2024). A static robust energy management approach for modelling low emission multi-vectored energy hub including emission markets and power-to-gas units. Energy 294 e130827. 10.1016/j.energy.2024.130827.

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Abstract

This paper develops a robust and sustainable energy management framework to model a multi-vectored energy hub (MVEH) system. A max-min-based static robust optimization model is developed to counter the uncertainties. Furthermore, a flexible energy demand management program, battery electric vehicles (BEVs), and compressed air battery storage (CABS) are integrated to enhance MVEH's flexibility. Hybrid power-to-X units (electrolyser, methanization reactor and fuel cells) are modelled to reduce green energy spillage and improve operational independence, including heat pumps. Moreover, the emission (carbon cap and trade) market along with carbon capture storage and utilization units (CCS–U), are incorporated to establish a low-emission multi-energy model. Simulation results demonstrate that with flexible resources and power-to-X units, MVEH reduces the operating energy cost by 46.4 % and improves the system independence by 19.06 %. Besides, CCS-U units produce 92 % less emission while increasing the energy cost by 5.1 %. However, MVEH gains the right to sell carbon credits under the emission market. Thus, the multi-vectored system's economical, reliable, and environmental viability are ensured. Finally, sensitivity analysis proves the robustness of the proposed framework against natural gas and carbon price fluctuations.

Item Type: Article
Research Programs: Biodiversity and Natural Resources (BNR)
Biodiversity and Natural Resources (BNR) > Agriculture, Forestry, and Ecosystem Services (AFE)
Depositing User: Michaela Rossini
Date Deposited: 28 Mar 2024 11:05
Last Modified: 28 Mar 2024 11:05
URI: https://pure.iiasa.ac.at/19582

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