Effect of power-to-gas technology in energy hub optimal operation and gas network congestion reduction
Salehi, Javad; Namvar, Amin; Samadi Gazijahani, Farhad; Shafie-khah, Miadreza; Catalao, Joao P.S. (2022-02-01)
Salehi, Javad
Namvar, Amin
Samadi Gazijahani, Farhad
Shafie-khah, Miadreza
Catalao, Joao P.S.
Elsevier
01.02.2022
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2023030629990
https://urn.fi/URN:NBN:fi-fe2023030629990
Kuvaus
vertaisarvioitu
©2022 Elsevier. This manuscript version is made available under the Creative Commons Attribution–NonCommercial–NoDerivatives 4.0 International (CC BY–NC–ND 4.0) license, https://creativecommons.org/licenses/by-nc-nd/4.0/
©2022 Elsevier. This manuscript version is made available under the Creative Commons Attribution–NonCommercial–NoDerivatives 4.0 International (CC BY–NC–ND 4.0) license, https://creativecommons.org/licenses/by-nc-nd/4.0/
Tiivistelmä
Natural gas will play a key role in the transition to a lower-carbon economy, constituting a natural alternative to coal and acting as a backup resource to the intermittent nature of renewable generation. These energy carriers can be structurally linked together by Power-to-X technologies because of their interaction to increase energy efficiency. For this purpose, this paper proposes an innovative model to optimally manage the electricity and natural gas grids in a cost-efficient manner. In this model, an energy hub has water, electricity, and gas oil as inputs, supplying electric and thermal loads. Besides, the energy hub uses the Power-to-gas (P2G) technology to produce natural gas, selling it to a gas network to reduce the congestion in gas pipelines and the energy hub owner's costs. A demand response program has been also applied in this model to shift the loads from on-peak times to off-peak ones. Various technologies such as energy storage and distributed generation have been used in the modeling to reach the goals targeted by operators. Furthermore, a scenario generation method has been applied to model the uncertainty of wind turbine output. The proposed problem has been finally formulated as mixed-integer linear programming that has been solved under GAMS software by using CPLEX solver to reach the global optimality. The results obtained from simulations demonstrate that the proposed model can significantly reduce the operation cost, while properly alleviating gas network congestion.
Kokoelmat
- Artikkelit [2922]