E3S Web Conf.
Volume 238, 2021100RES 2020 – Applied Energy Symposium (ICAE), 100% RENEWABLE: Strategies, Technologies and Challenges for a Fossil Free Future
|Number of page(s)||6|
|Published online||16 February 2021|
Design of a multi-energy system under different hydrogen deployment scenarios
University of Rome Tor Vergata, Department of Industrial Engineering, via del Politecnico 1, 00133, Rome, Italy
* Corresponding author: firstname.lastname@example.org
Multi Energy Systems (MES) are effective means to increase Renewable Energy Sources (RES) penetration in the energy system and therefore to move toward a decentralized low-carbon system. Several energy vectors can be integrated together to exploit synergies in a MES framework, such as electricity, heat and hydrogen. The latter is one of the most promising energy carriers to promote widespread use of MES. Predictive management and well-defined sizing methodology are mandatory to achieve maximum performance out of MES. In this study a grid-connected MES consisting of a photovoltaic (PV) plant, a Battery Energy Storage System (BESS) and a Proton Exchange Membrane Fuel Cell (PEMFC) as a programmable Combined Cooling Heat and Power (CCHP) source, is modelled. Natural gas is considered as an alternative fuel to pure hydrogen. Mixed Integer Linear Programming and Genetic Algorithm are used respectively to solve operation and sizing problems. A single-objective optimization approach, including emission factors as optimization constraints, is carried out to find the optimal configuration of the MES. Several future scenarios are studied, considering different percentages of hydrogen in the gas mixture and comparing the techno-economic performance of the system with respect to a pure hydrogen fueling scenario. Results showed that the environmental objective within the design optimization, promote the use of hydrogen, especially in scenarios with high share of green hydrogen.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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