Abstract
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.
Highlights
Urban areas are high density centres of energy demand and are responsible for a large share of carbon emissions
The follower problem, that consists in the dispatch optimization, is formulated with a Mixed Integer Linear Programming (MILP) algorithm that minimizes the operational costs of the Multi Energy Systems (MES), based on the leader problem sizes result
The percentage of hydrogen present in the fuel before treatment is expressed through the Hydrogen Fuel Ratio (HFR) and the emission factor of the hydrogen fraction contained in the fuel is assumed to be 2.2 kgCO2/kgH2, equal to the 50% of the limit imposed by the certification of hydrogen CertifHy [12, 22]
Summary
Urban areas are high density centres of energy demand and are responsible for a large share of carbon emissions. It is worth noting that the economic objective is the most common in the design optimization, looking for a configuration of the energy system to minimize costs [4] Such an approach can be too much conservative, avoiding components not yet economically competitive with the electric grid, gas grid or in general with technologies with a high Technology Readiness Level (TRL). The hydrogen produced by electrolysis is a low carbon alternative for the supply of this fuel and its production is expected to be growing rapidly [12] In this context, hydrogen represents a fundamental energy vector, to be integrated into the MES, for a low-carbon future for urban areas. The follower problem, that consists in the dispatch optimization, is formulated with a MILP algorithm that minimizes the operational costs of the MES, based on the leader problem sizes result. The main novelty of this work is the development of a design methodology of an urban trigenerative MES that includes hydrogen market development and green hydrogen [12] deployment scenarios in the optimization process
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