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Biomass is an abundant renewable energy resource that can be converted into carbon-based biofuels. Pyrolysis is a thermochemical process that allows the rapid conversion of residual biomass and biowaste into bio-oil, a liquid biofuel with a high energy density. Hydrodeoxygenation (HDO) is a catalytic process in which typically high-pressure hydrogen is used to remove oxygen mainly through dehydration, decarboxylation and decarbonylation reactions from the oxygenated compounds of bio-oil. The objective of this work is to evaluate the process of hydrodeoxygenation under mild conditions, i.e. atmospheric pressure, quantifying the hydrogen consumption and the degree of deoxygenation. The organic fraction of the pyrolysis oil of spent coffee grounds has been processed in a packed-bed reactor in a semi-continuous regime. The performance of two different MoO3/NiO alumina-supported catalysts were evaluated at 350°C and LHSV of 0.5. The results showed a high upgraded oil yield (72-87 w/w %), limited gas production (up to 1 w/w%) and a limited coking (12-26 % w/w). GC-MS analysis of upgraded oil showed a significant reduction of hydrocarbons molecular weight, as well as caffeine, fatty acids and furans relative concentration, while pyridines, phenolics and ketones were still very abundant. The measured hydrogen consumption was very limited (up to 1g/L bio-oil), suggesting that increasing pressure would be beneficial for higher degree of deoxygenation. [ABSTRACT FROM AUTHOR]

The transport sector is today a major source of pollutant and greenhouse gas emissions. Fuel Cell Hybrid Electric Vehicles are a solution to reduce its environmental impact, thanks to the zero pollutant tailpipe emissions and longer driving ranges if compared with full electric vehicles. A Digital Twin of a FCHEV is developed in this study, through the assessment of models of mechanical and thermal systems within the vehicle. The Simulink/Simscape model here presented is able to support both the design choices and the test of control strategies. The results obtained allow characterizing the impact of the auxiliary systems on the driving range, whose relative value ranges from 28% to 40% of the overall energy demand depending on the ambient temperature, and the range is between 430 km and 356 km respectively for mild and cold temperature.

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.