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Abstract As main contributors to greenhouse gas emissions, power and transportation are crucial sectors for energy system decarbonization. Their interaction is expected to increase significantly: plug-in electric vehicles add a new electric load, increasing grid demand and potentially requiring substantial grid upgrade; hydrogen production for fuel cell electric vehicles or for clean fuels synthesis could exploit the projected massive power overgeneration by intermittent and seasonally-dependent renewable sources via Power-to-Hydrogen. This work investigates the infrastructural needs involved with a broad diffusion of clean mobility, adopting a sector integration perspective at the national scale. The analysis combines a multi-node energy system balance simulation and a techno-economic assessment of the infrastructure to deliver energy vectors for mobility. The article explores the long-term case of Italy, considering a massive increase of renewable power generation capacity and investigating different mobility scenarios, where low-emission vehicles account for 50% of the stock. First, the model solves the energy balances, integrating the consumption related to mobility energy vectors and taking into account power grid constraints. Then, an optimal infrastructure is identified, composed of both a hydrogen delivery network and a widespread installation of charging points. Results show that the infrastructural requirements bring about investment costs in the range of 43–63 G€. Lower specific costs are associated with the exclusive presence of FCEVs, whereas the full reliance on BEVs leads to the most significant costs. Scenarios that combine FCEVs and BEVs lie in between, suggesting that the overall power + mobility system benefits from the presence of both drivetrain options.

Thermo-economically optimal design = optimal molecule + optimal process + optimal equipment.

This paper presents a stochastic bi-level approach for tariff design in the electricity market where the leader is represented by a retailer and the follower by a residential prosumager, i.e. a consumer equipped with an energy system consisting of photovoltaic panels and a battery storage device. Both players solve an optimization problem subject to uncertainty in market prices, weather-related variables and electricity demand. To account for the retailer’s attitude towards risk, the upper level problem includes a safety measure to maximize. The model allows to determine a dynamic pricing scheme with time-variant rates delivering the average profit that can be gained in a given percentage of unfavorable realizations of the uncertain parameters and the optimal load pattern that minimizes the expected prosumager's electricity bill. The stochastic bi-level problem is reformulated as a single level model and different approaches to deal with the lower level problem and the non linearity in the objective function are analyzed and empirically investigated. A large number of numerical experiments have been carried out on real test cases. The results have shown the efficacy of the proposed approach as a tool to define pricing schemes that reflect the retailer's risk attitude underlining the importance of explicitly dealing with uncertainty.

National net zero emission targets could, if fully implemented, reduce best estimates of projected global average temperature increase to 2.0–2.4 °C by 2100, bringing the Paris Agreement temperature goal within reach. A total of 131 countries are discussing, have announced or have adopted net zero targets, covering 72% of global emissions. These targets could substantially lower projected warming as compared to currently implemented policies (2.9–3.2 °C) or pledges submitted to the Paris Agreement (2.4–2.9 °C). Current pledges for emissions cuts are insufficient to meet the Paris Agreement temperature goal. The wave of net zero targets being discussed and adopted could make the Paris goal possible if further countries follow suit.

Industrial heat and cooling applications are an essential fraction of the overall energy demand, mainly produced by fossil fuels. Solar thermal energy production can satisfy such a need by adopting the High Vacuum Flat Plate Collectors (HVFPCs) and increasing their efficiency. The absorptance and emittance of Selective Solar Absorbers (SSAs) determine the thermal efficiency of HVFPCs. Being the absorptance already maximized, the thermal emittance of the absorber should be minimized to increase further the operating temperature of the collector and its efficiency. This research aims to reduce the thermal emittance of commercially available Selective Solar Absorber by depositing a thin silver film on the aluminium substrate. So, in this work, the thermal stability of a silver coating has been investigated, and a diffusion barrier layer has been adopted to stabilize the coating performance up to 360 degrees C. The low-emissive layer of Ag and a diffusion barrier of CrOx guarantees a decrease of 11% in thermal emittance at 200 degrees C of commercially available SSA deposited on aluminium. Further emittance reduction can be obtained by depositing a thin Ag film on both sides of the aluminium substrate before the SSA deposition, proving to be a promising way to enhance the efficiency of HVFPCs.

Studying the thermal performance of Double Skin Facades (DSFs) with vertical layers has dominated the literature,however, there is still a lack of in-depth research on the performance of DSFs with atypical geometries suchas folded cases which can be applied to Building Integrated Photovoltaic (BIPV) systems to improve their performance.To this end, the study evaluates the influence of the fold geometry on heat transfer, flow structure, andairflow rate in the Folded DSF cavities under a hot climate in Iran using an efficient method titled “patching”; themethod integrates Soltrace3 with a 2D steady-state CFD model by ANSYS-Fluent. The results show that the foldposition and its depth can alter the DSFs performance significantly; the higher the fold depth the more distortionof the flow field inside the cavity; from a practical perspective, the fold position in the upper part of the cavity issuitable for BIPVs application since it can capture 250% higher amount of solar radiation compared to a conventionalvertical-layer DSF as the Base Case; the net heat gain through outer layer could improve with increaseof fold depth and reach at least 33% higher than the Base Case, meanwhile, the total electricity generationpotential of folded cases could be up to 169% higher than the Base Case; thus, the study proved that if thearchitectural design is of interest, it is highly recommended to consider folded DSFs as a design option.

Abstract The analysis of a large amount of data on the failures of absorption refrigeration machines of the ammonia-water type was carried out. The data derive from the records of a 10-year maintenance contract under which every machine was installed. The records were computerized for the period 1989–1992, and they refer to sales starting from 1980 (i.e. to 73 778 machines). The failures are classified, identifying the most serious (generator and solution pump). The rate of early failures is rather high, but the failures are generally minor and easily repaired. The production quality was not constant, with a very bad year in 1984. The failure rate is evaluated for the first 10 years of life of the equipment. In general terms, one machine in two does not require any intervention during that period.

Abstract While the employment of Exhaust Gas Recirculation (EGR) is a well-established technique in Internal Combustion Engines to limit NOx emissions, its adoption in Gas Turbine engines hasn’t yet found a practical application due to its expensive and complex installation that doesn’t justify the emissions reduction when compared to already established DLN combustion technologies. EGR becomes an interesting option in GT engines considering the possibility of increasing the CO2 content of the exhaust gases to improve the efficiency of Carbon Capture and Storage (CCS) units. However, the decrease in oxygen content of the combustion air is extremely challenging in terms of combustion stability and therefore of engine operability. In the present work, a low NOx burner was studied at ambient pressure in a reactive single burner test rig. The burner was fed with methane and characterised in terms of emissions and stability limits at different operating conditions. In addition, the flame position and shape were studied through OH* chemiluminescence imaging together with the flow field thanks to PIV measurements. The effects of CO2 addition on the flame were then investigated at different EGR increasing levels, highlighting the impact of the oxygen content on the combustion reaction intensity. Variations in emissions and burner stability limits in terms of maximum sustainable CO2 content were also studied, to detail the burner operating window. Data have been thoroughly analysed to gather information on the burner behaviour to support the design of new technical solutions capable of ensuring both proper flame stability and low CO and NOx emissions.

Power-to-methane (PtM) is a prospective solution to the mismatching between the supply and consumption of renewable energy resources (RES) by converting renewable power into methane. However, the continuous fluctuation of RES causes the PtM system to deviate from the design condition in the vast majority of cases, and thus it is significantly vital to study the operating characteristics of the PtM system under off-design conditions. This paper proposes a comprehensive investigation framework from design to off-design steps for the performance improvement of a PtM system combining solid oxide electrolysis cell with methanation reactor, and solar energy is selected as renewable energy input. Firstly, the system with the total exergy efficiency (ηEX,tot) of 11.83% and levelized cost of exergy (LCOE) of 150.76 $/MWh is selected as the optimal design condition based on the homogeneous assessment from both thermodynamic and economic aspects, by means of Non-dominated sorting genetic algorithm-II. Then, based on the optimal design point, the off-design performances are quantitatively investigated under varying solar radiation and key operating parameters, in terms of synthetic natural gas (SNG) yield and ηEX,tot. The results indicate that with the increment in solar radiation, the SNG yield rises, while the ηEX,tot increases first and then decreases. Finally, the multi-objective optimization based on the Artificial Neural Network models is implemented for the system under off-design conditions to acquire the best trade-off between hourly SNG yield and ηEX,tot. The off-design optimization solutions reveal that the hourly optimal SNG yield is located in the range of 275.06–946.53 kW, achieving a total annual SNG yield of 1697 MWh/y, and the hourly optimal ηEX,tot mainly varies in the range of 10.40–11.40%.

This paper proposes a technique for the probabilistic wind power forecasting (WPF) of a newly built wind farm (NWF) using a limited amount of historical data. First, the state-of-the-art Transformer network is employed to capture the power generation pattern of different wind farms (WFs) based on abundant historical training samples. Then, the Bayesian averaging regression method is applied to transfer the learned power generation pattern to the NWF by assigning proper weights to the WPF results of different WFs. This enables the proposed method to yield accurate NWF power predictions utilizing a limited amount of historical data. The Bayesian characteristics further enable the quantification of multiple uncertainties in forecasting results that may be essential for the NWF operator when the input is uncertain. Comprehensive tests were also performed by employing other deterministic and probabilistic WPF methods using field data. By comparing the results, the proposed method is demonstrated to produce accurate forecasting results with sparse historical data. Moreover, the uncertainties of outcomes are quantified, and acceptable performance is achieved.