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The yeast Yarrowia lipolytica is an industrially relevant microorganism, which is able to convert low-value wastes into different high-value, bio-based products, such as enzymes, lipids, and other important metabolites. Waste cooking oil (WCO) represents one of the main streams generated in the food supply chain, especially from the domestic sector. The need to avoid its incorrect disposal makes this waste a resource for developing bioprocesses in the perspective of a circular bioeconomy. To this end, the strain Y. lipolytica W29 was used as a platform for the simultaneous production of intracellular lipids and extracellular lipases. Three different minimal media conditions with different pH controls were utilized in a small-scale (50 mL final volume) screening strategy, and the best condition was tested for an up-scaling procedure in higher volumes (800 mL) by selecting the best-performing possibility. The tested media were constituted by YNB media with high nitrogen restriction (1 g L−1 (NH4)2SO4) and different carbon sources (3% w v−1 glucose and 10% v v−1 WCO) with different levels of pH controls. Lipase production and SCO content were analyzed. A direct correlation was found between decreasing FFA availability in the media and increasing SCO levels and lipase activity. The simultaneous production of extracellular lipase (1.164 ± 0.025 U mL−1) and intracellular single-cell oil accumulation by Y. lipolytica W29 growing on WCO demonstrates the potential and the industrial relevance of this biorefinery model.

We develop a semi-analytical model for polarization curve of a polymer electrolyte membrane (PEM) fuel cell with distributed (aged) along the oxygen channel MEA transport and kinetic parameters of the membrane–electrode assembly (MEA). We show that the curve corresponding to varying along the channel parameter, in general, does not reduce to the curve for a certain constant value of this parameter. A possibility to determine the shape of the deteriorated MEA parameter along the oxygen channel by fitting the model equation to the cell polarization data is demonstrated.

This paper presents a novel control system for the participation of plug-in electric vehicles (PEVs) in the provisioning of ancillary services for frequency regulation, in a way that is transparent to the driver and harmonized with the smart charging service requirements. Given a power-frequency droop curve, which specifies how the set of PEVs collectively participate to the provisioning of the frequency regulation service (we call this curve a “global” droop curve), we propose an algorithm to compute “local” droop curves (one for each PEV), which are optimized according to the current status of the PEV and the current progress of the smart recharging session. Once aggregated, the local droop curves match the global one (so that the PEVs contribute as expected to the provisioning of the ancillary service). One innovative aspect of the proposed algorithm is that it is specifically designed to be interoperable with the algorithms that control the PEV recharging process; hence, it is transparent to the PEV drivers. Simulation results are presented to validate the proposed solution.

The growing concern about climate change and the contemporary increase in mobility requirements call for faster, cheaper, safer, and cleaner means of transportation. The retrofitting of fossil-fueled piston engine ultralight aerial vehicles to hydrogen power systems is an option recently proposed in this direction. The goal of this investigation is a comparative analysis of the environmental impact of conventional and hydrogen-based propulsive systems. As a case study, a hybrid electric configuration consisting of a fuel cell with a nominal power of about 30 kW, a 6 kWh LFP battery, and a pressurized hydrogen vessel is proposed to replace a piston prop configuration for an ultralight aerial vehicle. Both power systems are modeled with a backward approach that allows the efficiency of the main components to be evaluated based on the load and altitude at every moment of the flight with a time step of 1 s. A typical 90 min flight mission is considered for the comparative analysis, which is performed in terms of direct and indirect emissions of carbon dioxide, water, and pollutant substances. For the hydrogen-based configuration, two possible strategies are adopted for the use of the battery: charge sustaining and charge depleting. Moreover, the effect of the altitude on the parasitic power of the fuel cell compressor and, consequently, on the net efficiency of the fuel cell system is taken into account. The results showed that even if the use of hydrogen confines the direct environmental impact to the emission of water (in a similar quantity to the fossil fuel case), the indirect emissions associated with the production, transportation, and delivery of hydrogen and electricity compromise the desired achievement of pollutant-free propulsion in terms of equivalent emissions of CO2 and VOCs if hydrogen is obtained from natural gas reforming. However, in the case of green hydrogen from electrolysis with wind energy, the total (direct and indirect) emissions of CO2 can be reduced up to 1/5 of the fossil fuel case. The proposed configuration has the additional advantage of eliminating the problem of lead, which is used as an additive in the AVGAS 100LL.

The management of the distribution network is becoming increasingly important as the penetration of distributed energy resources is increasing. Reliable knowledge of the real-time status of the network is essential if algorithms are to be used to help distribution system operators define network configurations. State Estimation (SE) algorithms are capable of producing such an accurate snapshot of the network state but, in turn, require a wide range of information, e.g., network topology, real-time measurement and power profiles from customers/productions. Those profiles which may, in principle, be provided by smart meters are not always available due to technical limitations of existing Advanced Metering Infrastructure (AMI) in terms of communication, storage and computing power. That means that power profiles are only available for a subset of customers. The paper proposes an approach that can overcome these limitations: the remaining profiles, required by SE algorithms, are generated on the basis of customer-related information, identifying clusters of customers with similar features, such as the same contract and pattern of energy consumption. For each cluster, a power profile estimator is generated using long-term power profiles of a limited sub-set of customers, randomly selected from the cluster itself. The synthesized full power profile, representing each customer of the distribution network, is then obtained by scaling the power profile estimator of the cluster to which the customer belongs, by the monthly energy exchanged by that customer, data that are easily available. The feasibility of the proposed approach was validated considering the distribution grid of Unareti SpA, an Italian Distribution System Operator (DSO), operating in northern Italy and serving approximately one million customers. The application of the proposed approach to the actual infrastructure shows some limitations in terms of the accuracy of the estimation of the power profile of the customer. In particular, the proposed methodology is not fully able to properly represent clusters composed of customers with a large variability in terms of power exchange with the distribution network. In any case, the root mean square error of the synthesized full power profile with the respect to validation power profiles belonging to the same cluster is, in the worst case, on the order of 6.3%, while in the rest of cases is well below 5%. Thus, the proposed approach represents a good compromise between accuracy in representing the behavior of customers on the network and resources (in terms of computational power, data storage and communication resources) to achieve that results.

The construction sector is among the major players responsible for global energy consumption and therefore related emissions, both because of the constantly increasing indoor air quality standard which requires increasingly higher energy demands as well as the great share of historical buildings which are now obsolete and are not up to date with current regulations. Phase change materials (PCMs) applied on the building envelope represent a feasible possibility to improve the performance of existing buildings, also the historical ones, increasing their thermal inertia without violating any legal restriction or causing further alterations to the structure. More specifically, focus of this research was on the addition of a granular paraffin PCM into a lime-based plaster. Experimental tests at lab scale and numerical simulations with COMSOL Multiphysics were carried out to characterize the plasters realized, namely one reference lime-based plaster and one with incorporated 10% by mass of granular PCM (named REFp and PCMp, respectively). The behavior of these plasters applied on the exterior side of a wall was then simulated and compared in terms of temperatures and heat fluxes. However, considering that the estimated thermal conductivity of the reference lime-based plaster was lower than the values found in literature, the simulations were carried out considering an additional plaster, namely a lime-based plaster (renamed LITp), whose properties were found in literature and considered quite representative of a consistent share of existing historical buildings. Great improvements were observed from the application of PCM into the plaster, with reductions of the incoming energy between 9% and 18%.

Before the COVID-19 pandemic, ventilation in buildings was not always given its due importance. The World Health Organization has highlighted the important role of air exchange with the outdoors in improving the air quality in buildings; buildings should, therefore, be equipped with mechanical ventilation or adequate air conditioning systems. This paper aims to investigate different retrofit solutions for air conditioning, evaluating them in terms of energy consumption and cost and the impact of increased outdoor air exchange rates on countering the propagation of COVID-19; the latter is the main novelty of the paper. As a case study, we take an existing office building located in Central Italy that was previously not equipped with a mechanical ventilation system (a system with primary air was introduced during the study). The energy analysis was conducted using dynamic simulation software after validation through energy bills; energy and economic analyses were conducted considering different external-air exchange rates. An optimal number of outdoor air changes was found to mitigate the risk of COVID-19 infection, a finding in line with the international literature. The increase in air changes with outdoor air leads to a rise in energy consumption and costs. These values were evaluated for different air conditioning systems and operational schedules. These drawbacks can be made less significant by combining interventions in the system with energy-efficiency measures applied to the building envelope.

The diffusion of electric vehicles (EVs) can be sustained by the presence of integrated solutions offering parking and clean power supply. The recourse to DC systems allows better integration of EV bidirectional energy exchange, photovoltaic panels, and energy storage. In this paper, a methodology for optimal techno-economic sizing of a DC-microgrid for covering EV mobility needs is carried out. It is based on the definition of different scenarios of operation, according to typical EV usage outlooks and environmental conditions. In each scenario, optimal operation is carried out by means of a specific approach for EV commitment on different stations. The sizing procedure is able to handle the modular structure of microgrid devices. The proposed approach is applied to a case study of an envisaged EV service fleet for the Bari port authority.