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The potential role of hydrogen as a tool for the decarbonization of the energy sector is widely recognized. In this paper, a comprehensive analysis of the marginal utility of increasing the hydrogen penetration on the energy and environmental performances of a multi-energy system is developed to assess its potential. A distributed energy system satisfying the energy requirements for an existing building is chosen as test case, assumed as representative of a wide set of applications. Starting from real energy consumption profiles, representative scenarios and optimized design configurations are defined using a methodology that takes into account uncertainties both in demand and renewable production profiles and in techno-economic parameters assumptions. For each multi energy system configuration, an optimal dispatch control strategy is achieved through a mixed-integer linear programming method to maximize the building self-independence from the grid. Results show how an increase of hydrogen technologies penetration allows a reduction of the specific carbon footprint of the system down to 100 grCO2/kWh while increasing the system resilience up to 85%. Detailed information about the marginal effect of H2 technologies on resilience, carbon footprint, and fossil energy savings are presented and can be used for extensions to similar applications.

The previous works on the use of PEM Fuel Cell based power supply system for the operation of off-grid RBS (Radio Base Stations) sites showed a strong influence of system design parameters on the energy conversion performance. In this paper a perturbation of system design is performed through validated models to understand better the variability of performance over a full year operation. Results show that a ratio of energy produced by fossil over energy produced by renewables sources of 0.2 can be reached slightly increasing the photovoltaic plant size without affecting drastically the renewable exploitation. Moreover a positive Net Present Value can be achieved in comparison with the traditional diesel genset solution (from 260k€ to 350k€). The NPV value increases with the PV size and with a reduction of the battery size that leads to a steep reduction in the RES exploitation. Therefore, an optimum has to be sought as a compromise between the two aspects.

Electrification of the transport sector and massive installation of renewables are seen as two cornerstones for achieving a carbon neutral energy system. Nevertheless, uncontrolled electric vehicle charge combined with fluctuating energy production could induce power quality issues and system inefficiencies, causing an opposite outcome. Thus, in order to make sure that the energy system could benefit from electric mobility and renewable energy sources installation, proper design and control strategy of the charging stations is crucial. The aim of this study is to implement an optimal design methodology for an Electric Vehicle charging station located at a workplace. PV peak power, Electric Energy Storage capacity with retired Electric Vehicle batteries and number of charging columns to install are optimally defined targeting the carbon neutrality of the charging station operation. Two different charging strategy are implemented and compared to quantify the influence of the control approach on the final optimal charging station configuration. Moreover, energy demand and production uncertainties are taken into account in the production of the input data. The obtained results suggest that an optimal control strategy allows to have always a greater emission reduction and to downsize the PV and Electric Energy Storage capacity needed to achieve the carbon neutrality of the EV charging process.

Dual-fuel diesel–methane low-temperature combustion (LTC) has been investigated by various research groups, showing high potential for emissions reduction (especially oxides of nitrogen oxide (NOx) and particulate matter (PM)) without adversely affecting fuel conversion efficiency in comparison with conventional diesel combustion. However, when operated at low load conditions, dual-fuel LTC typically exhibits poor combustion efficiencies. This behavior is mainly due to low bulk gas temperatures under lean conditions, resulting in unacceptably high carbon monoxide (CO) and unburned hydrocarbon (UHC) emissions. A feasible and rather innovative solution may be to split the pilot injection of liquid fuel into two injection pulses, with the second pilot injection supporting CO and UHC oxidation once combustion is initiated by the first one. In this study, diesel–methane dual-fuel LTC is investigated numerically in a single-cylinder heavy-duty engine operating at 5 bar brake mean effective pressure (BMEP) at 85% and 75% percentage of energy substitution (PES) by methane (taken as a natural gas (NG) surrogate). A multidimensional model is first validated in comparison with the experimental data obtained on the same single-cylinder engine for early single pilot diesel injection at 310 crank angle degrees (CAD) and 500 bar rail pressure. With the single pilot injection case as baseline, the effects of multiple pilot injections and different rail pressures on combustion and emissions are investigated, again showing good agreement with the experimental data. Apparent heat release rate and cylinder pressure histories as well as combustion efficiency trends are correctly captured by the numerical model. Results prove that higher rail pressures yield reductions of HC and CO by 90% and 75%, respectively, at the expense of NOx emissions, which increase by ∼30% from baseline still remaining at very low level (under 1 g/kWh). Furthermore, it is shown that postinjection during the expansion stroke does not support the stable development of the combustion front as the combustion process is confined close to the diesel spray core.

This study proposes a methodology for sizing and operating new flexibility options within a German carpentry, targeting to be operated as Net Zero Energy Factory (NZEF). A key element of this system is the maximization of the integration of the electric power locally generated by a photovoltaic plant and the electric demand for driving the manufacturing processes. This aim is achieved with a proper integration between design choices in terms flexibility options and optimal control of energy fluxes. In this work, benefits and criticalities arising from the integration of different flexibility options, such as stationary and mobile Energy Storage Systems, are identified and analyzed. A double step optimization process is implemented. First, a Model Predictive Control strategy is used to schedule the manufacturing machines and the energy storage systems (stationary and mobile). Then, a multi-objective optimization aiming at the minimization of annual energy grid exchange and the optimal exploitation of battery capacity is carried out with the Genetic Algorithm. Such a methodology allows the factory operators to optimally size the flexibility capacity (the battery energy storage in this application) needed to operate their industrial facility as a net-zero energy factory. Results show that an optimally controlled stationary energy storage system allows a reduction of energy exchange with the grid up to 53%. The further introduction of electric vehicles increases of about 5% and 67% the renewable energy self-consumption and carbon emissions savings, respectively, ensuring also a significant increase in the yearly annual savings (up to 406%).

Nowadays several companies are taking into consideration the possibility to electrify their vehicles' fleet. Users have to deal with the problem of choosing a model of Electric Vehicle and properly sizing a Charging Station in such a way that the investment costs are minimized, and the logistic constraints respected. From the grid side, the growing energy demand caused by the electrification of the transport sector is introducing grid instabilities and Distributed System Operators have to ensure the service reliability, keeping operating costs down. This work shows how the optimal allocation and control of the Electric Vehicle charging allow to both minimize the user investment costs and avoid grid congestions during peak periods at the same time. Two different charging scheduling strategies, namely a standard and an optimal control strategy, are proposed considering different Charging Station configurations (single level and multi-level type). The possible layouts are then analyzed and compared from the user and the Distribution System Operator point of view. The obtained results suggest that a multi-level Charging Station configuration integrated with an optimal control strategy leads to a reduction of around 46% of the investment costs and for the power profile a decrease of 44%, 11% and 31% of standard deviation, mean and maximum value, respectively.

Multi energy systems are effective means to move toward a decentralized low-carbon system. Several energy vectors can be integrated together according to a multi energy system framework, such as electricity, heat, and hydrogen, being the latter one of the most promising energy carriers to support widespread use of such energy systems for a number of applications. In this paper, a methodology to optimally design a multi energy system is applied to different future low-carbon scenarios. A wide range of technologies is studied, including trigenerative components such as a gas microturbine, a Solide Oxide Fuel Cell, and a Proton Exchange Membrane Fuel Cell. Several scenarios are analyzed accounting for environmental and technical targets and considering the variability of costs of hydrogen technologies. Results highlight that building-scale configurations that allow simultaneous environmental and economic benefits consider different storage technologies and a trigeneration plant based on Solide Oxide Fuel Cells. The integration of hydrogen technologies and storage systems are thus effective solutions to access further reduction in terms of both primary energy consumption and carbon dioxide emissions. The availability of green hydrogen, considering future cost projections, allows achieving the lowest carbon footprint at relatively low costs.

The integration of different conversion technologies can strongly contribute to the biomass potential exploitation. To this aim, the use of intermediate pyrolysis biochar is analyzed in this paper as an alternative co-substrate in anaerobic digestion. The specie Ampelodesmos mauritanicus has been specifically chosen in this case for its capacity to tolerate, accumulate and, in some cases, degrade organic and inorganic pollutants. The biochar, produced under intermediate pyrolysis conditions at 450 °C, 500 °C and 550 °C, has been here considered for a biomethane potential assessment. The intermediate pyrolysis process improves the herbaceous bioavailability and promotes the microbial activity by reducing the digestion lag phase. Three reactors, namely B450, B500 and B550, have been considered in this study. Acclimatized cow manure from food wastes digestion has been used as inoculum with 5 g of biochar. The reactors have been continuously monitored for 15 days keeping the temperature fixed at 37 °C. Excluding the inoculum contribution, an accumulated methane production of 465–540.4 ml CH4/g-VS has been measured with an LHV evaluated in the range 25.8–26.9 MJ/kg. The modified Gompertz equation has been then used to describe the influence of biochar production temperature on methane conversion. A lag phase of 1.8, 2.2 and 3.8 days respectively for B450, B500 and B550, has been estimated showing an inverse proportionality to the biochar production temperature. The biomass to biogas energy conversion analysis reveals a reduction in the efficiency with the biochar production temperature increase. This fact is attributed to the steep reduction in volatile solids occurring by increasing the pyrolysis process severity. As a whole, the paper present a novel approach to possibly combine phytoremediation and production of renewable energy by using Ampelodesmos mauritanicus.

Dual-fuel combustion mode in compression ignition engines has been tested thoroughly, showing high potential for the reduction of emissions (especially nitric oxides and particulate matter) while keeping unchanged the fuel conversion efficiency compared with conventional Diesel engines. Controlling the reactivity of the secondary fuel is crucial for this kind of application. To this aim, a combined experimental/numerical approach is proposed in this study to provide, on one side, experimental data in controlled conditions for the calibration of the numerical models; on the other side, a numerical framework for the accurate simulation of the dual-fuel injection in engine-like operating conditions. More in detail, a constant-volume combustion vessel has been used to simulate and analyze the injection process varying the characteristic control parameters. Detailed high-resolution images of the injection and combustion processes were acquired for the validation of the numerical framework. Numerical simulations, carried out by means of the CONVERGE CFD code using a Reynolds Average Navier Stokes (RANS) approach allow for understanding the key differences between the nominal and off-design settings. Results have been compared with the experimental data in terms of liquid spray penetration. A comparison with high resolution images has also been done to prove the accuracy of the model to describe the spray evolution in terms of spray characteristics. In the provided picture, this contribution aims at demonstrating the robustness of the experimental/numerical framework that is essential for further development of such engine solution.

In the context of renewable sources exploitation, the thermochemical conversion of biomass may give a significant contribution to the flexible and programmable production of electric and thermal power. From this perspective, the biomass fast pyrolysis conversion process is more than a promising technology but only few models have been developed so far to describe the behavior of a screw reactor system. This paper is thus focused on numerical modeling of a shaftless screw fast pyrolyzer with special attention on the residence time distribution and the definition of the kinetic framework, as well as the heat and mass transfer phenomena representation. A steady-state model with constant wall temperature has been developed to generate temperature profile and conversion patterns along the reactor. Residence Time Distribution evaluation has been developed as well to take into account non-ideal mass conveying characteristics of the proposed reactor design. The reaction framework, considering the conductive, convective and radiative heat transfer mechanisms, is based on a 4 parallel Distributed Activation Energy Model. The structure includes the three major biomass pseudo-component occurring in the biomass thermal degradation, namely cellulose hemicellulose and lignin, together with the moisture evaporation process. The numerical results are compared with results collected experimentally from the fast pyrolysis of spent coffee grounds in a lab-scale screw reactor. Numerical temperature profiles for both the gas and solid phase are in good agreement with the experimental ones. The peak bio-oil production has been observed in the range of 500 °C. The results also show a strong dependence of results on wall temperature and gas-solid heating rate.

The implementation of the Distributed Generation (DG) concept requires to face with technical issues regarding integration and control of energy fluxes at the grid nodes. A predictive control strategy integrating renewable and non-renewable sources, as well as energy storage systems, is a potential solution to face with the aforementioned problems. The behavior of a smart building consisting of 30 apartments has been considered in this work. The Hybrid Renewable System (HRS) has been controlled by a Model Predictive Control (MPC) strategy. The HRS includes both sub-systems for the conversion of renewable energy sources and non-renewable ones, connected to the main grid. Several scenarios have been tested under different weather conditions and renewable sources penetration quotas. Results obtained with the MPC control strategy have been compared with a Rule Based Control (RBC) one, turning out that the use of MPC improves the integration of the residential microgrid with the renewable sources available at the grid thanks to the predictive system smoothing out the energy demand profile and absorbing the peak of production from the photovoltaic and wind farms, even in cases of high RES penetration.

This study reports the implications of using spent coffee hydrochar as substrate for anaerobic digestion (AD) processes. Three different spent coffee hydrochars produced at 180, 220 and 250 °C, 1 h residence time, were investigated for their biomethane potential in AD process inoculated with cow manure. Spent coffee hydrochars were characterized in terms of ultimate, proximate and higher heating value (HHV), and their theoretical bio-methane yield evaluated using Boyle-Buswell equation and compared to the experimental values. The results were then analyzed using the modified Gompertz equation to determine the main AD evolution parameters. Different hydrochar properties were related to AD process performances. AD of spent coffee hydrochars produced at 180 °C showed the highest biomethane production rate (46 mL CH4/gVS.d), a biomethane potential of 491 mL/gVS (AD lasting 25 days), and a biomethane gas daily composition of about 70%.

Purpose Thermochemical conversion processes are one of the possible solutions for the flexible production of electric and thermal power from biomass. The pyrolysis degradation process presents, among the others, the interesting features of biofuels and high energy density bio-oil production potential high conversion rate. In this paper, numerical results of a slow batch and continuous fast pyrolyzers, are presented, aiming at validating both a tridimensional computational fluid dynamics-discrete element method (CFD–DEM) and a monodimensional distributed activation energy model (DAEM) represents with data collected in dedicated experiments. The purpose of this paper is then to provide reliable models for industrial scale-up and direct design purposes. Design/methodology/approach The slow pyrolysis experimental system, a batch of small-scale constant-pressure bomb for allothermic conversion processes, is presented. A DEM numerical model has been implemented by means of a modified OpenFOAM solver. The fast pyrolysis experimental system and a lab scale screw reactor designed for biomass fast pyrolysis conversion are also presented along with a 1D numerical model to represent its operation. The model which is developed for continuous stationary feeding conditions and based on a four-parallel reaction chemical framework is presented in detail. Findings The slow pyrolysis numerical results are compared with experimental data in terms of both gaseous species production and reduction of the bed height showing good predictive capabilities. Fast pyrolysis numerical results have been compared to the experimental data obtained from the fast pyrolysis process of spruce wood pellet. The comparison shows that the chemical reaction modeling based on a Gaussian DAEM is capable of giving results in very good agreement with the bio-oil yield evaluated experimentally. Originality/value As general results of the proposed activities, a mixed experimental and numerical approach has demonstrated a very good potential in developing design tools for pyrolysis development.

The use of ultra-lean mixture natural gas fueled Internal Combustion Engines has been widely accepted to improve thermal efficiency and reduce exhaust emissions. This is mainly due to the intrinsic features of natural gas such as the wide availability and lower carbon content. Other advantages may occur running the engine under lean operating condition, as for example the lower flame temperature, the higher volumetric efficiency and compression ratios achievable, together with the opportunity of load control by varying the mixture equivalent ratio. Issues related to combustion stability and increase of CoV may however arise at leaner conditions. A comprehensive analysis of natural gas ultra-lean combustion process has been presented in this work using local charge stratification (Partially Stratified Charge combustion) to stabilize the process and limit the above-mentioned issues. A detailed analysis of the main sub-phases of the Partially Stratified Charge combustion process has been performed using a LES approach to highlight the main driving mechanisms of this combustion strategy. The accuracy of the numerical results has been evaluated by means of statistical and grid independence analysis. The effects of the local conditions around the spark plug on the propagation of the subsequent combustion event have demonstrated to play a key role on the efficiency of ignition and combustion sub-processes. A trade-off between the competing mechanisms of heat losses generated by heat convection of the gaseous jet and decay of the turbulent kinetic energy enhancing the process has been highlighted by the numerical results. Results show that a one-equation closure model is able to predict accurately the evolution of the injection process, providing a more reliable description of the local distribution of the fuel-oxidizer mixture and turbulent kinetic energy. Very good agreement between numerical results and experimental data has been obtained for the simulation of the combustion process. In particular, the numerical framework here proposed has been able to correctly capture two fundamental aspects of the PSC combustion, such as the interaction between the fuel jet and the flame evolution, which results in an elongated and strongly corrugated flame plumb, and the quenching due to the local high velocity field around the spark plug. These phenomena are crucial to control the combustion stability and the cycle-by-cycle variability in lean burn Internal Combustion Engines.

This paper is focused on the numerical analysis of a screw pyrolyzer with special attention on kinetics, heat and mass transfer phenomena by means of a computational 1D tool. A steady-state model has been developed to generate temperature profiles and conversion patterns over the reactor axis. Residence time distribution capabilities have been considered to take into account the axial dispersion. The framework, including heat transport processes, is based on a 4 parallel Distributed Activation Energy Model. Its structure includes the three major biomass pseudo-component occurring in the biomass thermal degradation. The results of a generic biomass are then analyzed in terms of products distribution and heat transfer characteristics.

Using natural gas in internal combustion engines (ICEs) has been emerging as a promising strategy to improve thermal efficiency and limit exhaust emissions. Major benefits can be had in fact running under lean combustion conditions. However, as the mixture is leaned out beyond the Lean Misfire Limit (LML), some issues may occur in terms of effective and stable engine operation. Thus, different solutions have been proposed over the last decade to overcome those problems. Among them, the stratification of the charge has been shown to successfully extend the LML with respect to conventional lean burn engines. Upon development and optimization of such strategies, Computational Fluid Dynamics (CFD) may be particularly useful to understand thoroughly the phenomena occurring during the mixing and combustion phases and their dynamic coupling. A detailed description of the turbulent properties of the PSC injection process is crucial to reliably represent the stratification effects. The LES approach has been validated as accurate to capture the typical scales of motion of the mixing process due to the PSC injection into a Constant Volume Combustion Chamber (CVCC). This work aims at extending the studies already done into the CVCC toward the analysis of the behavior of a real engine, comparing the current findings with the CVCC data.

Distributed generation systems and microgrids are instrumental for a greater penetration of renewables to achieve a substantial reduction on carbon emissions. However, microgrids performances and reliability strongly depend on the continuous interaction between power generation, storage and load requirements, highlighting the importance in developing a proper energy management strategy and the relative control system. In this work a Model predictive Control (MPC) strategy, based on a Mixed Linear Integer Programming framework, has been applied to a residential microgrid case. Theoretical results obtained confirm that grid connected microgrids have potential capabilities in grid balancing allowing for a larger penetration of fluctuating renewable energy sources and thus producing economic benefits for both end-user and grid operators. A microgrid test bench to reproduce previous microgrid model is also presented in the paper. The experimental setup has been used to validate results obtained from simulation. Results obtained confirm the potential of this solution and its real applicability.

The results of a wide demonstration test of Off-Grid Radio Base Stations powered with fuel cells and locally available renewable energy sources are presented. The experimental activity has been conducted as part of the FCPoweredRBS project to assess and verify the potential of hydrogen and fuel cells as power and energy sources for the telecom market. For this application, Fuel Cells have been integrated as a programmable power generator with a photovoltaic system and an energy storage system. Both electrochemical batteries and hydrogen produced locally with an electrolyzer have been tested as energy storage solutions. Data collected for a full year have been used to assess the potential of the systems proposed in comparison with diesel generators which are the standard solution for such applications. Results show that the hybrid renewable energy solution may be competitive in terms of energy efficiency and minimum consumption of fossil fuel consumption. Proper sizing and control strategy optimization are key aspects to this aim. Despite the use of FC technology and the integration of many different components, field tests have shown an acceptable level of stability and reliability.

Dual fuel diesel-methane low temperature combustion (LTC) has been investigated by various research groups, showing high potential for emissions reduction (especially oxides of nitrogen (NOx) and particulate matter (PM)) without adversely affecting fuel conversion efficiency in comparison with conventional diesel combustion. However, when operated at low load conditions, dual fuel LTC typically exhibit poor combustion efficiencies. This behavior is mainly due to low bulk gas temperatures under lean conditions, resulting in unacceptably high carbon monoxide (CO) and unburned hydrocarbon (UHC) emissions. A feasible and rather innovative solution may be to split the pilot injection of liquid fuel into two injection pulses, with the second pilot injection supporting the methane combustion once the process is initiated by the first one. In this work, diesel-methane dual fuel LTC is investigated numerically in a single-cylinder heavy-duty engine operating at 5 bar brake mean effective pressure (BMEP) at 85% and 75% percentage of energy substitution (PES) by methane (taken as a natural gas surrogate). A multidimensional model is first validated in comparison with experimental data obtained on the same single-cylinder engine for early single pilot diesel injection at 310 CAD and 500 bar rail pressure. With the single pilot injection case as baseline, the effects of multiple pilot injections and different rail pressures on combustion emissions are investigated, again showing good agreement with experimental data. Apparent heat release rate and cylinder pressure histories as well as combustion efficiency trends are correctly captured by the numerical model. Results prove that higher rail pressures yield reductions of HC and CO by 90% and 75%, respectively, at the expense of NOx emissions, which increase by ∼30% from baseline. Furthermore, it is shown that post-injection during the expansion stroke does not support the stable development of the combustion front as the combustion process is confined close to the diesel spray core.

The increasing penetration of Renewable Energy Source (RES) makes consumption flexibility one of the major requirements to maintain electric grid stability. A key role in effectively matching volatile RES production with load demand can be played by manufacturing enterprises, as they offer a few flexibility options. The aim of this work is from one side to develop a new control algorithm for increasing the flexibility and from the other side to identify and evaluate new flexibility options within manufacturing enterprises, with the aim to move towards the concept of Net-Zero-Energy Factories. A Model Predictive Control strategy, featured with a Mixed-Integer-Linear-Programming algorithm, has been implemented to optimally scheduling the production of a furniture industry. A sensitivity analysis on buffer stocks dimension is carried out in order to identify the optimal storage sizing (for material and energy) allowing to minimize the net yearly energy exchange with the grid. The studied approach allows to reduce by 27% the total energy exchange with the grid with respect to a baseline case study. Further decrease of 50 % has been obtained with the introduction of a battery storage system.

The previous works on the use of PEM Fuel Cell based power supply system for the operation of off-grid RBS (Radio Base Stations) sites showed a strong influence of system design parameters on the energy conversion performance. In this paper a perturbation of system design is studied with validated models to understand the variability of performance over a full year operation. Moreover, a multi-objective optimal sizing methodology is proposed in terms of the minimization of a functional parameter taking into account costs, RES (Renewable Energy Sources) exploitation and pollutant emission factors. The influence of different weather conditions on the HRES (Hybrid Renewable Energy Systems) performance is analyzed investigating the system behavior for three different locations in Europe. The analysis of three real case studies showed that 20% ratio of the energy produced by fossil fuels over the energy produced by renewables sources can be obtained slightly increasing the PV (PhotoVoltaic) plant size with minor effects on the RES exploitation. Moreover, a lower LCOE (Levelized Cost Of Energy) can be achieved increasing the PV size and reducing battery size with an unavoidable reduction of the RES exploitation. Results for different sites highlighted the obtainment of different optimal sizings for each site. However, similar performance parameters can be obtained in the different case studies for Tilos, Rome and Brighton with an average LCOE of 0.5 €/kWh and a variability in the order of 0.1 €/kWh.

Hybrid Renewable Energy Systems (HRESs) can rely on the integration of multiple renewable and non-renewable energy sources. Those are effective means to increase the exploitation of local renewable energy sources in the Distributed Generation (DG) paradigm concept. The design of HRES is usually performed matching load and production profiles in a long- to medium-term time horizon with the aim to optimize energy performance with respect to costs. In this work, a multi-objective parameter is defined to identify the optimal configuration of the hybrid system. Costs, renewable energy self-consumption and emission factors are included in the functional parameter to be targeted. Production and disposal emission factors are evaluated by means of a Life Cycle Analysis (LCA) for PV and batteries in order to show how this would affect the sizing of the HRES. Moreover, the effects of a Thermal Energy Storage (TES) system on the performance and the design of a residential HRES in analyzed when both electric and thermal loads are considered in the energy management strategy. A beneficial effect of the TES inclusion is observed, resulting in system downsizing at same energy and emission performance, as well as in a lower LCOE (Levelized Cost of Energy) and higher PV energy self-consumption.Hybrid Renewable Energy Systems (HRESs) can rely on the integration of multiple renewable and non-renewable energy sources. Those are effective means to increase the exploitation of local renewable energy sources in the Distributed Generation (DG) paradigm concept. The design of HRES is usually performed matching load and production profiles in a long- to medium-term time horizon with the aim to optimize energy performance with respect to costs. In this work, a multi-objective parameter is defined to identify the optimal configuration of the hybrid system. Costs, renewable energy self-consumption and emission factors are included in the functional parameter to be targeted. Production and disposal emission factors are evaluated by means of a Life Cycle Analysis (LCA) for PV and batteries in order to show how this would affect the sizing of the HRES. Moreover, the effects of a Thermal Energy Storage (TES) system on the performance and the design of a residential HRES in analyzed when both electric and therm...

Energy Management System (EMS) optimal strategies have shown great potential to match the fluctuating energy production from renewables with an electric demand profile, which opens the way to a deeper penetration of renewable energy sources (RES) into the electric system. At a single building level, however, handling of different energy sources to fulfill both thermal and electric requirements is still a challenging task. The present work describes the potential of an EMS based on Model Predictive Control (MPC) strategies to both maximize the RES exploitation and serve as an ancillary service for the grid when a Heat Pump (HP) coupled with a Thermal Energy Storage (TES) is used in a residential Hybrid Renewable Energy System (HRES). Cost savings up to 30% as well as a reduction of the purchased energy unbalance with the grid (about 15%–20% depending on the season) have been achieved. Moreover, the thermal energy storage leads to a more efficient and reliable use of the Heat Pump by generally decreasing the load factor smoothing the power output. The proposed control strategy allows to have a more stable room temperature, with evident benefits also in terms of thermal comfort.

Energy Management Systems (EMS) strategies aim at matching energy production with the request, as they are off-phased and highly variable whenever LV networks are considered. This work demonstrates how an EMS based on a Model Predictive Control (MPC) strategy can perform better improving the accuracy of the load forecasting algorithm. To that aim a novel approach is presented, that is characterized by the correlation between real time and historical consumption data. The technique has been tested for over a year of operation. Three test cases have been compared (low error load forecasting, higher error load forecasting and correlation-corrected load forecasting) and techno-economic advantages have been obtained with the new approach. Indeed, a reduction of 14,1% in energy unbalance with the grid and of 8,7% in annual operational costs have been obtained when the load forecast correction is performed. Moreover, the critical components of the system (Electrochemical Energy Storage and Fuel Cell) result to work in less stressful operating conditions, another positive effective of the technique.

Over the last few decades, emissions regulations for internal combustion engines have become increasingly restrictive, pushing researchers around the world to exploit innovative propulsion solutions. Among them, the dual fuel low temperature combustion (LTC) strategy has proven capable of reducing fuel consumption and while meeting emissions regulations for oxides of nitrogen (NOx) and particulate matter (PM) without problematic aftertreatment systems. However, further investigations are still needed to reduce engine-out hydrocarbon (HC) and carbon monoxide (CO) emissions as well as to extend the operational range and to further improve the performance and efficiency of dual-fuel engines. In this scenario, the present study focuses on numerical simulation of fumigated methane-diesel dual fuel LTC in a single-cylinder research engine (SCRE) operating at low load and high methane percent energy substitution (PES). Results are validated against experimental cylinder pressure and apparent heat release rate (AHRR) data. A 3D full-cylinder RANS simulation is used to thoroughly understand the influence of the start of injection (SOI) of diesel fuel on the overall combustion behavior, clarifying the causes of AHRR transition from two-stage AHRR at late SOIs to single-stage AHRR at early SOIs, low temperature heat release (LTHR) behavior, as well as high HC production. The numerical campaign shows that it is crucial to reliably represent the interaction between the diesel spray and the in-cylinder charge to match both local and overall methane energy fraction, which in turn, ensures a proper representation of the whole combustion. To that aim, even a slight deviation (∼3%) of the trapped mass or of the thermodynamic conditions would compromise the numerical accuracy, highlighting the importance of properly capturing all the phenomena occurring during the engine cycle. The comparison between numerical and experimental AHRR curves shows the capability of the numerical framework proposed to correctly represent the dual-fuel combustion process, including low temperature heat release (LTHR) and the transition from two-stage to single stage AHRR with advancing SOI. The numerical simulations allow for quantitative evaluation of the residence time of vapor-phase diesel fuel inside the combustion chamber and at the same time tracking the evolution of local diesel mass fraction during ignition delay — showing their influence on the LTHR phenomena. Oxidation regions of diesel and ignition points of methane are also displayed for each case, clarifying the reasons for the observed differences in combustion evolution at different SOIs.

Dual-fuel combustion has shown high potential for the reduction of emissions (especially nitric oxides and particulate matter) keeping almost unchanged fuel conversion efficiency compared with conventional Diesel engines. However, a deep understanding of the phenomena controlling dual-fuel ignition and combustion processes is still needed to further improving engine behavior especially at low load. To this aim, a combined experimental/numerical approach is proposed in this paper, consisting in a detailed experimental test campaign along with a numerical model to represent and then verify the similarities between engine and chamber local thermodynamics conditions. The design and operation of a tailored experimental setup to study the fundamentals of the dual-fuel combustion process at engine-like operating conditions in optically accessible constant volume combustion chamber is a challenging task. In this paper, similar conditions characterizing the engine operation are represented with a first combustion of a lean air-methane mixture. Then, methane is injected into the chamber to mimic low load engine operation condition in terms of overall equivalence ratio. The oxygen left from the first combustion supports the oxidation of the post-injected methane whose ignition is triggered by a diesel pilot injection. Special care is addressed in characterizing heat and mass losses as well as the mass of methane introduced. During experiments, chamber pressure is measured and thus the evolution of the combustion process is characterized. Numerical simulations, carried out by means of the CONVERGE CFD code, are used to check the charge distribution inside the chamber, and evaluate the local thermodynamic conditions after the gas exchange process. A comparison between the experimental and numerical pressure trace profiles has been performed to validate the numerical model. Results obtained confirm the validity of the proposed approach highlighting the need for a careful calibration of the injection parameters to achieve the target conditions close to the spray injection location.Dual-fuel combustion has shown high potential for the reduction of emissions (especially nitric oxides and particulate matter) keeping almost unchanged fuel conversion efficiency compared with conventional Diesel engines. However, a deep understanding of the phenomena controlling dual-fuel ignition and combustion processes is still needed to further improving engine behavior especially at low load. To this aim, a combined experimental/numerical approach is proposed in this paper, consisting in a detailed experimental test campaign along with a numerical model to represent and then verify the similarities between engine and chamber local thermodynamics conditions. The design and operation of a tailored experimental setup to study the fundamentals of the dual-fuel combustion process at engine-like operating conditions in optically accessible constant volume combustion chamber is a challenging task. In this paper, similar conditions characterizing the engine operation are represented with a first combustion ...

Ultra-Lean operating conditions have a great potential toward the increase of engine thermal efficiency and control of pollutant emissions in Internal Combustion Engines; however, cyclic variability and stability are still critical issues to be solved. The use of natural gas may partially solve these issues due to a more efficient mixing process, widening the flammability limits. An analysis of natural gas ultra-lean combustion process is presented in this work using local charge stratification to stabilize the process. In particular, the predictive capabilities of the numerical model are here validated up to ultra-lean (λ=2.0) mixtures. Moreover, an analysis of the ignition timing has been performed, to find the optimal trade-off between flame quenching and turbulent kinetic energy decay as produced by the jet in the vicinity of the spark location. The optimal ignition timing has been calculated in the range of 5ms.

Purpose – In the recent years the interest toward the use of biomass as a fuel for energy conversion, along with the continuous tightening of regulations, has driven the improvement of accurate design techniques which are required to optimize the combustion process and simultaneously control pollutant emissions. In this paper the use of a 3D Computational Fluid Dynamics approach is analyzed to that aim by means of an application to an existing 50 MW biomass fixed-bed combustion furnace fueled by grape marc. The paper aims to discuss these issues. Design/methodology/approach – The studied furnace is an interesting example of biomass utilization as it may integrate biomass with organic residual by an industrial process. The numerical model has been implemented into an OpenFOAM solver, with an Eulerian-Lagrangian approach. In particular, the fully 3D approach here presented, directly solves for the gas and solid evolution in both the combustion bed and the freeboard. Special care has also been devoted to the...

Direct injection (DI) strategy of natural gas (NG) into internal combustion engines (ICE) has led to higher thermal efficiency and lower exhaust emissions. In order to thoroughly understand the most relevant phenomena affecting the performances of such engines, computational fluid dynamics (CFD) plays a key role as an accurate description of the jet evolution and interaction within the combustion chamber is required to that aim. Accurate description of high-pressure gaseous jets is rather challenging at high Mach numbers, as the injected gas is strongly under-expanded once in the ambient, giving room to shocks due to compressibility effects. Also the interaction between shock waves and mixing layers needs to be carefully represented with a multi-dimensional model, calling for substantial computational resources requirements. In this paper a numerical investigation of the behavior of a gaseous jet (Argon) through an outward opening injector has been carried out. A Large Eddy Simulation (LES) approach has been used in order to track the structures derived by the interaction of the injected fuel with the surrounding ambient. Although already good results were obtained using a Reynolds Averaged Navier-Stokes (RANS) approach, the adoption of LES is required to characterize more accurately the jet properties in terms of vortex structures and mixing effectiveness. The effect of the Nozzle Pressure Ratio (NPR) on the jet evolution has been highlighted in the paper, showing how a higher NPR would give a faster injection process, compromising however the homogeneity of the mixture.

Lean-burn natural gas engines can be used to reduce exhaust emissions significantly. However, as the mixture is leaned out, the occurrence of extinction and incomplete combustion increases, resulting in poor performance and stability, as well as elevated levels of unburned hydrocarbon (UHC) and nitrogen oxides (NOx) emissions. The partially stratified charge (PSC) method can be used to mitigate these issues, while extending the lean misfire limit (LML) beyond its equivalent, homogeneous level. In this chapter, the PSC ignition and combustion processes are examined following a comprehensive experimental and numerical approach. Experiments are conducted in an idealized PSC configuration, using a constant volume combustion chamber (CVCC), to identify the principle enabling mechanisms of the PSC methodology. Engine tests conducted in a single-cylinder research engine (SCRE) demonstrate the feasibility of various PSC implementations in improving performance and emission characteristics in real-world settings. Complementary numerical analyses for the CVCC are obtained through large eddy simulations (LES), while Reynolds-averaged Navier–Stokes (RANS) simulations are conducted for SCRE with reduced chemical kinetics. The corresponding simulated results provide additional insights in characterizing the effect of fuel stratification on flame kernel maturation and flame propagation, the interplay between chemistry and turbulence at different overall air–fuel ratios, as well as formation of major pollutant species.

Gasoline Direct Injection (GDI) is a leading technology for Spark Ignition (SI) engines: control of the injection process is a key to design the engine properly. The aim of this paper is a numerical investigation of the gasoline injection and the resulting development of plumes from an 8-hole Spray G injector into a quiescent chamber. A LES approach has been used to represent with high accuracy the mixing process between the injected fuel and the surrounding mixture. A Lagrangian approach is employed to model the liquid spray. The fuel, considered as a surrogate of gasoline, is the iso-octane which is injected into the high-pressure vessel filled with nitrogen. The numerical results have been compared against experimental data realized in the optical chamber. To reveal the geometry of plumes two different imaging techniques have been used in a quasi-simultaneous mode: Mie-scattering for the liquid phase and schlieren for the gaseous one. Different operating conditions, in terms of temperature and pressure inside the chamber, have been tested to check the robustness of the numerical framework proposed by varying operating conditions. Results obtained show a very good agreement between the numerical results and the experimental data confirming the capabilities of the approach to describe accurately all the physical phenomena involved in the injection process. The influence of the grid size and the number of parcels has been highlighted showing the existence of threshold values for accuracy. Further investigation on the mixing characteristics of the spray have been performed looking at the turbulence generated by the spray-ambient interaction and the local ignition probability index.

Hybrid Power System (HPS) are effective means for the increase of the exploitation of local renewable energy sources in the Distributed Generation (DG) paradigm concept. This work aims at analyzing thoroughly the effects mentioned for two different energy demand profiles: an industrial facility and a residential complex of 75 apartments. A parametric analysis with different components sizing is proposed to evaluate the optimal solution in terms of deployment of renewable energies, resilience of the system and environmental impact, considering the economic convenience as a sustainability constraint. Results show that the two main drivers for the convenience of such systems are the load profile and the PV power plant power sizing. The former shows greater effectiveness of the microgrid management for the residential load rather than the industrial one. The latter shows that the correct sizing of the PV powerplant allows for a smarter use of the battery and gives lesser dependence on the energy exchanged with the grid.

The thermochemical conversion of biomass can be effective for flexible and programmable production of electric and thermal power. Only a few models have been developed so far in the literature to describe the behavior of a screw reactor system designed for biomass fast pyrolysis. The temperature profile plays a crucial role in particular for fast pyrolysis purposes. Hence, a complete heat transfer model is required to that aim. This paper is focused on numerical modeling of a shaftless screw pyrolyzer with special focus on the kinetic framework, as well as the description of heat and mass transfer phenomena. A steady-state model with constant wall temperature has been developed to generate temperature profile and conversion patterns along the reactor. Residence time distribution input has been considered to take into account non-perfect mass conveying characteristics. The model, including all the different heat flux mechanisms such as conduction, convection and radiation, is based on a four parallel Distributed Activation Energy Model. The structure includes the three major biomass pseudo-component occurring in the biomass thermal degradation, and namely cellulose hemicellulose and lignin, along with the moisture evaporation process. Numerical results have been compared with experimental data of spruce wood pellet fast pyrolysis obtained in a lab-scale screw reactor. Numerical temperature profiles for both gas and solid phase, are in good agreement with experimental data. The results obtained allow for demonstrating that the selected framework gives realistic conversion rates for all the fast pyrolysis products namely bio-oil, char, and syngas. The maximum bio-oil production from ground spruce wood has been observed at 500 °C, with yield in the range of 64%. Moreover, the results show a strong dependence on wall temperature, gas-solid heating rate, and screw geometry.

Electrochemical energy storage has become important in the last years to improve the energetic efficiency of stationary and hybrid energy production systems. Lithium batteries represent the best choice, since they have high energy and power density, high number of cycles and a good temperature behaviour compared to other technologies. It becomes important the monitoring of the state of the battery to know online the energy content, to avoid dangerous operating conditions and to extend the useful life. In this work, we have defined a test procedure to study the ageing of LiPO (lithium polymer) batteries through the EIS (electrochemical impedance spectroscopy) technique. Through a fitting procedure performed on the acquired IS (impedance spectra), we have extracted the parameters of an equivalent circuit model to reproduce the voltage discharge curves of the batteries and to study the performance under load. Then we have introduced a relation between the ohmic resistance of the battery and the available capacity to evaluate the SOH (state of health) through the ToE (Theory of Evidence). The method is able to detect the SOH of the tested batteries with a maximum error of 3.73%, with an enhancement to 8.66% when an anomalous cell is considered.

The State of Health (SOH) of a battery is important to know the maximum energy that a battery can release while is operative and to plan the correct maintenance. In this work, we have implemented a diagnostic method to evaluate the SOH of single nickel metal hydride (NiMH) cells, that have an important role in power tools applications. Single NiMH cells of 1.2 V and 1.3 Ah have been characterized with Electrochemical Impedance Spectroscopy (EIS) technique to evaluate the SOH with synthetic methods. Through the study of an equivalent circuit model, we determine that three free parameters synthesize the information contained in an impedance spectrum. A new simplification allows us to construct a diagnostic diagram with only two degree of freedom. A mathematical approach based on the Dempster–Schafer Theory of Evidence has been implemented to interpret the diagnostic diagram. Combining the points obtained by the impedance spectra (IS) at different State of Charge (SOC) and SOH, the Theory of Evidence can improve the estimation of the SOH iteratively, a great advantage compared to the classic Theory of Probability.