Clean Technol., Volume 3, Issue 3 (September 2021) – 9 articles

Perennial rye grass is a widely used forage species in Ireland, on which the ruminant sector of agriculture is heavily dependent. While this species of grass is the primary source of fodder for cows, it is also abundant in plant protein, which could form a potential alternative ingredient in monogastric animal feed using a green biorefinery approach. In this study, perennial rye grass was processed using a novel biorefining process to extract value added products including protein as a potential replacement for soybean meal in monogastric feeds. Feed trials were conducted on a commercial farm with 55 weaner pigs for 31 days until slaughter. The diets comprised a control and a trial diet which integrated the green biorefinery protein concentrate. The effects of the new diet were determined by measuring the daily feed intake (DFI), average weight gain (AWG) and feed conversion ratio (FCR). Amino acid profiles of grass protein concentrate and soybean meal were comparable, with the latter having a slightly higher amount of total protein content, lysine and cysteine. The DFI and ADW indicated that the treatment diet was superior to the control. DFI for the treatment diet (1.512 kg/d) was 8% higher than the control diet (1.400 kg/d) by the end of the trial. Additionally, the ADW for the treatment diet was 6.44% higher than that achieved in the control sample. Meanwhile, FCR calculations indicated that the treatment diet is just as efficient as the conventional diet. Overall, the results of the study indicate positive potential for perennial ryegrass-derived green biorefinery protein concentrate as an alternative protein source for pig feed formulations in Ireland. Full article

In a context of accelerating deployment of distributed generation in power distribution grid, this work proposes an answer to an important and urgent need for better management tools in order to ‘intelligently’ operate these grids and maintain quality of service. To this aim, a model-based predictive control (MPC) strategy is proposed, allowing efficient re-routing of power flows using flexible assets, while respecting operational constraints as well as the voltage constraints prescribed by ENEDIS, the French distribution grid operator. The flexible assets used in the case study—a low-voltage power distribution grid in southern France—are a biogas plant and a water tower. Non-parametric machine-learning-based models, i.e., Gaussian process regression (GPR) models, are developed for intraday forecasting of global horizontal irradiance (GHI), grid load, and water demand, to better anticipate emerging constraints. The forecasts’ quality decreases as the forecast horizon grows longer, but quickly stabilizes around a constant error value. Then, the impact of forecasting errors on the performance of the control strategy is evaluated, revealing a resilient behaviour where little degradation is observed in terms of performance and computation cost. To enhance the strategy’s resilience and minimise voltage overflow, a worst-case scenario approach is proposed for the next time step and its contribution is examined. This is the main contribution of the paper. The purpose of the min–max problem added upstream of the main optimisation problem is to both anticipate and minimise the voltage overshooting resulting from forecasting errors. In this min–max problem, the feasible space defined by the confidence intervals of the forecasts is searched, in order to determine the worst-case scenario in terms of constraint violation, over the next time step. Then, such information is incorporated into the decision-making process of the main optimisation problem. Results show that these incidents are indeed reduced thanks to the min–max problem, both in terms of frequency of their occurrence and the total surface area of overshooting. Full article

The search for alternative fuels for internal combustion engines is ongoing. Among the alternatives, plant-based fuels can also be mentioned. Alcohol is not a common fuel for diesel engines because the physical and chemical properties of the alcohols are closer to those of gasoline. In our research, the combustion properties of diesel-n-butanol mixtures have been investigated to obtain results on the effect of butanol blending on combustion. Among the combustion properties, ignition delay, in-cylinder pressure, and heat release rate can be mentioned. They have been observed under different compression conditions on an engine on which the compression ratio can be adjusted. The method used was a quite simple one, so the speed of the engine was set to a constant 900 rpm without load, while three compression ratios (19.92, 15.27, and 12.53) were adjusted with a fuel flow rate of 13 mL/min and the pre-injection angle of 18° BTDC. Blending butanol into the investigated fuel does not significantly affect maximal values of indicated pressure, while much more effect on the pressure rising rate can be detected. Furthermore, heat release rate and ignition delay increased at every compression ratio investigated. Despite the low blending rates of butanol in the mixtures, butanol significantly affects the combustion parameters, especially at high compression ratios. Full article

Cost-effective CO₂ capture and storage (CCS) is critical for the rapid global decarbonization effort recommended by climate science. The increase in levelized cost of electricity (LCOE) of plants with CCS is primarily associated to the large energy penalty involved in CO₂ capture. This study therefore evaluates three high-efficiency CCS concepts based on integrated gasification combined cycles (IGCC): (1) gas switching combustion (GSC), (2) GSC with added natural gas firing (GSC-AF) to increase the turbine inlet temperature, and (3) oxygen production pre-combustion (OPPC) that replaces the air separation unit (ASU) with more efficient gas switching oxygen production (GSOP) reactors. Relative to a supercritical pulverized coal benchmark, these options returned CO₂ avoidance costs of 37.8, 22.4 and 37.5 €/ton (including CO₂ transport and storage), respectively. Thus, despite the higher fuel cost and emissions associated with added natural gas firing, the GSC-AF configuration emerged as the most promising solution. This advantage is maintained even at CO₂ prices of 100 €/ton, after which hydrogen firing can be used to avoid further CO₂ cost escalations. The GSC-AF case also shows lower sensitivity to uncertain economic parameters such as discount rate and capacity factor, outperforms other clean energy benchmarks, offers flexibility benefits for balancing wind and solar power, and can achieve significant further performance gains from the use of more advanced gas turbine technology. Based on all these insights, the GSC-AF configuration is identified as a promising solution for further development. Full article

In this work, the development of an energy recovery control unit to be incorporated in the light-emitting diodes (LEDs) lighting systems of heavy-duty vehicles is presented. This innovative industrial product adopts modern power electronics technology to improve existing trucks’ LED lighting system by eliminating the so far inevitable power consumption by the conventional central control unit of the majority of these vehicles, which is obligatory for the uninterruptable operation of their lighting system. The main idea of this innovative product is its capability to virtually increase the lighting system power consumption without actually consuming this amount of energy, thus facilitating the central control unit requirements regarding these vehicles in an energy-conscious way. Under this light, a mature power converter’s topology is employed to draw the proper amounts of power from the vehicle’s batteries supply, to the level that the central control unit recognizes, and return this energy back to the batteries. The tests results of the developed industrial product highlight the energy saving potential of the proposed energy recovery scheme, while the Life Cycle Cost Analysis (LCCA) results confirm its techno-economical and environmental profit for the truck applications under study. Full article

This study elucidates the effects of the particle size, carbonation time, curing time and pressure on the efficiency of carbon storage in Portland cement mortar. Using pressure chamber experiments, our findings show how carbonation efficiency increases with a decrease in the particle size. Approximately 6.4% and 8.2% (w/w) carbonations were achieved in the coarse-sand and fine-sand based mortar samples, respectively. For the hydration/curing time of 7 h, up to 12% carbonation was achieved. This reduced to 8.2% at 40 h curing period. On the pressure effect, for comparable curing conditions, 2 bar at 7 h carbonation time gives 1.4% yield, and 8.2% at 5 bar. Furthermore, analysing the effect of the carbonation time, under comparable conditions, shows that 4 h of carbonation time gives up to 8.2% yield while 64 h of carbonation gives up to 18.5%. It can be reliably inferred that, under similar conditions, carbonation efficiency increases with lower-sized particles or higher-surface areas, increases with carbonation time and higher pressure but decreases with hydration/curing time. Microstructural analyses with X-ray diffraction (XRD) and scanning electron microscopy (SEM) further show the visual disappearance of calcium-silicate-hydrate (C-S-H) together with the inhibition of ettringite formation by the presence of CO₂ and CaCO₃ formation during carbonation. Full article

The development of engine technologies and research on combustion processes are focused on finding new generation CI engines with simple control of the combustion process while efficiently maintaining desirable engine performance and meeting emission regulations. This comprehensive study on the relatively low hydrogen energy fraction (0.65–1.80%), supplied by onboard water electrolysers and on water injection, was performed on the performance and emission parameters of the CI engine. The article presents results of both experiment and simulation about the effect of hydroxygen and water injection on the combustion process, auto-ignition delay, combustion intensity, the temperature of the mixture and engine performance at BMEP of 0.2 MPa, 0.4 MPa, 0.6 MPa, and 0.8 MPa at a speed of 1900 rpm. For the first part, the test engine operated with diesel fuel with 3.5 L/min of hydroxygen gas supplied with an external mixture formation. The HHO has an effect on the combustion process at all range of BMEP. A decrease in BTE and increase in BSFC were noticed during tests. The peak pressure and the rate of heat release decreased, but the NO_x decreased as well. The second part of experiment was performed with the injection of a substantial amount of water, 8.4–17.4 kg/h (140–290 cm³/min), and the same amount of hydroxygen. The injection of water further decreased the NO_x; therefore, HHO and WI can be used to meet emission regulations. A simulation of the combustion process was carried out with the AVL BOOST sub-program BURN. The AVL BOOST simulation provided a detailed view of the in-cylinder pressure, pressure-rise, combustion intensity shape parameter and SOC. Full article

Monitoring volatile organic compounds (VOCs) places a crucial role in environmental pollutants control and indoor air quality. In this study, a metal-oxide (MOx) sensor detector (used in a commercially available monitor) was employed to delineate the composition of air containing three common VOCs (ethanol, acetone, and hexane) under various concentrations. Experiments with a single component and double components were conducted to investigate how the solvents interact with the metal oxide sensor. The experimental results revealed that the affinity between VOC and sensor was in the following order: acetone > ethanol > n-hexane. A mathematical model was developed, based on the experimental findings and data analysis, to convert the output resistance value of the sensor into concentration values, which, in turn, can be used to calculate a VOC-based air quality index. Empirical equations were established based on inferences of vapour composition versus resistance trends, and on an approach of using original and diluted air samples to generate two sets of resistance data per sample. The calibration of numerous model parameters allowed matching simulated curves to measured data. Therefore, the predictive mathematical model enabled quantifying the total concentration of sensed VOCs, in addition to estimating the VOC composition. This first attempt to obtain semiquantitative data from a single MOx sensor, despite the remaining selectivity challenges, is aimed at expanding the capability of mobile air pollutants monitoring devices. Full article