• Energy Research
• engineering and technology close
• 7. Clean energy close
• 13. Climate action close
• 12. Responsible consumption close

Four species of wood: two softwoods (Douglas-fir and pine) and two hardwoods (aspen and hybrid poplar) are investigated for their size reduction energy consumption and ground particles size distributions. Lignin content, ash content, and density of wood is measured. Specific grinding energy was 155.9, 226.1, 209.1, and 276.3 kJ/kg for Douglas-fir, pine, aspen, and hybrid poplar, respectively. The analysis of variance shows that lignin content (ranged from 26 to 36.7 %wt based on oven-dry, extractive-free wood) and ash content (ranged from 0.36 to 0.55 % wt dry basis) are significant factors on effective energy consumption of grinding.

AbstractIn this paper a complete vehicle system simulation tool chain which applies a Multi Objective Optimization (MOO) methodology for designing the Electric Powertrain (ePT) of Battery Electric Vehicles (BEV) is presented. Optimization scope includes all relevant electric powertrain components from battery, inverter, electric machine to gear box. In addition to cost, vehicle dynamics, energy consumption and range are further optimization targets. For an overall minimal system cost design a multiplicity of interactions between all powertrain components has to be taken into account. High system complexity prevents an expert to consider all relevant correlations without the support of numeric simulation tools. The presented simulation tool chain enables fast identification of the best cost/benefit trade off regarding system cost while considering all defined system performance requirements. The approach enables experts to find unconventional solutions which would have been overlooked applying a classical straight forward approach and, thus, helps to sharpen the expert's knowledge in cause-effect relationships on the system level. Typical use cases are given and illustrated by several practical examples.

The use of superconducting magnetic energy storage (SMES) has been widely reported in the literature to mitigate various load frequency control (LFC) issues in a multi-area power system. Most of these are thyristor based SMES, employing proportional type controllers. In this paper, a supervisory adaptive model predictive control scheme (AMPC) is proposed for a voltage source converter based relatively small rating SMES for LFC application. The reference power command for the SMES is derived from the AMPC in such a manner that it effectively handles the operational constraints of the SMES system. A representative first-order system emulating the inner loop dynamics of the SMES chopper system, is tuned offline via genetic algorithm (GA) and is used to derive dynamic constraints for the cost function in AMPC. The effectiveness of the scheme is demonstrated through simulations.

AbstractHere, we present the results of evaluation of solar energy potential and photovoltaic (PV) module performance from actual data measured over a period of more than 2 years in the Gobi Desert of Mongolia. To allow estimation of solar energy potentials and durability of PV systems in the Gobi Desert area, a data acquisition system, including crystalline silicon (c‐Si), polycrystalline silicon (p‐Si) modules, and two sets of precision pyranometers, thermometers, and anemometer, was installed at Sainshand City in October 2002. This system measures 23 parameters, including solar irradiation and meteorological parameters, every 10 min. High output gain was observed due to operation at extremely low ambient temperatures and the module performance ratios (PRs) were high (>1·0) in winter. In summary, the present study showed that a PV module with a high temperature coefficient, such as crystalline silicon, is advantageous for use in the Gobi Desert area. Copyright © 2006 John Wiley & Sons, Ltd.

Experimental investigation into the effects of different pilot amounts of dimethyl ether (DME) on the performance and emission of a single-cylinder directinjection DME engine is conducted. The results show that a DME engine can operate at a wider range of speeds and loads at quasi-homogenous charge compression ignition (QHCCI) mode. The brake thermal efficiency increases while the exhaust temperature decreases. NOx emission decreases by about 30%–50% although there is a slight increase in HC and CO emissions. NOx, HC and CO emissions increase with an increase in the amount of DME pilot. QHCCI is a good way to increase thermal efficiency and decrease NOx emission.

Abstract Predicting and optimizing radiative thermal properties have been acknowledged as an efficient way to improve thermal insulation performance of fibrous materials with high porosity. Based on experimental investigation of infrared spectral of ultrafine fibrous insulations with diameters of 520–650 nm, a method of calculating radiative thermal properties was presented by combining Rosseland equation, Mie scattering theory, Beer’s law and Subtractive Kramers–Kronig (SKK) relation. To ensure the calculation correct the uniqueness analysis was performed for Poly(vinylidene fluoride) (PVDF) fibers, which indicated the valid fiber diameter was less than 1.06 μm. The calculated thermal radiative conductivities by using the method agreed well with the measured data. The effect of fiber diameter on the thermal properties of the fibrous insulations was also investigated to minimize the radiative thermal conductivity. The results indicated that the minimized radiative thermal conductivities by regulating fiber diameters could be approximately 25% smaller than those for experimental fiber diameters. The method of predicting and minimizing radiative thermal conductivities of fibrous insulations demonstrated in this paper could be of great advantage to thermal engineering applications aiming to reducing heat loss and saving energy.

IT technologies related to Industry 4.0 facilitate the implementation of the framework for sustainable manufacturing. At the same time, Industry 4.0 integrates IT processes and systems of production companies with IT solutions of cooperating companies that support a complete manufactured product life cycle. Thus, the implementation of sustainable manufacturing implies a rapid increase in interfaces between IT solutions of cooperating companies. This, in turn, raises concerns about security among manufacturing company executives. The lack of a recognized methodology supporting the decision-making process of choosing the right methods and means of cybersecurity is, in effect, a significant barrier to the development of sustainable manufacturing. As a result, the propagation of technologies in Industry 4.0 and the implementation of the sustainable manufacturing framework in companies are slowing down significantly. The main novelty of this article, addressing the above deficiencies, is the creation, using the combined DEMATEL and ANP (DANP) and PROMETHEE II methods, of a ranking of the proposed three groups of measures, seven dimensions and twenty criteria to be implemented in companies to ensure cybersecurity in Industry 4.0 and facilitate the implementation of the sustainable production principles. The contribution of Industry 4.0 components and the proposed cybersecurity scheme to achieve the Sustainable Development goals, reducing the carbon footprint of companies and introducing circular economy elements was also indicated. Using DANP and PROMETHEE II, it can be concluded that: (i) the major criterion of cybersecurity in companies is validation and maintaining electronic signatures and seals; (ii) the most crucial area of cybersecurity is network security; (iii) the most significant group of measures in this regard are technological measures.

Reactive power consumption of the modern power system is a very important problem that to solve well. Due to the line commutated current source converter-based (LCC) HVDC system is a multivariable and strong coupling nonlinear system, it is difficult to model reactive power consumption of receiving end of LCC-HVDC by traditional analysis method. This paper proposes the reactive power consumption model of receiving end of LCC-HVDC on account of the radial basis function (RBF) neural network. The model with the turn-off angle for input, with reactive power loss on the inverter side of LCC-HVDC for output, using 500kV, 1000MW LCC-HVDC system PSCAD simulation test data training RBF neural network and testing network generalization ability. The results indicate that the reactive power loss model on account of the RBF neural network has much faster convergence speed and higher convergence precision.

AbstractMembrane Technology and Research, Inc. has proposed a hybrid system combining amine scrubbing with membrane technology to reduce energy cost. Previous studies of CO2 absorption mainly focused on coal-fired flue gas with 12% CO2. However, in the hybrid process, the CO2 in the flue gas can be enriched to 20%. Natural gas turbines will have flue gas with as little as 3% CO2。 Based on the arrangement, the hybrid amine/membrane system provides a gas to the system that has double the CO2 concentration of normal flue gas, reduces the volume of gas sent to the capture unit, or reduces the removal requirements for the capture unit.The objective of this work is to minimize the total energy use of stripping concentrated piperazine (PZ) at rich loading when treating flue gas from 3 to 20% inlet CO2. The base-case stripping configuration is the advanced flash stripper with warm rich bypass and cold rich exchanger bypass. . This configuration includes two split cross-exchangers in series, a convective steam heater, a smaller stripper column, a low residence time flash tank, and stripping at high temperature to produce CO2 at 5 to 17bar. Rich loading in 5 and 8m PZ was varied from 0.37 to 0.43mol CO2/mol N. For each rich loading, lean loading was optimized to minimize the total equivalent work. The “Independence” model for PZ in Aspen Plus® was used to simulate the stripping performance.Because 5m PZ has a lower viscosity than 8m PZ, it can achieve a reduced approach temperature in the cross exchanger. The total energy performance for 5m PZ is practically the same as 8m PZ, even though the capacity of 5m PZ is lower. Significantly more energy is required to regenerate solvents with lower rich loading. As CO2 rich loading increases, the equivalent work requirement decreases for the same loading difference between rich and lean.Stripping data for 24 cases, including heat duty, equivalent work, CO2 output pressure, and optimal cold and warm rich bypass were used to build a correlation with CO2 rich and lean loading. The Second Law efficiency based on the ratio of stripping minimum work and total ideal work was introduced to make the most of stripping work. The Second Law efficiency has a maximum value at a specific CO2 loading.