• Energy Research
• other engineering and technologies close
• 7. Clean energy close
• 11. Sustainability close
• 4. Education close
• KR close

Interconnectivity and interoperability are very important features in the development of integrated energy management systems for industrial facilities. A simple and common strategy for exchanging energy-related information among the entities in a facility is currently lacking. To this end, the purpose of this study is to present an IoT-based communication framework with a common information model to facilitate the development of a demand response (DR) energy management system for industrial customers. Additionally, we developed and implemented an IoT-based energy-management platform based on a common information model and open communication protocols, which takes advantage of integrated energy supply networks to deploy DR energy management in an industrial facility. The experimental results of this study demonstrate that the proposed platform can not only improve the interconnectivity of the entities in industrial energy management systems but also reduce the energy costs of industrial facilities.

Abstract Date biomass is a carbon-rich renewable resource that can be considered a potential carbon-rich substrate for energy generation over anaerobic digestion (AD). However, due to its complex nature, appropriate pretreatment is necessary to achieve a higher methane yield. Hence, the current study was envisioned to evaluate the influence of three different pretreatment strategies, namely acid, alkali, and hydrothermal pretreatment on biochemical methane potential (BMP) of seven diverse sorts of Algerian date biomass, namely Pedicels, Fibrilium, Petiole, Fruit bunch, Spath, Palm, and its mixture. Among all the pretreatment conditions, alkaline pretreatment highly influenced the lignin composition of date biomass and showed higher BMP. Among all sorts of biomass, higher BMP was detected through Palm as 295.9 mL CH4/g-TS, whereas the lowest BMP values were recorded with Petiole as 226.74 mL CH4/g-TS. Among all the experimental variations, ammonium pretreated Palm biomass documented the highest substrate conversion efficiency (63.80%), which correlates well with the observed higher BMP values. Nevertheless, there was a very marginal improvement in BMP detected in the case of other pretreatment strategies compared to alkaline pretreatment. This might be due to the efficacy of the applied pretreatment method on delignification of date biomass.

The combustion possibility of Indonesia KBB coal as a pulverized fuel for a thermal power plant was studied with a thermogravimetric analysis (TGA), drop tube furnace (DTF) and ignition temperature (IT) tester. TGA results showed that combustion patterns of coal samples were divided into devolatilization and oxidation reactions, and the fixed carbon contained with minor content in high moisture KBB coal (HM KBB) was quickly burned at a lower temperature than that of bituminous C&A coal (Design C&A). The linear regression for the Arrhenius plot to the experimental data is very good, and activation energies for overall combustion of Design C&A and HM KBB are 63.19 and 81.89 kJ/mol, respectively. It was derived that activation energies of dry KBB coal (Dry KBB) produced through drying of HM KBB and its mixture (Dry KBB Mixture) are 79.82 and 61.66 kJ/mol in reciprocal proportion to specific surface area. Test results show that the volatile content contained in coal samples except for HM KBB with the lowest surface area significantly improved the combustion reactivity. The conversion behavior of the coals observed in DTF was similar to that reflected in TGA. DTF studies showed that the combustion of Dry KBB Mixture was also completed at a residence time of around 1 s and set temperature range of 1,200°C similar to commercial coal fired plant. Although Dry KBB has the highest conversion of the four coals, it was not appropriate as a single pulverized fuel of coal fired plant because its initial deformation (IDT) and ignition temperatures of about 1,088 and 198°C, respectively, were too low to cause slagging in boiler, and firing at the pulverizer. The high IDT of Dry KBB Mixture ash with minimum of 1,250°C is not expected to be associated with slagging and fouling in pulverized coal fired systems. The liability of spontaneous combustion of coal samples was increased with increasing the moisture and volatile contents whereas that of Dry KBB was the highest due to the high surface area. It was, therefore, proposed that the combustion of mixtures of Dry KBB with Design C&A was the most appropriate for the prevention of slagging and spontaneous combustion in pulverized coal fired boilers and has excellent combustion efficiency.

Torrefaction is a thermal treatment process to pre-treat biomass at temperature of under an inert atmosphere. It was known that torrefaction process strongly depended on the decomposition temperature of the lignocellulosic constituents in biomass. In this work, the torrefaction characteristics of baggase has been studied. This study focuses on the relation between the energy yields, heating values, gas emission, volatile and ash constituents with torrefaction temperatures and times. The activation energies of baggase torrefaction has been studied by using TGA (Thermogravimetric Analyzer). From this work, it was seen that ash constituents and heating values were increased with torrefaction temperature, while volatile constituents and energy yields decreased. It was also found that carbon monoxide containing oxygen were decomposed at a lower temperature than those of hydrocarbon compounds, .

This paper presents a CFD analysis of three types of axial-flow magnesium-based automotive cooling fans. The numerical modeling was conducted for geometrically modified fan designs: one with no-beads, the second one with beads at the suction-side of the fan namely reverse-beads fan, and the third one with beads installed at the pressure-side of the fan namely forward-beads fan. The effect of geometric modifications of the fan blades on the volumetric flow rate, fan efficiency, and energy efficiency was investigated using Reynolds-averaged Navier-Stokes (RANS) equations following the multiple reference frame methodology. The fan with no-beads was fabricated using 3D printing technology and tested to measure the flow velocity. Subsequently, the fans with beads along with the no-beads fan designs were numerically analyzed. The volumetric flow rate, fan efficiency, and energy efficiency were quantified as a function of fan rotating speed. The results show that the reverse-beads fan produced a relatively more volumetric flow rate and energy-efficient compared to the forward-beads fan. Moreover, to further improve the performance of the reverse-beads fan, the location and size of the bead structure were varied along the radial direction of the fan blade. The optimized reverse-beads fan significantly improves the fan performance.

Abstract Wood biomass char was used in a direct carbon fuel cell (DCFC) as an alternative fuel. This has many advantages because the DCFC is a high-efficiency system and wood biomass is a carbon-free and regenerative material. Several analytical techniques were employed to analyze the characteristics of three fuels, their effects on the cell’s performance, and the electrochemical reactions between the fuels and the electrolyte in the system. The morphological and textural characteristics of biomass char were similar to those of two types of coal used as fuels for a DCFC system in spite of the char’s significantly lower carbon content. A practical evaluation of the fuels used in the DCFC system was conducted, and when using the biomass char, the maximum power density was 60–70% that of the corresponding value for coal under the same conditions. The performance of the biomass char fuel was improved by stirring. The possibility of its practical application was also discussed.

Abstract This study newly introduces a complementary cooperative algorithm considering generative adversarial network (GAN)-Conditional Latent Space (CLS) combined with bidirectional long short-term memory (BLSTM) for improved and efficient lithium-ion rechargeable battery state prediction. The GAN-CLS algorithm, which is an advanced method of GAN, can generate corresponding images from an input label description. Long short-term memory (LSTM) is a specific recurrent neural network (RNN) architecture that can predict sequences more accurately than conventional RNNs. In terms of battery state prediction, the combination of two methods (GAN-CLS and LSTM) surely provides more improved and efficient rechargeable battery state prediction in contrast to conventional state predictors. The procedure of this study is as follows. First, we propose methods to enhance the data from battery charge/discharge by converting prepared data to images; then, the GAN-CLS method is used to generate corresponding battery data from previous images. Subsequently, the generated data is used to train the BLSTM model. Finally, the trained model is used to predict the battery state. By various experiments and verification, it is concluded that the proposed study can be a good solution for rechargeable battery state prediction (reduction of the time cost 50 times in modeling and 20 times in train/test, provision of a more accurate prediction mean square error (MSE) smaller than 0.0025 and the average MSE less than 0.0013).

Nowadays, wave energy plays an important role in renewable energy resource. In over thirty years, researches in wave energy converter system (WEC) have been deployed and carried out. This paper presents a design of wave energy converter using 5 cylinders combining with hydraulic power take-off system in order to convert the mechanical energy from ocean wave to electricity, or another useful and usable source. The WEC uses ordered 5 cylinders to represent the motion of the floating buoy under the wave elevation. The design and specification of the WEC system are presented. Buoy and wave interaction mathematical model is built and the hydraulic mathematical model is also presented. The system performance test is implemented and the result is shown.

The Energy Information Administration (EIA) of the U.S. Department of Energy has projected net electricity generation through 2040 for ten selected countries and the world. These ten countries including China and the U.S. are projected to produce 70% of the world electricity generation. Some of the past projections by EIA have been rated too conservative. Using a simple experience curve, we produce alternative projections for comparison. Our projections are significantly higher for eight out of the ten countries. Utilities operating in these eight countries may need to reexamine their plan for future net electricity generation.