Search

Recently, salt-assisted pyrolyzation has been deemed an emerging and efficient method for the preparation of biochars due to its facile operation as well as its good structural and chemical properties. In this work, biochars (MBCx) are prepared by heating bamboo powders in eutectic salts (Li2CO3 + K2CO3) at 500–600 °C in the air. Multiple technologies are employed to examine the physiochemical properties of bamboo biochars. Correlations between heating temperature and structural features and carbon dioxide uptakes of bamboo biochars have been investigated. The results show that heating temperature has a significant influence on the physicochemical properties of bamboo biochars. With the elevation of the heating temperature, the defect structures of bamboo biochars gradually ascend, especially when the heating temperature reaches 600 °C. MBCx biochars visibly exceed conventional bamboo biochar prepared via pyrolyzation in a nitrogen stream free of salt addition. Pyrolysis of bamboo in eutectic salts endows biochars with higher oxygen content and more carbon defects, which likely accounts for their better CO2 capture activities. [ABSTRACT FROM AUTHOR]

Modern energy batteries are mainly used in pure electric vehicles. The stability of battery operation relies heavily on thermal management systems for which phase-change batteries have become an effective solution. In this study, we designed a battery thermal management system divided into two parts: a shaped phase-change material (PCM) module and a battery module. In the qualitative PCM module, polyethylene glycol was used to absorb heat, expanded graphite (EG) was used as the thermally conductive agent, and copper foam formed the support skeleton. The battery module comprised an 18650 lithium-ion battery with an enthalpy of 155 J/g. In our experiments, we applied PCMs to the battery modules and demonstrated the effectiveness of composite PCM (CPCM) in effectively lowering the temperature of both battery packs and minimizing the temperature discrepancies among individual batteries. At a gradually increasing discharge rate (1C/2C/3C), the battery's Tmax could be lowered and the temperature could be de creased at various positions. It was evident that the battery temperature could be effectively preserved using CPCM. The findings of this study lay a foundation for future research on battery thermal management. Finally, the copper foam and EG contributed significantly to the prevention of leakage. [ABSTRACT FROM AUTHOR]

With the opening of the Chinese electricity market, as a retailer that provides energy services to consumers, the park-integrated energy system (PIES) not only serves as an effective way to earn benefits and reduce carbon emissions but also impacts the energy consumption characteristics of consumers. The PIES implements this function by adjusting the energy selling price in free energy markets. The pricing mechanism model (P-M model) is established to obtain the energy selling price in the planning and design stages. In this model, the impact of the demand response on the energy configuration and the impact of the changes in energy configuration on the energy cost price are both considered. Additionally, the optimal result ensures that both the consumers and the PIES benefit simultaneously. The reactive demand response zone, which represents a consumer trap, is found in numerical studies. The results indicate the following: (1) from the perspective of P-M model optimization, the benefit exclusive point of the PIES is the optimal solution in the short term; (2) from the perspective of the long-term benefit, the ultimate result in the relationship between the PIES and consumers is that the PIES will share its profits with consumers; in other words, benefit sharing point is the optimal solution for the long term. [ABSTRACT FROM AUTHOR]

Personal thermal preference information can help to create a building environment that satisfies all staff, instead of an environment that only satisfies most people, to enhance personal thermal comfort. Research has shown that thermal preference can be predicted using parameters that are based on various local body parts, but the selected body parts are often different. Using too many body parts for the measurements leads to high costs, while using too few body parts results in large errors. In this study, 19 adult subjects (8 females and 11 males) were recruited, their overall and local thermal preferences were surveyed, and the skin temperature of seven body parts were measured. A machine learning algorithm, random forest, was employed to analyse the contributions of different body parts. Three criteria (the best combination, fewest combination, and common combinations) were employed to select body parts to use to establish thermal preference models for individuals and groups. The results show that the prediction power of these combinations reached 0.91 ± 0.07 (accuracy), 0.75 ± 0.16 (Cohen's kappa), and 0.87 ± 0.09 (AUC) when using 2–8 body parts. The common combinations are recommended for their balance of their prediction power and the number of local body parts involved. This study offers a reference for efficient and economic measurements for thermal comfort research in building environments. [ABSTRACT FROM AUTHOR]

Various algorithms predominantly use data-driven methods for forecasting building electricity consumption. Among them, algorithms that use deep learning methods and, long and short-term memory (LSTM) have shown strong prediction accuracy in numerous fields. However, the LSTM algorithm still has certain limitations, e.g., the accuracy of forecasting the building air conditioning power consumption was not very high. To explore ways of improving the prediction accuracy, this study selects a high-rise office building in Shanghai to predict the air conditioning power consumption and lighting power consumption, respectively and discusses the influence of weather parameters and schedule parameters on the prediction accuracy. The results demonstrate that using the LSTM algorithm to accurately predict the electricity consumption of air conditioners is more challenging than predicting lighting electricity consumption. To improve the prediction accuracy of air conditioning power consumption, two parameters, relative humidity, and scheduling, must be added to the prediction model. [ABSTRACT FROM AUTHOR]

Steam-CO2 reforming of biomass derived synthesis gas (bio-syngas) was investigated with regard to the steam concentration in the feed using Rh-loaded alumina foam monolith catalysts, which was also accompanied by thermodynamic equilibrium calculation. With 40 vol % steam addition, steam methane reforming and water gas shift reaction were prevailed at the temperature below 640 °C, above which methane dry reforming and reverse-water gas shift reaction were intensified. Substantial change of activation energy based on the methane conversion was observed at 640 °C, where the reaction seemed to be shifted from the kinetic controlled region to the mass transfer controlled region. At the reduced steam of 20 vol %, the increase in the gas velocity led to the increase in the contribution of steam reforming. Comparing to the absence of steam, the addition of steam (40 vol %) resulted in the increase in the production of H2 and CO2, which in turn increased the H2/CO ratio by 95% and decreased the CO/CO2 ratio by 60%. Rh-loaded alumina monolith was revealed to have a good stability in upgrading of the raw bio-syngas. [ABSTRACT FROM AUTHOR]

Human thermoregulation models can predict human thermal responses to evaluate thermal comfort and help create a healthy environment, while their applicability to older people has not been sufficiently validated. This study aimed to evaluate the performance of the Stolwijk model and the Tanabe model for predicting older people's mean and local skin temperatures under thermal transient conditions. Eighteen healthy older people were recruited and exposed to transient environments including neutral (26 °C), low-temperature (23 and 21 °C), and high-temperature (29 and 32 °C) conditions. The local skin temperatures of the subjects were measured and compared to predictions of the Stolwijk model and the Tanabe model. The results revealed that the Stolwijk model and the Tanabe model could accurately predict the mean skin temperature of older people under neutral and high-temperature conditions, while their predictive accuracy declined under low-temperature conditions. Increased deviations were observed in the predictions of local skin temperatures for all conditions. This work attempted to provide an understanding of older people's thermal response characteristics under transient conditions and to inspire the improvement of thermoregulation models for older people. [ABSTRACT FROM AUTHOR]

The analysis of energy configuration in the planning of data-center-park-integrated energy systems (DCP-IESs) has become an enormous challenge, owing to multi-energy complementarity, energy cascade use, and energy security. In this study, a configuration model of DCP-IESs was established to obtain the economic and low-carbon energy uses of the data centers, based on mixed integer linear programming. In the model, carbon emissions were converted to economic indicators through carbon pricing. Then, the configuration model was modified according to the security of the proposed device switching logic, and the Markov-based reliability estimation method was used to ensure the redundant design of the configuration. Using the new energy configuration method, the DCP-IES configuration scheme could be obtained under economical, low-carbon, and high reliability conditions. A data center park in Shanghai was selected as a case study, and the results are as follows: it will only take 2.88 years for the economics of DCP-IES to reach those of traditional data center energy systems. Additionally, the use of configuration model in DCP-IES would result in a reduction in annual carbon emissions of 39,323 tons, with a power usage effectiveness of 1.388, whereas an increase in reliability results in an increasingly faster increase in the initial investment cost. [ABSTRACT FROM AUTHOR]