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Hydrothermal liquefaction (HTL) is an effective way to treat solid wastes with high moisture content. The co-hydrothermal liquefaction (co-HTL) experiments of oily scum and poplar sawdust biochar at the different hydrothermal temperatures were performed in this work. The changes of the appearance and components of the liquid products were comprehensively studied. The results showed that the addition of biochar into oily scum significantly reduced the moisture content of the residue hydrochars obtained after co-HTL. As the hydrothermal temperature increased, the liquid products obtained from co-HTL turned clearer and lighter in color, and the recovery rate of the liquid products significantly increased. The co-HTL of bi-ochar and oily scum could effectively improve the liquid quality and enhance the recovery rate of hydrochars. The carbon numbers of the liquid products obtained from co-HTL were concentrated in C5-C11, which were main compositions of gas-oline. This work can provide basic data and theoretical reference for oily scum efficient treatment and engineering practice.

Solar-driven transformation of biomass and its derivatives has attracted tremendous attention in replacing fossil sources to generate chemicals. Developing high-performance photocatalysts for selective conversion of bio-platform molecules remains a great challenge. Herein, metal-doped photocatalyst was designed for the selective catalysis of biomass derivatives, 5-hydroxymethylfurfural (HMF) was efficiently and controllably converted to 2,5-dicarboxylic furan (DFF) or 5-formyl furantocarboxylic acid (FFCA). In the neutral solution, 64% HMF was converted within 12 h and mainly produced DFF with the selectivity of 74–82%. In 0.5 M Na2CO3 aqueous solution, 30% HMF was converted within 2 h and mainly produced FFCA with the selectivity of 69%. The characterization and photoelectrochemical measurement of photocatalyst showed that the modified material had higher carrier transmission efficiency and better visible light response. The mechanism analysis showed that the photogenerated h+ was the main active specie of the FeOOH/MP, and the introduction of FeOOH inhibited the formation of ˙OH in aqueous solution to realize the highly selective conversion process.

CaO captures CO2 from pyrolysis, forming CaCO3 that activates biochar via decomposition.

Background: Compared with the traditional power system, the large-scale access of distributed energy resources in the new power system has a great impact on the structure and operation mode of the power grid, and it is also more susceptible to device-level and network-level FDI attacks. Objective: In order to improve the accuracy and precision of detecting false data injection attacks in distributed energy resources integration into distribution networks and to further explore time series modeling methods for measurement data, it is helpful for the FDIAs detection method to be widely adopted and applied in new power systems. Methods: To address false data injection attacks on distributed energy resource integration into distribution grids within new power systems, a data-driven time series anomaly detection method is employed. Firstly, time-aware shapelets are extracted from time series data, and then the shapelet evolution graph is constructed to capture the correlation between the shapelets. Finally, time series representation vectors are learned using segment embeddings derived from the shapelet evolution graph through the DeepWalk algorithm. These representation vectors are then input into a BO-XGBoost anomaly detector, facilitating the detection of FDIAs. Results: After multiple rounds of parameter tuning, the parameters of Shapelet quantity (K=40) and segment length (L=4) achieved an accuracy of 92.8% in FDIA detection. Comparative experimental results with different algorithms indicate that, compared to other unsupervised learning methods, this approach exhibits an accuracy improvement of 20-40%. In the case of BOXGBOOST, it achieves a 5% increase in accuracy compared to the unmodified XGBOOST. Conclusion: The experimental results indicate that this method can effectively detect false data injection attacks on the integration of distributed energy resources into distribution grids within new power systems. This model significantly enhances detection accuracy and precision while also imparting physical significance to the dynamic evolution of time series models.

In this study, a coupled numerical computation approach integrating aerothermal and thermomechanical effects was employed to investigate the cooling efficiency and thermal stress characteristics of gas turbine stator blades. A comprehensive analysis was conducted considering varying turbulence intensities in the coolant flow (spanning from 0.05 to 0.15) and different coolant media configurations, including pure air, dual-medium mixture of air and steam, and pure steam. The distributional traits of cooling efficiency and thermal stress on the stator blade surface under these conditions were meticulously examined. Furthermore, quantitative assessments were performed to determine the extent to which coolant turbulence intensity and coolant type affect the average cooling efficiency and maximum equivalent thermal stress of turbine stator blades, thereby revealing the influence laws. The results reveal that the minimum cooling efficiency on the stator blade surface predominantly occurs at the position of channel 4 on the pressure surface, while the highest cooling efficiency is generally found near the leading edge of the suction surface. Regions of elevated thermal stress were consistently concentrated around the stator blade tip and root areas. When the coolant turbulence intensity increased from 0.05 to 0.15, the average cooling efficiency on the stator blade surface improved by 2.06%, accompanied by a reduction of 1.12% in the maximum thermal stress. In comparison to pure air cooling, dual-medium (air and steam) cooling and pure steam cooling lead to respective enhancements in the average cooling efficiency of approximately 3.3% and 13.2%, with corresponding decreases in the maximum thermal stress of 2.18% and 10.2%.

Abstract Coal-fired power plants are commonly used as adjustable power sources to complement the fluctuating output of wind and solar energy. The investigation is required to determine the flexible peak-shaving capabilities of coal-fired boilers. A modified scheme for a lignite-fired power plant to further improve the primary air temperature using the outlet steam from the low-temperature reheater is studied while increasing the inlet flue gas temperature of the air preheater is considered the conventional scheme. Thermodynamic models of the power plant are constructed using ebsilon software. The operational characteristics of both schemes are compared under 30% turbine heat acceptance (THA)–100%THA conditions and the economic performance of the modified scheme is also evaluated. Results indicate that the modified scheme exhibits superior thermodynamic and economic performances compared to the conventional scheme. The disparity in power generation efficiency between the conventional and modified schemes reaches a maximum of 0.23 percentage points under 75%THA conditions. The net present value of the modified scheme amounts to 4.51 million dollars over the power plant lifespan of 30 years. The modified scheme allows the conventional denitrification catalyst to maintain an optimal temperature range even under 30%THA conditions, resulting in a power generation efficiency only 4.8 percentage points lower than that under 100%THA conditions, thus demonstrating remarkable operational flexibility. This study presents an efficient, cost-effective, and adaptable approach for lignite-fired power plants.

An argon magnetic fluid is a collection of free charged particles moving in random directions especially that is a weakly ionized argon discharge and on the average, electrically neutral. The 2-D numerical steady-state model of an argon magnetic fluid generator is presented to investigate the thermodynamic behaviors and the distribution of current density. The CFD codes, OpenFOAM, and FLUENT, are utilized in a modified form to model the argon magnetic flow inside the generator. Modeling a thermal magnetic fluid requires a combination of mutually related fluid dynamics and electromagnetic phenomena. With the appropriate thermophysical model, a pressure-based, steady-state, incompressible magnetic fluid solver based on OpenFOAM was originally developed. Meanwhile, FLUENT was expanded upon secondary development functions of user-defined scalar and user-defined function to develop magnetic fluid solution and make reference comparison. The results demonstrated that the numerical simulations obtained with the OpenFOAM solver were in good agreement with those from FLUENT. The highest temperature and velocity were both observed near the cathode region, with the main body temperature exceeding 6000 K. The anode region exerted a compressive effect on the temperature field and accelerated the MHD flow. The current density was primarily distributed in a columnar pattern, concentrated in the cathode region and exponentially decreasing along the axis towards the anode region, with a significant radial gradient.

Photovoltaic inverter plays a crucial role in photovoltaic power generation. For high-power photovoltaic inverter, its heat loss accounts for about 2% of the total power. If the large amount of heat generated during the operation of the inverter is not dissipated in time, excessive temperature rise will reduce the safety of the devices. This paper proposes a closed photovoltaic inverter structure based on heat pipe and liquid cooling which overcomes the noise, dust and other problems caused by traditional air-cooling heat dissipation method and reduces cost of the volume occupied inside the body. Heat is dissipated through heat pipes, which are efficient heat transfer units. A simulation model of the actual cabinet was estab-lished using CFD, and the maximum junction temperature in the inverter was in-vestigated under different coolant temperatures, flow rates, cooling liquid, and heat loads. The results showed that the liquid cooling heat dissipation structure can effectively dissipate the heat inside the cabinet. The impact of two different types of heat sink used for power modules on temperature uniformity was studied. The results indicated that the 9-heat pipe type heat sink has better heat dissipation and uniform hot spots performance, the maximum heat source temperatures in the chip and capacitor were reduced by 9.91?C and 7.49?C, respectively. Finally, the performance of the two types of radiators under different heat loads was studied.

Background: The accurate locating of fault sections in a distribution network can lay an effective foundation for the rapid processing of faults. However, the waveform of highresistance grounding faults is relatively weak, which increases the difficulty of fault feature extraction and localization. In addition, the complex operating conditions and interference factors of the actual distribution network can affect the fault section localization method, leading to incorrect location problems. Objective: In order to overcome the limitations of existing fault section localization methods on fault resistance values and application scenarios, a fault section localization method for distribution networks based on synchronous phasor measurement is proposed in this paper. Methods: Firstly, the transient zero sequence equivalent network of single-phase to ground faults in the distribution network is analyzed, revealing the differences in zero-sequence current within different sections of the faulty line. At the same time, based on the zero-sequence current waveform recorded by the waveform measurement device in actual distribution network, the characteristics of the waveform in different sections in the time and frequency domains are analyzed. Furthermore, a fault feature extraction method based on wavelet packet transform is proposed to construct fault differential features for different sections. Then, the grey correlation analysis method is adopted to calculate the correlation coefficients between different sections to construct locating criteria, thereby achieving accurate locating of fault sections in distribution network. Results: The experimental results using field data indicate that the localization accuracy can reach 98.90%, and the calculation time is about 102.65 ms, which has high localization accuracy and localization efficiency. Conclusion: Through analysis and relevant experiments, it is concluded that the proposed method can accurately locate faults in actual distribution networks, and still has correct locating results for high resistance grounding faults. The effectiveness of the method has been verified.