Abstract

To catch up with the sustainability transition progress, the global capacity of PV system is predicted to grow dramatically in the following decades, including high-latitude regions. To effectively use the urban space resource for PV power generation in the high-latitude areas, wall-mounted PV system is becoming an attractive solution. This paper evaluates the potential of wall-mounted PV system in the high-latitude areas with a case study in Swedish contexts through a PV power generation model by considering weather conditions (including snowfall, icing and melting), orientation, and economics. The key performances are compared with rooftop fixed-tilt angle PV systems in Swedish contexts. Although the annual power generation of the wall-mounted PV system is around 5% lower under heavy snow conditions, its power generation during the snow season (from October to April) increases significantly. In general, the power generation in March almost doubled and the increase could be more than 25% in April. Therefore, wall-mounted PV system can contribute to the winter electricity supply in high-latitude areas, when the electricity price is high.

Abstract

This paper employs a 3D numerical simulation to investigate the effect of various non-uniform longitudinal fins at the bottom region of a rectangular container on natural convection and RT42 phase change material (PCM) melting characteristics. Using a container with rectangular fins as a baseline, the influence of the geometric structure and arrangement of the fins on PCM melting characteristics is explored by varying the heights of the left (Ll) and right (Lr) non-uniform fins. The results indicate that adding non-uniform longitudinal fins at the bottom enhances the heat transfer of PCM at the bottom and corners of the container, significantly reducing melting time and improving temperature uniformity and heat storage rate. Optimal performance is achieved when Ll = 3 mm and Lr = 7 mm, with a reduction in melting time by 27.5% and an increase in heat storage rate by 37.3% compared to the baseline case.

Abstract

Heat transfer characteristics (HTC) of supercritical CO2 (SCO2) is crucial for many applications in the field of energy conversion. However, there are very few studies concerning the effects of vibration on the HTC of SCO2. In this paper, the effects of transverse vibration on the HTC of SCO2 flowing upward within a vertical tube (d=4.57 mm, L=1000 mm) are investigated experimentally and compared with a horizontal tube. The results reveal that vibration mitigates heat transfer deterioration (HTD) in the vertical tube, reduces the second peak of wall temperature along the channel significantly, and enhances heat transfer coefficient (htc). Vibration is more effective in enhancing heat transfer in the vertical tube compared to the horizontal tube. The vibration intensification mainly acts in the region before the mainstream enthalpy (hb) reaches the pseudo-critical enthalpy (hpc). Based on pseudo-boiling theory, vibration enhances heat transfer by inhibiting the growth of near-wall gas-like film and the temperature gradient inside the gas-like film.

Abstract

Unlike conventional fractured-vuggy carbonate reservoirs, the gas condensate reservoir in fault zone of Shunbei belongs to a thick reservoir controlled by faults, with a gas column heights of up to 400-600 meters and gravity segregation. Clarifying the mechanism of gas injection development in the carbonate gas condensate reservoirs controlled by faults can provide important theoretical guidance for the development plans of gas injection and pressure maintenance. Firstly, for the purpose of miscible flooding, enhancing condensate oil recovery, and CCUS, CO2 was chosen as the injection medium. Then, a geological model was established based on a typical well group in Fault Zone of Shunbei, and the best gas injection location was selected by considering the gravity segregation and combining the mechanism of gas injection to reducing condensate damage in gas condensate reservoirs. Finally, the optimization of gas injection was conducted and the optimal injection timing, injection strategy and injection rate was selected. The results indicate that:
1. Compared to bottom gas injection, top gas injection is the optimal location to obtain a better recovery rate of condensate oil for the gas condensate reservoir in fault zone of Shunbei.
2. The optimal gas injection timing is when the reservoir pressure drops to the dew point pressure.
3. The optimal gas injection strategy involves continuous gas injection in the early stage to maintain pressure, periodic gas injection in the mid-term, and depletion development in the later stage.
4. The optimal gas injection rate for the well group in Shunbei area is 350,000 cubic meters of CO2 per day.
In the actual development of gas condensate reservoirs, gas injection and development plans should be developed based on the gas injection mechanism and considering the feasibility and economics This study can provide reference for the efficiency of gas injection for enhancement of condensate recovery in a gas condensate reservoir.

Abstract

For low permeability reservoirs, water-flooding development is usually adopted, which leads to induced fractures near the wellbore, increasing reservoir heterogeneity, making the residual oil distribution more complex, and significantly increasing development costs. This study focuses on low-permeability reservoirs. Based on well test pressure monitoring data from production sites and their characteristic patterns on log-log pressure response plots, and considering the characteristics of water injection-induced fracture composite zones, four typical models and their corresponding water flooding types were identified. Through analyzing the dynamic mechanisms of opening and closing of water injection-induced fractures, a new method for interpreting the opening pressure of these fractures was proposed. This method accurately characterizes the opening pressure thresholds of water injection-induced fractures under different classification models. Subsequently, several water injection wells in the J Oilfield were selected to verify the opening pressure thresholds and analyzed the opening pressure thresholds for water injection-induced fractures corresponding to different reservoir depths, permeabilities, and the four classification models. The results show that this method of interpreting the opening pressure of induced fractures based on well test pressure monitoring data exhibits high rationality and accuracy in characterizing the opening pressure thresholds of induced fractures. The opening pressure of induced fractures in Mode 2 and Mode 3 is higher than that in Mode 4; with increasing depth, the opening pressure of induced fractures tends to increase; and as the interpreted permeability from well testing increases, the opening pressure of induced fractures tends to decrease.

Abstract

The presence of bio-oil distillation sludge (DS) disrupts biomass refining and poses health risks. This study investigates DS utilization in industrial bio-oil refining through co-pyrolysis with walnut shell (WS). Char characterization elucidates structural changes induced by co-pyrolysis. Observations show increased DS ratios smoothened the pleated structure of W3D1, with heightened graphitized structure observed at higher DS ratios through Raman analysis. Gasification indices (R0.5 and R0.9) indicate significant enhancements through co-pyrolysis. Mineral composition analysis revealed silicon in DS reduced ash deposition, while WS blending increased deposition risks due to potassium and calcium content. Investigation into the synergistic relationship between biochar’s carbonaceous structure parameters and gasification indices emphasized stronger correlations with R0.9, indicating pronounced synergy in later gasification stages.

Abstract

Achieving a balance between cost-effectiveness and high performance in hydrogen storage materials is a significant challenge. This study presents a novel method for synthesizing hollow porous carbon spheres with a cluster-like structure using economical materials such as biogas slurry, starch, and ferric oxide. Through a systematic analysis of activation temperatures and ratios, optimal conditions were identified. The resulting materials, CS850-4.5 and CS800-4, achieved high gravimetric H2 uptake of 4.5 wt% (77 K, 50 bar) and volumetric H2 uptake of 25.9 g/L (77 K, 30 bar), respectively. This approach offers dual advantages in both performance and economic viability.

Abstract

Solar energy systems suffer from the unstable nature of solar irradiance. This paper proposes a novel approach to predict solar irradiance using a sequential model with a Long Short-Term Memory (LSTM) network. The model uses the mean squared error (MSE) loss function and the Adam optimization algorithm to provide robustness to noise and efficient computation of gradients. The model aims to forecast solar irradiance for 2023 in Dhaka, Bangladesh, using weather data and sunlight duration data from NASA Power and Data. GISS NASA. The dataset includes daily records from 2000-2023. The proposed LSTM model achieves 5.47% more accuracy than RandomForestRegressor in terms of root mean squared error (RMSE) to predict 1 year of irradiance data, indicating a substantial degree of precision in forecasting the objective variable. The results corroborate previous research highlighting the advantages of utilizing temporal dependencies and historical data to achieve accurate solar energy forecasts.

Abstract

The integration of machine learning and deep learning technologies has revolutionized solar power production by addressing challenges such as variability and unpredictability. This paper explores the application of Explainable AI (XAI) through the proposed SPXAI model to enhance the efficiency and reliability of solar energy systems. SPXAI collects extensive power production data from solar farms and employs machine learning and deep learning models to analyze this data on an hourly basis. This analysis provides clear insights into predictions, identifies influential factors, and offers rule-based explanations for complex model decisions. Additionally, SPXAI makes real-time, data-driven decisions to optimize solar panel performance, such as adjusting panel orientations, scheduling predictive maintenance, and refining energy storage and distribution strategies. This approach enhances transparency and reliance on AI-driven recommendations, reducing operational costs and increasing solar power production reliability.

Abstract

In this paper, a sequential model combining two-dimensional mechanical deformation and three-dimensional non-isothermal deformation was developed to investigate the combined effects of assembly pressure and gas diffusion layer (GDL) thickness on the structure and performance of a high-temperature proton exchange membrane fuel cell (HT-PEMFC). Through the utilization of the response surface methodology (RSM), it was determined that the HT-PEMFC exhibited its optimal overall performance when the assembly pressure was set at 1.38 MPa and the GDL thickness was 0.375 mm. Additionally, the study also delved into the effects of assembly pressure and GDL thickness on various aspects of the HT-PEMFC, including polarization curves, hydrogen distribution, oxygen distribution, and temperature distribution. It was observed that the temperature in the gas channel was consistently higher than in other solid regions.