In space refrigeration and heat pump systems, the presence of lubricating oil in mini-channel condensers introduces problems of reduced heat transfer efficiency and increased pressure drop. In this paper, the flow condensation of refrigerant R134a in a mini-channel under microgravity is investigated by numerical simulation, and the effects of lubricating oil on heat transfer and pressure drop are analyzed for different tube shapes, hydraulic diameters, and mass fluxes. It was found that as the lubricating oil concentration increases, the heat transfer coefficient decreases while the pressure gradient increases for the same vapor quality. This phenomenon is due to the fact that the presence of the lubricating oil increases the fluid viscosity and the viscous shear increases, leading to a reduction in the inertial forces and the relative velocity of the gas-liquid. Define the ratio of the condensation heat transfer coefficient of the oil-containing refrigerant to the condensation heat transfer coefficient of the pure refrigerant at the same operating condition as the “oil impact factor”. When holding the oil concentration constant, the oil impact factor increases as the mass flow rate decreases and the channel hydraulic diameter increases. Moreover, as the refrigerant vapor quality decrease, the oil impact factor also exhibits an upward trend. This study provides optimization insights for the design and development of condensers used in space refrigeration/heat pump systems.
With the development and popularization of gas-fired power generation and P2G technology, the electrical system is becoming more and more closely connected. Gas energy is a good form of energy storage or transition in integrated energy system. However, few theoretical studies conduct on the coupling development of gas network and integrated energy network from the perspective of natural gas network planning. Improper natural gas system infrastructure planning will lead to waste of resources and environmental impact. Therefore, this paper aims to improve the efficiency of gas transport from the perspective of gas pipeline network planning and promote the development of low carbon economic coupling of gas integrated system (IGES). We propose a multi-dimensional natural gas network system planning strategy that enhances the link between it and electrical system to solve how to convey natural gas from P2G station into pipelines. The strategy simulates the planning behavior of natural gas pipeline network company under the background of integrated electricity and gas system and analyzes the economic and environmental benefits of the new strategy. The results show that a feasible planning scheme can improve the economic benefits of gas network operators and reduce the carbon emissions. Based on these analyses and conclusions, recommendations are made for policy formulation and planning directions at different levels. In summary, the new gas pipe network planning strategy will help to enhance the importance of gas pipe network in the IGES and promote energy conservation and environmental protection in the energy industry.
Increasing attention is paid to the influence of microclimate factors on building energy use. However, there is limited research focusing on high-rise office buildings. This study aims to analyse the accuracy of building energy performance for high-rise office buildings by considering microclimate factors. A real-life high-rise office building located in Hong Kong was selected as the case building. One-year onsite measurement for five microclimate factors was conducted. Three scenarios were considered to evaluate the microclimate effect on building energy use. By using different weather datasets, the deviation of the total building energy use is around 3%, while the deviation of the cooling energy use can be up to 7.9%. The results emphasise the importance of considering the urban microclimate effects on energy consumption.
In the pursuit of sustainability and energy efficiency, accurate short-term prediction of HVAC energy consumption is crucial. Deep learning emerges as a promising solution for handling diverse data challenges in building HVAC systems. While deep generative learning excels in computer vision, its potential in predicting energy consumption remains largely untapped. This study first introduces a novel framework, transforming forecasting into a conditional generative problem in the temporal domain. We then propose DAF-GAN, an image inpainting-based data-driven method for Day-Ahead Forecasting of buildingsâ€™ HVAC energy consumption using multi-channel Generative Adversarial Networks (GANs). In day-ahead forecasting tasks across eleven real-world buildings, DAF-GAN exhibits relative improvements of 17% to 68% across four different error metrics compared to six traditional and deep learning models. DAF-GAN also demonstrates less bias and superior stability when applied to different buildings, holding promise for enhancing energy-efficient building automation and management.
Groundwater pollution caused by oil spill accidents has been reported occasionally, and the groundwater remediation of petroleum hydrocarbons is an important research direction. In the process of in-situ groundwater remediation, a permeable reactive barrier can effectively prevent the spread of contamination plume. However, selecting the optimal material and estimating the width remains critical and challenging problems in the design of permeable reactive barrier. Meanwhile, the site environment is also an important part to consider. In this study, aimed at the oil pollution site of a military base in South Korea, the best adsorption material was determined through batch and column experiments, and a PRB with the best width in line with the service life was designed through various design methods. In the width design, based on the material balance equation, the method of using the width of the material transport area is innovated.
Existing combined heat and power plants are seeking additional heat sinks to address challenges arising from the declining district heating demand and the increasing share of renewable energy in primary energy use in the coming decades. In the meantime, the world’s demand for sustainable fuel production keeps increasing due to the need to reduce carbon emissions and mitigate the effects of climate change. Fast pyrolysis, as a thermochemical conversion process based on widely available feedstocks such as lignocellulosic biomass, is promising to provide a long-term supply of sustainable fuels, and could be integrated into existing combined heat and power plants due to the scalability and maturity of this method. This work focuses on techno-economic analysis of integrating fast pyrolysis into existing combined heat and power plants for biofuel production. A process model of fast pyrolysis and bio-oil upgrading is established in Aspen Plus to simulate the integration process. In this work, particular attention is given to the profitability analysis based on different final fuel products(crude pyrolysis oil and upgraded bio-oil). Different hydrogen generation solutions (electrolysis, and gasification) for onsite bio-oil upgrading are also examined. This study also performs an analysis of several economic indicators, such as payback period, net present value, and internal rate of return to provide insights for the future business model development for such systems. Sensitivity analysis is also carried out to further reveal the impacts of key variables in the economic evaluation process on the system’s profitability.
This paper presents a performance investigation of a sensible thermal storage (STS) system for cooking applications. The system consists of a cooker and storage units. The cooker unit supports the pot and the storage unit stores heat from heated Duratherm-630 oil. The system’s thermal performance was tested by cooking beans and boiling water. A 1,800W heating element was used to heat the oil to 220 Â°C. It took 2 hours and 50 minutes to cook beans while charging and 160 minutes to boil 40 litres of water during discharging. The temperature in the storage unit after cooking while discharging process was 120 Â°C. This temperature range can be used to cook other types of food.
The zero-carbonization trend has accelerated the popularity of EVs due to their low-carbon emissions and energy-efficiency advantages. FCS act as both charging service operator and load aggregator. They need to benefit from providing charging service to electric vehicle users while also coordinating the charging power of EVs to prevent overloading. This paper proposes a novel approach that integrates charging right trading and charging pricing using reinforcement learning algorithms. The proposed framework takes into account the influence of charging right prices on charging demand of EV users. It employs a reinforcement learning algorithm to learn the optimal charging pricing strategy and EV charging schedule for FCS, with the aim of maximizing the benefit of FCS. Numerical experiments are conducted to demonstrate the effectiveness of the proposed method.
In the Changqing gas field, fracturing fluid plays a pivotal role in the development of tight sandstone fracturing. However, its extensive usage and single-use nature have led to environmental concerns and resource wastage. Traditional fracturing fluids lack the capability for multiple recycling, underscoring the imperative for a fracturing fluid system that not only meets performance criteria but also facilitates recyclability. This study introduces a fracturing fluid formulated from exopolysaccharides complemented with Carboxymethyl Cellulose and Benzenesulfonicacid, to address this reusability challenge. Experimental evaluations were conducted on both the fresh fracturing fluid prepared with clean water and the reusable fracturing fluid formulated with returned post-fracture fluid. Results indicate that the fluid aligns with the Changqing gas field’s stipulated criteria for apparent viscosity, gel breaking, and reservoir protection. A field trial involving 5,690 mÂ³ of fracturing fluid yielded a recovery of 5,357 mÂ³, translating to a remarkable 94.15% recycling efficiency. The potential for recycling this fluid offers substantial environmental and economic advantages, including water conservation, diminished waste fluid emissions, and the promotion of eco-friendly, sustainable production methodologies.
Advance water injection is one of the effective methods to alleviate the rapid decline of formation pressure in ultra-low permeability reservoirs, to establish an effective displacement system between oil and water wells, and to increase the production of wells. In order to make up for the influence of threshold pressure gradient and stress sensitivity which are not fully considered in the traditional advance water injection pressure calculation model, based on the material balance method, threshold pressure gradient and stress sensitivity equations are introduced, a nonlinear flow model of the relationship between the advance water injection volume and formation pressure is established, and an iterative solution calculation program is compiled. Taking Y2 ultra-low permeability reservoir in Changqing Oilfield, China, as an example, the formation pressure values under different amounts of advance water injection in the well group of this block are calculated and compared with the numerical simulation results, which are basically in agreement with each other, proving that the model for calculating the advance water injection pressure established in this paper has a high calculation accuracy. The pressure and pressure gradient distribution law in the reservoir under different advance water injection volume is further revealed. When the advance water injection volume of the well group is greater than 10,000m3, the pressure lift becomes slower, and the pressure gradient between the oil and water wells is higher than the threshold pressure gradient, which forms an effective displacement system. The study results can provide theoretical guidance for the development of advance water injection technical programs for ultra-low permeability reservoirs.