Abstract

The bio-natural gas (BNG) industry, which utilizes organic waste to produce biogas and purify it into BNG, has gained rapid development because it is in line with global carbon neutrality targets and sustainable development strategies. However, the difficulty in utilizing the carbon dioxide separated by the purification system restricts the green development of the BNG industry. Liquid CO2 is easier to store and transport compared to gaseous state, but liquefaction not only consumes power but also requires a high-grade cold source. In this research, based on a BNG station with a daily production of 5000 m3, a novel CO2 resource utilization system is proposed, which combines the waste heat recovery of CO2 compression heat with the utilization of cold energy from liquid natural gas (LNG) gasification to achieve energy saving and consumption reduction. The system consists of a two-stage CO2 cascade compression system, an organic Rankine cycle system and an LNG gasification system. A thermodynamic analysis was conducted on the system, and the results show that the ORC system effectively recover the waste heat of the CO2 cascade compression system, reducing the power output by 12.8%. When the evaporation and condensation temperatures of the ORC system are 368.15 K and 303.15 K, respectively, the cold energy recovery rate of LNG gasification reaches 62.6%. The pressurization ratio of the CO2 cascade compression system and the evaporation temperature of the ORC system have a large impact on the combined system, and the exergy analysis and parameter optimization design will be carried out subsequently. This study will provide theoretical guidance for CO2 resource utilization in BNG industry.

Abstract

As urbanization progresses, global building energy consumption is on the rise, emphasizing the need for a dependable energy consumption prediction model. This study presents a multi-stage machine learning approach comprising a clustering decomposition model (GMM), a prediction model (XGBoost), and an optimization model (PSO). Prior to clustering, the RF model evaluates the significance of various features influencing building energy consumption. GMM partitions the data into distinct clusters, while the PSO model fine-tunes the initial parameters of XGBoost. Validation is conducted using a dataset comprising 458,836 hourly records spanning three years from 20 office buildings in Shanghai, China. The average hourly energy consumption for all buildings is 79.2 kWh, but there is significant variation, with a standard deviation of 126.3 kWh. The prediction results indicate that the proposed model consistently achieves an R² exceeding 0.85 across diverse test sets, demonstrating robust accuracy and generalization capabilities. These findings offer valuable insights for future building design and energy management strategies.

Abstract

A virtual power plant (VPP) plays a key role in integrating renewable energy and responding grid frequency fluctuations caused by the variable output of renewable sources. However, correcting frequency deviations doesn’t represent maintain the power balance. VPPs must maintain stability through tertiary frequency regulation (TFR), often relying on power trading with the grid due to limited internal resources. To reduce this grid dependency, a coordinated control strategy is proposed to optimize the use of internal energy storage. It includes three methods: time-sharing to handle fluctuation timing uncertainty, demand analysis to address fluctuation power uncertainty, and resources selection to identify VPP resources for TFR participation. Simulations show that during the “longest duration of fluctuation”, the strategy effectively stabilized the VPP and reduced power trading, decreasing the grid power from 32.5 MW to 3.8 MW through coordinated control of plan adjustments, over-limit power regulation. In the “highest power deviation of fluctuation” coordinated control of plan adjustments and over-limit power regulation reduce power trading from 43 MW to 9.7 MW and energy traded from 215 MWh to 48.5 MWh—a 77.44% reduction.

Abstract

In the present era, electric vehicles are progressively gaining popularity on a global scale. The objective of using a battery thermal management system (BTMS) is to ensure that the power battery pack maintains a controlled temperature range during both charging and discharging processes. This paper aims to enhance the performance of the BTMS by incorporating topologically optimized fins into the composite phase-change material (PCM) and liquid cooling coupling BTMS. Specifically, paraffin with expanded graphite (EG) and foam aluminum nitride as composite phase-change materials were selected. Utilizing COMSOL Multiphysics software, topology optimization was employed to determine the material distribution within the design domain. Subsequently, a 3D model was constructed and the performances of three systems—without fins, with rectangular fins, and with topology-optimized fins—were compared. The results show that after 720 s of discharging at a 5C charge/discharge rate, the average temperature of the battery with the topology optimized fin system is 15.16 °C lower than that of the battery without fins and 1.32 °C lower than that of the battery with rectangular fins. This indicates that the system with topology optimized fins has better heat transfer efficiency

Abstract

The Building Integrated Photovoltaic Thermal (BIPVT) module is a composite module that combines a photovoltaic module and a solar thermal collector module and has the advantage of producing power and heat at the same time. BIPVT module is affected by electric generation performance by heat collection performance. It is important to know the correlation between changes in power generation performance according to temperature changes of the BIPVT module. This study conducted a comparative experiment on temperature and power characteristics between different types of BIPVT modules without a glass cover. Three BIPVT modules with different thermal collection methods were installed in the mock-up facility at a vertical angle of 90Ëš vertically facing to the south. As the experimental result, the total efficiency of BIPVT module was highest in Case (1) at 34.8%, followed by Case (2) at 19.8%, Case (3) at 17.2%, and Reference at 10.9%.

Abstract

In recent years, rapid increase of woody biomass power plants creates huge demand for fuelwood. Further expanding the use of forest residues requires cost reduction of collecting them to meet the demand. On the other hand, large drones with a payload capacity of 200 kg or more have been developed. They have a possibility to expand the forest area where timber can be economically logged using drones, thereby supply of fuelwood can increase. In this study, we present conditions in the forest where drone logging should be used, including steep terrain and long distances from roads, followed by evaluating economic efficiency of forestry operation under the conditions. The results show that the drone logging can be used economically in most of the sub-compartments with the conditions. Amount of forest residues available can increase more than 60% by applying drone logging. The energy obtained the residues covers 29% of the electricity demand in the study area. The results suggest drone logging system can contribute significantly to decarbonization of the region.

Abstract

This paper proposes a structured evacuation simulator framework that incorporates various factors influencing evacuation behavior during flood disasters. The framework aims to advance the development of cyber-physical systems for disaster damage by simulating multiple factors, emphasizing their interaction, and incorporating information factors. The proposed framework consists of four main components: the main loop, module sets, variable blocks, and interactions with the external environment. The main loop controls the state of the evacuees and represents their state transitions. The psychological and environmental variables representing the evacuees’ state and situation are stored in the variable blocks, and the module sets describe the rules for updating these variables. The proposed framework adopts a federation strategy to realize interaction with other simulators and systems. By integrating the knowledge from previous evacuation simulation research and adapting to a society with advanced information technology, this study contributes to the development of comprehensive and dynamic evacuation simulators for flood disasters. The proposed structured evacuation simulator framework offers flexibility and extensibility in modeling evacuation behavior, facilitating the analysis and planning of evacuation strategies in the context of cyber-physical systems for disaster damage reduction.

Abstract

Communication networks often experience failures during natural disasters such as floods, making it difficult for affected individuals to access critical information. This research proposes a power failure emulator that reproduces the interdependencies between communication failures and power supply during flood events. The emulator models the behavior of ground- based substations and determines the power supply status in flood-affected areas. It is designed to work in coordination with multiple interdependent simulators and systems, including a flood analysis simulator, an evacuation simulator, a communication failure emulator, and an evacuation route information system, using a federation strategy. The power failure emulator exchanges information with other components via a federation bus, communicating the state of power supply to the communication failure emulator, thus reproducing the impact on communication networks. The objective is to generate more realistic scenarios that consider the interdependencies between power supply and communication networks during natural disasters, enabling the analysis of the impact of communication failures on information access for affected individuals and facilitating the development of more effective disaster response strategies.

Abstract

In the current work, a numerical works for oxy-methane (CH4/CO2/O2) partially premixed flames were conducted to investigate the complex interactions between different flame features and operational factors by exploring a premixed oxymethane flame within a dual annular counter-rotating swirl (DACRS). The numerical model is validated against experimental temperature along the burner axis. The effect of equivalence ratio, oxygen fractions, and flow/flame interactions on the temperature distribution and flame structure were studied. The burner is divided internally into two annular tubes. The secondary gas stream is routed via the gap between the inner and outer tubes, while the primary gas stream is contained within the inner (pilot) tube. The velocity ratio of 3.0 is consistently maintained by the primary and secondary streams. The secondary stream’s velocity is fixed at 1.667 m/s, while the primary stream’s velocity is set at 5 m/s. Using this configuration, the relationships between flow and flame dynamics are investigated for a variety of equivalency ratios between different combinations of primary and secondary oxygen fractions (primary being 25%, and secondary being 39%). While the secondary equivalency ratio (𝜑s) fluctuates, the primary equivalency ratio (𝜑p) stays constant at 0.9. The results show that equivalence ratio changes have a significant impact on flame shape, reactivity, stability, and burner operability, whereas oxygen fraction changes have a significant impact on flame dynamics, recirculation zone formation, and temperature distribution.

Abstract

As a core component of Heating, Ventilation, and Air Conditioning (HVAC) systems, the Air Handling Unit (AHU) significantly contributes to energy consumption. With the increasing demand for reduced carbon emissions and enhanced energy efficiency, optimizing the performance of fans within AHUs to lower energy usage has become a primary focus of research. This study aims to investigate the optimal fan type and combination format that can promote higher performance in AHUs. Firstly, groups of experiments were conducted to evaluate the performance of the Electronically Commutated (EC) fans equipped with spiral guide vanes and conventional EC fans. Secondly, fluid dynamic models of these fans’ applications in AHU were developed and simulated through Computational Fluid Dynamics (CFD). Finally, the performances comparisons were carried out among AHUs using EC fans with spiral guide vanes and those using traditional EC fans with different layouts. Results revealed that the EC fan with spiral guide vanes exhibited higher energy efficiency, lower energy consumption, and greater pressure head compared to conventional EC fans with the same blade design and dimensions. Furthermore, an array configuration of EC fans with spiral guide vanes generated fewer vortices in the AHU air channel. The pressure loss regions were reduced so that the air velocity in the AHU outlet was increased. Therefore, the selected fans in an array arrangement are more efficient to overcome air flow resistance in an AHU, simultaneously reducing its energy consumption. These findings provide valuable insights into the potential benefits of employing spiral guide vane technology to enhance the energy efficiency and operational performance of AHUs.