To integrate more renewable energy into the power grid, large-scale thermal power plants have to extend their operating ranges and participating in deep peak shaving. In order to improve the thermal economy of large-scale thermal power plants participating in deep peak shaving, and to determine the performance of a thermal system under different conditions, a method of modeling for the performance prediction of large-scale thermal power plants in deep peak shaving is proposed. In the algorithm design of the model, a three-layer iterative cycle logic is constructed, and the coupling relationship between the parameters of the thermal system is analyzed from the mechanism level. All of the steam water parameters and the correction values of the flow rate at all levels of the system after the parameter disturbance are obtained. The algorithm can simulate the response of a thermal power plant under load variation and operation parameter variation. Compare the error between the data given by the prediction model and the test, the accuracy of the proposed prediction model is verified. When the unit participates in deep peak shaving, the prediction model is used to analyze the relative deviation of the unit thermal efficiency caused by cycle parameters and energy efficiency of equipment. It provides a date basis for the performance evaluation and multi-parameter coupling optimization. The research results can be used to determine the operation mode and equipment transformation scheme.

The structure of an integrated energy system is complex. Thermoeconomics can play a significant role in the analysis of IES because it makes up for the deficiency of traditional thermodynamic analysis and provides new information on the cost and energy conversion efficiency. When using thermoeconomics to analyze the energy efficiency of an IES, one key issue that needs to be solved is how to transfer irreversible loss across thermal cycles, so that the mechanism of system performance degradation can be fully revealed. To this end, an irreversible cost and exergy cost integrated analysis method based on improved thermoeconomics is proposed, in which the cumulative and transmission impact of irreversible loss across thermal cycles is evaluated using linear transformation of matrix. A case study on a 389MW combined cooling, heating, and power IES demonstrates the effectiveness of the proposed approach. The proposed approach can reveal the key links impairing the overall energy efficiency and transfer of irreversible loss across thermal cycles. The approach can be extended to various types of IES to provide directions for the assessment and optimization of the system.

In this study, a ground-based washing inerting (GBWI) method was proposed, and the application of GBWI in the field of fire prevention and explosion suppression of unmanned aerial vehicle (UAV) fuel tanks was studied using a volume of fluid (VOF) two-phase flow model at a given typical flight envelope. The variation in oxygen concentration in tank ullage during flight was calculated considering the entrance of ambient air and the escape of dissolved oxygen from the fuel. The results indicate that the oxygen concentration in the ullage increases with increasing initial oxygen concentration in the ullage and the initial fuel load after GBWI. In the climb and cruise stages, the oxygen concentration in the ullage increases slowly, while in the tactical descent stage, the oxygen concentration in the ullage increases rapidly, easily exceeding the limiting oxygen concentration (LOC) of aviation fuel combustion. To expand the application range of GBWI, an optimization scheme of nitrogen filling protection was proposed so that the GBWI could meet the requirements of an inert tank at different fuel loads and initial oxygen concentrations in the ullage. Compared with a traditional on-board inert gas generation system (OBIGGS), the optimized GBWI method could greatly reduce the fuel compensation loss and improve the maneuverability of UAVs at the same time.

This study investigates the dynamics of mass transfer between gas and liquid during the fuel scrubbing inerting process, utilizing a mixed inert gas (MIG) composed of CO₂, N₂, and trace amounts of O₂. The goal is to lower oxygen concentrations in aircraft fuel tanks, thereby reducing the risk of explosions. The experiments were conducted on a fuel scrubbing inerting platform, where an MIG was utilized to deoxygenate aviation fuel. Changes in the oxygen concentration in the ullage (OCU) and the dissolved oxygen concentration in the fuel (DOCF) were measured during the scrubbing process. Validated by these experimental data, Computational Fluid Dynamics (CFD) simulations demonstrated the reliability of the model. The discrepancies between CFD predictions and experimental measurements were 4.11% for OCU and 5.23% for DOCF. The influence of the MIG bubble diameter, MIG flow rate, and fuel loading rate on DOCF, gas holdup (GH), and the oxygen volumetric mass transfer coefficient (OVMTC) was comprehensively examined. The results reveal that larger MIG bubble diameters lead to an increased DOCF but reduced GH and OVMTC. In contrast, a higher MIG flow rate decreases DOCF while boosting GH and OVMTC. Additionally, a greater fuel loading rate increases DOCF but decreases GH and OVMTC. These findings offer important insights for optimizing fuel scrubbing inerting systems, underscoring the necessity of selecting suitable operating parameters to enhance oxygen displacement and ensure aircraft safety.

Modern aircraft fuel tank explosion protection relies critically on inerting efficiency. This study presents and investigates a novel scrubbing deoxygenation strategy utilizing mixed inert gas (MIG) generated by oxygen-consuming inerting systems for high-vapor-pressure RP5 aviation fuel. A high-fidelity computational fluid dynamics (CFD) numerical framework was established using the Eulerian–Eulerian two-fluid model coupled with Higbie’s penetration theory, with experimental validation ensuring computational accuracy (maximum errors for ullage oxygen concentration and dissolved oxygen in fuel controlled within 4.11% and 5.23%, respectively). The research systematically elucidates the influence mechanisms of bubble diameter, MIG temperature, and superficial gas velocity on mass transfer characteristics (oxygen mass transfer coefficient and volumetric mass transfer coefficient). Key findings reveal that reducing bubble diameter achieves localized polarization of mass transfer intensity in the central plume region through an “area-velocity” synergistic effect, with the oxygen volumetric mass transfer coefficient at 1.0 mm diameter increasing by 51.3% compared to 2.5 mm. The performance enhancement from superficial gas velocity primarily stems from the “area multiplication effect” triggered by surging gas holdup. Notably, MIG temperature exhibits a unique three-stage reversal characteristic of “kinetically dominated early stage, thermodynamically controlled late stage” on deoxygenation performance. These results provide critical physical foundations for the forward design of next-generation multifunctional onboard inerting systems.

The establishment of a cost model for complex energy systems based on thermoeconomics can provide technical and economic evaluation indicators for complex energy systems. At the same time, to integrate more renewable energy into the grid, complex energy systems must participate in deep peak shaving. To evaluate the technical-economic performance of complex energy systems involved in deep peak shaving, a novel thermoeconomic cost construction method is proposed based on the production structure diagram, using the gas-steam combined cycle system as an example. These can effectively avoid the derivation error of high-dimensional models, improve the modeling and calculation speed, and obtain the variation trend of system thermoeconomics cost under load changes and operating parameter changes. The results show that the external and internal factor can change the power generator thermoeconomic cost. The power generation cost of the system increases with increasing natural gas price and environmental temperature. When the compressor pressure ratio increases, the power generation cost of the system also increases. At 100% load, the power generation cost reaches its lowest value when the exhaust temperature is equal to 615?C.