In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for n...In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network optimization.This study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic RESs.The primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss mitigation.Additionally,a carbon tax is included in the objective function to reduce carbon emissions.Thorough scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal solutions.Simulation results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution quality.Notably,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)effectively.This research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local minima.GBBLCO emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.展开更多
As the demand for more efficient and adaptable power distribution systems intensifies, especially in rural areas, innovative solutions like the Capacitor-Coupled Substation with a Controllable Network Transformer (CCS...As the demand for more efficient and adaptable power distribution systems intensifies, especially in rural areas, innovative solutions like the Capacitor-Coupled Substation with a Controllable Network Transformer (CCS-CNT) are becoming increasingly critical. Traditional power distribution networks, often limited by unidirectional flow capabilities and inflexibility, struggle to meet the complex demands of modern energy systems. The CCS-CNT system offers a transformative approach by enabling bidirectional power flow between high-voltage transmission lines and local distribution networks, a feature that is essential for integrating renewable energy sources and ensuring reliable electrification in underserved regions. This paper presents a detailed mathematical representation of power flow within the CCS-CNT system, emphasizing the control of both active and reactive power through the adjustment of voltage levels and phase angles. A control algorithm is developed to dynamically manage power flow, ensuring optimal performance by minimizing losses and maintaining voltage stability across the network. The proposed CCS-CNT system demonstrates significant potential in enhancing the efficiency and reliability of power distribution, making it particularly suited for rural electrification and other applications where traditional methods fall short. The findings underscore the system's capability to adapt to varying operational conditions, offering a robust solution for modern power distribution challenges.展开更多
In this study, the rapidity distribution, collective flows, and nuclear stopping power in ^(197)Au+^(197)Au collisions at intermediate energies were investigated using the ultrarelativistic quantum molecular dynamics(...In this study, the rapidity distribution, collective flows, and nuclear stopping power in ^(197)Au+^(197)Au collisions at intermediate energies were investigated using the ultrarelativistic quantum molecular dynamics(UrQMD) model with GEMINI++ code. The UrQMD model was adopted to simulate the dynamic evolution of heavy-ion collisions, whereas the GEMINI++ code was used to simulate the decay of primary fragments produced by UrQMD. The calculated results were compared with the INDRA and FOPI experimental data. It was found that the rapidity distribution, collective flows, and nuclear stopping power were affected to a certain extent by the decay of primary fragments, especially at lower beam energies. Furthermore, the experimental data of the collective flows and nuclear stopping power at the investigated beam energies were better reproduced when the sequential decay effect was included.展开更多
This paper presents an analysis of the power flow within the Northern Interconnected Grid of Cameroon. The Newton-Raphson method has been performed, known for its accuracy, under MATLAB software, to model and solve co...This paper presents an analysis of the power flow within the Northern Interconnected Grid of Cameroon. The Newton-Raphson method has been performed, known for its accuracy, under MATLAB software, to model and solve complex power flow equations. This study simulates a series of outage scenarios to evaluate the responsiveness of the grid. The results obtained underline the crucial importance of reactive power management and highlight the urgent need to consolidate the grid infrastructure of North Cameroon. To increase grid resilience and stability, the paper recommends the strategic integration of renewables and the development of interconnections with other power grids. These measures are presented as viable solutions to meet current and future energy distribution challenges, ensuring a reliable and sustainable power supply for Cameroon.展开更多
There are issues with flexible DC transmission system such as a lack of control freedom over power flow.In order to tackle these issues,a DC power flow controller(DCPFC)is incorporated into a multi-terminal,flexible D...There are issues with flexible DC transmission system such as a lack of control freedom over power flow.In order to tackle these issues,a DC power flow controller(DCPFC)is incorporated into a multi-terminal,flexible DC power grid.In recent years,a multi-port DC power flow controller based on a modular multi-level converter has become a focal point of research due to its simple structure and robust scalability.This work proposes a model predictive control(MPC)strategy for multi-port interline DC power flow controllers in order to improve their steady-state dynamic performance.Initially,the mathematical model of a multi-terminal DC power grid with a multi-port interline DC power flow controller is developed,and the relationship between each regulated variable and control variable is determined;The power flow controller is then discretized,and the cost function and weight factor are built with numerous control objectives.Sub module sorting method and nearest level approximation modulation regulate the power flow controller;Lastly,theMATLAB/Simulink simulation platformis used to verify the correctness of the establishedmathematicalmodel and the control performance of the suggestedMPC strategy.Finally,it is demonstrated that the control strategy possesses the benefits of robust dynamic performance,multiobjective control,and a simple structure.展开更多
Wind-farm flow control stands at the forefront of grand challenges in wind-energy science.The central issue is that current algorithms are based on simplified models and,thus,fall short of capturing the complex physic...Wind-farm flow control stands at the forefront of grand challenges in wind-energy science.The central issue is that current algorithms are based on simplified models and,thus,fall short of capturing the complex physics of wind farms associated with the high-dimensional nature of turbulence and multiscale wind-farm-atmosphere interactions.Reinforcement learning(RL),as a subset of machine learning,has demonstrated its effectiveness in solving high-dimensional problems in various domains,and the studies performed in the last decade prove that it can be exploited in the development of the next generation of algorithms for wind-farm flow control.This review has two main objectives.Firstly,it aims to provide an up-to-date overview of works focusing on the development of wind-farm flow control schemes utilizing RL methods.By examining the latest research in this area,the review seeks to offer a comprehensive understanding of the advancements made in wind-farm flow control through the application of RL techniques.Secondly,it aims to shed light on the obstacles that researchers face when implementing wind-farm flow control based on RL.By highlighting these challenges,the review aims to identify areas requiring further exploration and potential opportunities for future research.展开更多
Work on dynamic topology optimization of engineering structures for vibration suppression has mainly addressed the maximization of eigenfrequencies and gaps between consecutive eigenfrequencies of free vibration, mini...Work on dynamic topology optimization of engineering structures for vibration suppression has mainly addressed the maximization of eigenfrequencies and gaps between consecutive eigenfrequencies of free vibration, minimization of the dynamic compliance subject to forced vibration, and minimization of the structural frequency response. A dynamic topology optimization method of bi-material plate structures is presented based on power flow analysis. Topology optimization problems formulated directly with the design objective of minimizing the power flow response are dealt with. In comparison to the displacement or velocity response, the power flow response takes not only the amplitude of force and velocity into account, but also the phase relationship of the two vector quantities. The complex expression of power flow response is derived based on time-harmonic external mechanical loading and Rayleigh damping. The mathematical formulation of topology optimization is established based on power flow response and bi-material solid isotropic material with penalization(SIMP) model. Computational optimization procedure is developed by using adjoint design sensitivity analysis and the method of moving asymptotes(MMA). Several numerical examples are presented for bi-material plate structures with different loading frequencies, which verify the feasibility and effectiveness of this method. Additionally, optimum results between topological design of minimum power flow response and minimum dynamic compliance are compared, showing that the present method has strong adaptability for structural dynamic topology optimization problems. The proposed research provides a more accurate and effective approach for dynamic topology optimization of vibrating structures.展开更多
A general model of flexible isolation systems which involves both the passive and active control factors is established by inserting actuators into an passive isolation system. And the power flow transmission function...A general model of flexible isolation systems which involves both the passive and active control factors is established by inserting actuators into an passive isolation system. And the power flow transmission function in such a system as with multi disturbance, multi mounts, passive isolators and actuators is deduced. By means of the numerical simulation method, the influence of actuators on power flow transmission characteristic is studied. And as a conclusion, the passive active synthetic control strategy of power flow is summarized.展开更多
For demonstrating a multiterminal voltage-source converter(VSC)-based high-voltage DC(HVDC)(VSCHVDC) project, this study puts forward a technical route for calculating the power flow in a 500-kV VSC-HVDC power grid in...For demonstrating a multiterminal voltage-source converter(VSC)-based high-voltage DC(HVDC)(VSCHVDC) project, this study puts forward a technical route for calculating the power flow in a 500-kV VSC-HVDC power grid in comparison with that of an AC power grid. The Jacobian matrix used in the power-flow calculation was deduced through methods such as Newton–Laphson iteration and Taylor series expansion. Further, the operation effect of powerflow calculation on a true bipolar VSC-HVDC power grid was analyzed briefly. The elements of the Jacobian matrix corresponding to VSC were studied under the mode of droop control and the control strategy of VSC-HVDC power grid was analyzed in detail. The power-flow calculation model for VSC-HVDC power grid of the master–slave control mode was simplified using the PQ decomposition method of the power-flow calculation of an AC power grid. Moreover, a four-terminal model of the Zhangbei VSC-HVDC demonstration project was established and tested on MATLAB. The simulation results under two kinds of operating conditions were analyzed and compared to the results of BPA; the deviation between the power-flow results was studied. The results show that the proposed calculation method can provide a feasible support for calculating the power flow in VSC-HVDC grids.展开更多
Efficiently modulating the velocity distribution and flow pattern of non-Newtonian fluids is a critical challenge in the context of dual shaft eccentric mixers for process intensification,posing a significant barrier ...Efficiently modulating the velocity distribution and flow pattern of non-Newtonian fluids is a critical challenge in the context of dual shaft eccentric mixers for process intensification,posing a significant barrier for the existing technologies.Accordingly,this work reports a convenient strategy that changes the kinetic energy to controllably regulate the flow patterns from radial flow to axial flow.Results showed that the desired velocity distribution and flow patterns could be effectively obtained by varying the number and structure of baffles to change kinetic energy,and a more uniform velocity distribution,which could not be reached normally in standard baffle dual shaft mixers,was easily obtained.Furthermore,a comparative analysis of velocity and shear rate distributions is employed to elucidate the mechanism behind the generation of flow patterns in various dual-shaft eccentric mixers.Importantly,there is little difference in the power number of the laminar flow at the same Reynolds number,meaning that the baffle type has no effect on the power consumption,while the power number of both unbaffle and U-shaped baffle mixing systems decreases compared with the standard baffle mixing system in the transition flow.Finally,at the same rotational condition,the dimensionless mixing time of the U-shaped baffle mixing system is 15.3%and 7.9%shorter than that of the standard baffle and the unbaffle mixing system,respectively,which shows the advantage of the U-shaped baffle in stirring rate.展开更多
A modelling study is performed to compare the plasma flow and heat transfer characteristics of low-power arc-heated thrusters (arcjets) for three different propellants: hydrogen, nitrogen and argon. The all-speed S...A modelling study is performed to compare the plasma flow and heat transfer characteristics of low-power arc-heated thrusters (arcjets) for three different propellants: hydrogen, nitrogen and argon. The all-speed SIMPLE algorithm is employed to solve the governing equations, which take into account the effects of compressibility, Lorentz force and Joule heating, as well as the temperature- and pressure-dependence of the gas properties. The temperature, velocity and Mach number distributions calculated within the thruster nozzle obtained with different propellant gases are compared for the same thruster structure, dimensions, inlet-gas stagnant pressure and arc currents. The temperature distributions in the solid region of the anode-nozzle wall are also given. It is found that the flow and energy conversion processes in the thruster nozzle show many similar features for all three propellants. For example, the propellant is heated mainly in the near-cathode and constrictor region, with the highest plasma temperature appearing near the cathode tip; the flow transition from the subsonic to supersonic regime occurs within the constrictor region; the highest axial velocity appears inside the nozzle; and most of the input propellant flows towards the thruster exit through the cooler gas region near the anode-nozzle wall. However, since the properties of hydrogen, nitrogen and argon, especially their molecular weights, specific enthMpies and thermal conductivities, are different, there are appreciable differences in arcjet performance. For example, compared to the other two propellants, the hydrogen arcjet thruster shows a higher plasma temperature in the arc region, and higher axial velocity but lower temperature at the thruster exit. Correspondingly, the hydrogen arcjet thruster has the highest specific impulse and arc voltage for the same inlet stagnant pressure and arc current. The predictions of the modelling are compared favourably with available experimental results.展开更多
Power flow calculation is the basis of power grid planning and many system analysis tasks require convergent power flow conditions.To address the unsolvable power flow problem caused by the reactive power imbalance,a ...Power flow calculation is the basis of power grid planning and many system analysis tasks require convergent power flow conditions.To address the unsolvable power flow problem caused by the reactive power imbalance,a method for adjusting reactive power flow convergence based on deep reinforcement learning is proposed.The deep reinforcement learning method takes switching parallel reactive compensation as the action space and sets the reward value based on the power flow convergence and reactive power adjustment.For the non-convergence power flow,the 500 kV nodes with reactive power compensation devices on the low-voltage side are converted into PV nodes by node type switching.And the quantified reactive power non-convergence index is acquired.Then,the action space and reward value of deep reinforcement learning are reasonably designed and the adjustment strategy is obtained by taking the reactive power non-convergence index as the algorithm state space.Finally,the effectiveness of the power flow convergence adjustment algorithm is verified by an actual power grid system in a province.展开更多
基金supported by the Deanship of Postgraduate Studies and Scientific Research at Majmaah University in Saudi Arabia under Project Number(ICR-2024-1002).
文摘In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network optimization.This study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic RESs.The primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss mitigation.Additionally,a carbon tax is included in the objective function to reduce carbon emissions.Thorough scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal solutions.Simulation results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution quality.Notably,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)effectively.This research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local minima.GBBLCO emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.
文摘As the demand for more efficient and adaptable power distribution systems intensifies, especially in rural areas, innovative solutions like the Capacitor-Coupled Substation with a Controllable Network Transformer (CCS-CNT) are becoming increasingly critical. Traditional power distribution networks, often limited by unidirectional flow capabilities and inflexibility, struggle to meet the complex demands of modern energy systems. The CCS-CNT system offers a transformative approach by enabling bidirectional power flow between high-voltage transmission lines and local distribution networks, a feature that is essential for integrating renewable energy sources and ensuring reliable electrification in underserved regions. This paper presents a detailed mathematical representation of power flow within the CCS-CNT system, emphasizing the control of both active and reactive power through the adjustment of voltage levels and phase angles. A control algorithm is developed to dynamically manage power flow, ensuring optimal performance by minimizing losses and maintaining voltage stability across the network. The proposed CCS-CNT system demonstrates significant potential in enhancing the efficiency and reliability of power distribution, making it particularly suited for rural electrification and other applications where traditional methods fall short. The findings underscore the system's capability to adapt to varying operational conditions, offering a robust solution for modern power distribution challenges.
基金partly supported by the National Natural Science Foundation of China (Nos. U2032145 and 11875125)the National Key Research and Development Program of China (No. 2020YFE0202002)。
文摘In this study, the rapidity distribution, collective flows, and nuclear stopping power in ^(197)Au+^(197)Au collisions at intermediate energies were investigated using the ultrarelativistic quantum molecular dynamics(UrQMD) model with GEMINI++ code. The UrQMD model was adopted to simulate the dynamic evolution of heavy-ion collisions, whereas the GEMINI++ code was used to simulate the decay of primary fragments produced by UrQMD. The calculated results were compared with the INDRA and FOPI experimental data. It was found that the rapidity distribution, collective flows, and nuclear stopping power were affected to a certain extent by the decay of primary fragments, especially at lower beam energies. Furthermore, the experimental data of the collective flows and nuclear stopping power at the investigated beam energies were better reproduced when the sequential decay effect was included.
文摘This paper presents an analysis of the power flow within the Northern Interconnected Grid of Cameroon. The Newton-Raphson method has been performed, known for its accuracy, under MATLAB software, to model and solve complex power flow equations. This study simulates a series of outage scenarios to evaluate the responsiveness of the grid. The results obtained underline the crucial importance of reactive power management and highlight the urgent need to consolidate the grid infrastructure of North Cameroon. To increase grid resilience and stability, the paper recommends the strategic integration of renewables and the development of interconnections with other power grids. These measures are presented as viable solutions to meet current and future energy distribution challenges, ensuring a reliable and sustainable power supply for Cameroon.
基金funded by National Natural Science Foundation of China (52177074).
文摘There are issues with flexible DC transmission system such as a lack of control freedom over power flow.In order to tackle these issues,a DC power flow controller(DCPFC)is incorporated into a multi-terminal,flexible DC power grid.In recent years,a multi-port DC power flow controller based on a modular multi-level converter has become a focal point of research due to its simple structure and robust scalability.This work proposes a model predictive control(MPC)strategy for multi-port interline DC power flow controllers in order to improve their steady-state dynamic performance.Initially,the mathematical model of a multi-terminal DC power grid with a multi-port interline DC power flow controller is developed,and the relationship between each regulated variable and control variable is determined;The power flow controller is then discretized,and the cost function and weight factor are built with numerous control objectives.Sub module sorting method and nearest level approximation modulation regulate the power flow controller;Lastly,theMATLAB/Simulink simulation platformis used to verify the correctness of the establishedmathematicalmodel and the control performance of the suggestedMPC strategy.Finally,it is demonstrated that the control strategy possesses the benefits of robust dynamic performance,multiobjective control,and a simple structure.
基金the financial support from the Independent Research Fund Denmark(DFF)under Grant No.0217-00038B。
文摘Wind-farm flow control stands at the forefront of grand challenges in wind-energy science.The central issue is that current algorithms are based on simplified models and,thus,fall short of capturing the complex physics of wind farms associated with the high-dimensional nature of turbulence and multiscale wind-farm-atmosphere interactions.Reinforcement learning(RL),as a subset of machine learning,has demonstrated its effectiveness in solving high-dimensional problems in various domains,and the studies performed in the last decade prove that it can be exploited in the development of the next generation of algorithms for wind-farm flow control.This review has two main objectives.Firstly,it aims to provide an up-to-date overview of works focusing on the development of wind-farm flow control schemes utilizing RL methods.By examining the latest research in this area,the review seeks to offer a comprehensive understanding of the advancements made in wind-farm flow control through the application of RL techniques.Secondly,it aims to shed light on the obstacles that researchers face when implementing wind-farm flow control based on RL.By highlighting these challenges,the review aims to identify areas requiring further exploration and potential opportunities for future research.
基金supported by China Armament Pre-research Foundation(Grant No. 51318010402)UK Engineering and Physical Science Research Council (EPSRC), and China Scholarship Council (Grant No.2010611054)
文摘Work on dynamic topology optimization of engineering structures for vibration suppression has mainly addressed the maximization of eigenfrequencies and gaps between consecutive eigenfrequencies of free vibration, minimization of the dynamic compliance subject to forced vibration, and minimization of the structural frequency response. A dynamic topology optimization method of bi-material plate structures is presented based on power flow analysis. Topology optimization problems formulated directly with the design objective of minimizing the power flow response are dealt with. In comparison to the displacement or velocity response, the power flow response takes not only the amplitude of force and velocity into account, but also the phase relationship of the two vector quantities. The complex expression of power flow response is derived based on time-harmonic external mechanical loading and Rayleigh damping. The mathematical formulation of topology optimization is established based on power flow response and bi-material solid isotropic material with penalization(SIMP) model. Computational optimization procedure is developed by using adjoint design sensitivity analysis and the method of moving asymptotes(MMA). Several numerical examples are presented for bi-material plate structures with different loading frequencies, which verify the feasibility and effectiveness of this method. Additionally, optimum results between topological design of minimum power flow response and minimum dynamic compliance are compared, showing that the present method has strong adaptability for structural dynamic topology optimization problems. The proposed research provides a more accurate and effective approach for dynamic topology optimization of vibrating structures.
文摘A general model of flexible isolation systems which involves both the passive and active control factors is established by inserting actuators into an passive isolation system. And the power flow transmission function in such a system as with multi disturbance, multi mounts, passive isolators and actuators is deduced. By means of the numerical simulation method, the influence of actuators on power flow transmission characteristic is studied. And as a conclusion, the passive active synthetic control strategy of power flow is summarized.
基金supported by the State Grid Corporation of China Headquarter technology project (52010118000K)
文摘For demonstrating a multiterminal voltage-source converter(VSC)-based high-voltage DC(HVDC)(VSCHVDC) project, this study puts forward a technical route for calculating the power flow in a 500-kV VSC-HVDC power grid in comparison with that of an AC power grid. The Jacobian matrix used in the power-flow calculation was deduced through methods such as Newton–Laphson iteration and Taylor series expansion. Further, the operation effect of powerflow calculation on a true bipolar VSC-HVDC power grid was analyzed briefly. The elements of the Jacobian matrix corresponding to VSC were studied under the mode of droop control and the control strategy of VSC-HVDC power grid was analyzed in detail. The power-flow calculation model for VSC-HVDC power grid of the master–slave control mode was simplified using the PQ decomposition method of the power-flow calculation of an AC power grid. Moreover, a four-terminal model of the Zhangbei VSC-HVDC demonstration project was established and tested on MATLAB. The simulation results under two kinds of operating conditions were analyzed and compared to the results of BPA; the deviation between the power-flow results was studied. The results show that the proposed calculation method can provide a feasible support for calculating the power flow in VSC-HVDC grids.
基金supported by the National Natural Science Foundation of China(22078030,52021004)Natural Science Foundation of Chongqing(2022NSCO-LZX0014)+1 种基金Fundamental Research Funds for the Central Universities(2022CDJQY-005,2023CDJXY-047)National Key Research and Development Project(2022YFC3901204)。
文摘Efficiently modulating the velocity distribution and flow pattern of non-Newtonian fluids is a critical challenge in the context of dual shaft eccentric mixers for process intensification,posing a significant barrier for the existing technologies.Accordingly,this work reports a convenient strategy that changes the kinetic energy to controllably regulate the flow patterns from radial flow to axial flow.Results showed that the desired velocity distribution and flow patterns could be effectively obtained by varying the number and structure of baffles to change kinetic energy,and a more uniform velocity distribution,which could not be reached normally in standard baffle dual shaft mixers,was easily obtained.Furthermore,a comparative analysis of velocity and shear rate distributions is employed to elucidate the mechanism behind the generation of flow patterns in various dual-shaft eccentric mixers.Importantly,there is little difference in the power number of the laminar flow at the same Reynolds number,meaning that the baffle type has no effect on the power consumption,while the power number of both unbaffle and U-shaped baffle mixing systems decreases compared with the standard baffle mixing system in the transition flow.Finally,at the same rotational condition,the dimensionless mixing time of the U-shaped baffle mixing system is 15.3%and 7.9%shorter than that of the standard baffle and the unbaffle mixing system,respectively,which shows the advantage of the U-shaped baffle in stirring rate.
基金supported by National Natural Science Foundation of China (Nos.50836007, 10921062)
文摘A modelling study is performed to compare the plasma flow and heat transfer characteristics of low-power arc-heated thrusters (arcjets) for three different propellants: hydrogen, nitrogen and argon. The all-speed SIMPLE algorithm is employed to solve the governing equations, which take into account the effects of compressibility, Lorentz force and Joule heating, as well as the temperature- and pressure-dependence of the gas properties. The temperature, velocity and Mach number distributions calculated within the thruster nozzle obtained with different propellant gases are compared for the same thruster structure, dimensions, inlet-gas stagnant pressure and arc currents. The temperature distributions in the solid region of the anode-nozzle wall are also given. It is found that the flow and energy conversion processes in the thruster nozzle show many similar features for all three propellants. For example, the propellant is heated mainly in the near-cathode and constrictor region, with the highest plasma temperature appearing near the cathode tip; the flow transition from the subsonic to supersonic regime occurs within the constrictor region; the highest axial velocity appears inside the nozzle; and most of the input propellant flows towards the thruster exit through the cooler gas region near the anode-nozzle wall. However, since the properties of hydrogen, nitrogen and argon, especially their molecular weights, specific enthMpies and thermal conductivities, are different, there are appreciable differences in arcjet performance. For example, compared to the other two propellants, the hydrogen arcjet thruster shows a higher plasma temperature in the arc region, and higher axial velocity but lower temperature at the thruster exit. Correspondingly, the hydrogen arcjet thruster has the highest specific impulse and arc voltage for the same inlet stagnant pressure and arc current. The predictions of the modelling are compared favourably with available experimental results.
基金This work was partly supported by the Technology Project of State Grid Jiangsu Electric Power Co.,Ltd.,China,under Grant No.J2022095.
文摘Power flow calculation is the basis of power grid planning and many system analysis tasks require convergent power flow conditions.To address the unsolvable power flow problem caused by the reactive power imbalance,a method for adjusting reactive power flow convergence based on deep reinforcement learning is proposed.The deep reinforcement learning method takes switching parallel reactive compensation as the action space and sets the reward value based on the power flow convergence and reactive power adjustment.For the non-convergence power flow,the 500 kV nodes with reactive power compensation devices on the low-voltage side are converted into PV nodes by node type switching.And the quantified reactive power non-convergence index is acquired.Then,the action space and reward value of deep reinforcement learning are reasonably designed and the adjustment strategy is obtained by taking the reactive power non-convergence index as the algorithm state space.Finally,the effectiveness of the power flow convergence adjustment algorithm is verified by an actual power grid system in a province.