The gradual penetration of grid-forming(GFM)converters into new power systems with renewable energy sources may result in the emergence of small-signal instability *** issues can be elucidated using sequence impedance...
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The gradual penetration of grid-forming(GFM)converters into new power systems with renewable energy sources may result in the emergence of small-signal instability *** issues can be elucidated using sequence impedance models,which offer a more tangible and meaningful interpretation than dq-domain impedance models and state-space ***,existing research has primarily focused on the impact of power loops and inner control loops in GFM converters,which has not yet elucidated the precise physical interpretation of inner voltage and current loops of GFM converters in *** paper derives series-parallel sequence impedance models of multi-loop GFM converters,demonstrating that the voltage loop can be regarded as a parallel impedance and the current loop as a series ***,the corresponding small-signal stability characteristics can be identified through Bode diagrams of sequence impedances or by examining the physical meanings of impedances in series and in *** results indicate that the GFM converter with a single power loop is a candidate suitable for application in new power systems,given its reduced number of control parameters and enhanced low-frequency performance,particularly in weak *** results of PLECS simulations and corresponding prototype experiments verify the accuracy of the analytical analysis under diverse grid conditions.
Because of the important role of the absorption heat pump in low-grade thermal energy utilization,this paper extends it to micro domain and performs a finite-time thermodynamic modelling for a three-heat-reservoir(THR...
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Because of the important role of the absorption heat pump in low-grade thermal energy utilization,this paper extends it to micro domain and performs a finite-time thermodynamic modelling for a three-heat-reservoir(THR)thermal Brownian heat pump with heat transfer effect by using an equivalent combined cycle method,which was applied for macro endoreversible THR heat *** working principle and energy transformation rule are studied,and the coefficient of performance(COP)and heating load are *** a fixed overall thermal conductance of three heat exchangers,the maximal heating load is determined by optimizing thermal conductance distributions among three heat exchangers and barrier height,and the optimal working temperatures are also *** impact of external heat transfer is elucidated to show the difference between this model and a non-equilibrium thermodynamic *** indicate that external heat transfer determines the energy transformation directly,and performance characteristics are closer to reality when external heat transfer is *** heating load has a maximal value about thermal conductance allocation *** half the overall heat exchanger inventory needs to be assigned to the heat exchanger of the heating space for maximal heating *** the cycle is with only heat transfer effect,the net particle numbers are zero,and the cycle fails to pump *** research results are expected to offer an idea for thermodynamic optimization and design of micro THR thermal Brownian heat pump devices.
Predicting the metastatic direction of primary breast cancer (BC), thus assisting physicians in precise treatment, strict follow-up, and effectively improving the prognosis. The clinical data of 293,946 patients with ...
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Carbide dispersion reinforcing has been demonstrated to be an effective way of strengthening metal ma-trix ***,plagued by the nerve-wracking fact that the carbide particles tend to aggregate at the grain boundary of t...
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Carbide dispersion reinforcing has been demonstrated to be an effective way of strengthening metal ma-trix ***,plagued by the nerve-wracking fact that the carbide particles tend to aggregate at the grain boundary of the metal matrix,grow up,and form an incoherent interface with it,their im-provement in mechanical strength tends to be *** this study,spark plasma sintering(SPS)was used to prepare the bulk alloy Ni20Cr and its composites with different carbides including TiC,SiC,and *** leads to discharge and elevates temperature at the interface to melt the Ni20Cr alloy par-ticles *** cooled down,the alloy is heterogeneously solidified on the surface of the carbide and builds up a coherent interface with *** to the decomposition of Ti3SiC2 during sintering,it completely transformed into nanosized TiC particles,which are engulfed by the outer melted layer of Ni20Cr and well dispersed within the alloy *** comparison to the Ni20Cr alloy,the composite with merely 4 wt％Ti3SiC2 gains over three times enhancement in yield strength to 879 MPa,while keeping a moderate high elongation of 17.8％.Finite element analysis demonstrated that the combination of SPS and precursor MAX phase of Ti3SiC2,which results in the in-situ precipitation of coherent ultrafine TiC particles in alloy grains,plays the key role in getting a good balance between mechanical strength and ductility for the Ni20Cr matrix composites.
In this paper, the cooperative output regulation(COR) problem of a class of unknown heterogeneous multi-agent systems(MASs) with directed graphs is studied via a model-free reinforcement learning(RL) based fully distr...
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In this paper, the cooperative output regulation(COR) problem of a class of unknown heterogeneous multi-agent systems(MASs) with directed graphs is studied via a model-free reinforcement learning(RL) based fully distributed eventtriggered control(ETC) strategy. First, we consider the scenario that the exosystem is accessible globally to all agents, an internal model-based augmented algebraic Riccati equation(AARE) is constructed, and its solution is learned by the proposed model-free RL algorithm via online input-output data. Further, for the scenario that the exosystem is accessible only to its adjacent followers, the distributed observers are designed for each agent to get the state of the exosystem, and an internal modelbased fully distributed adaptive ETC protocol is then synthesized to construct the corresponding AARE, and the feedback gain matrix is learned in a model-free fashion. The model-free RL-based control protocol proposed in this paper can not only remove the prior knowledge of agents' dynamics, but also release the dependence on global information by the adaptive event-triggered mechanism(ETM) and the new graph-based Lyapunov function. Finally, simulation results are illustrated to show the feasibility and effectiveness of the proposed control scheme.
The manual process of evaluating answer scripts is strenuous. Evaluators use the answer key to assess the answers in the answer scripts. Advancements in technology and the introduction of new learning paradigms need a...
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With the development of cyber-physical systems,system security faces more risks from cyber-attacks. In this work,we study the problem that an external attacker implements covert sensor and actuator attacks with resour...
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With the development of cyber-physical systems,system security faces more risks from cyber-attacks. In this work,we study the problem that an external attacker implements covert sensor and actuator attacks with resource constraints(the total resource consumption of the attacks is not greater than a given initial resource of the attacker) to mislead a discrete event system under supervisory control to reach unsafe states. We consider that the attacker can implement two types of attacks: One by modifying the sensor readings observed by a supervisor and the other by enabling the actuator commands disabled by the supervisor. Each attack has its corresponding resource consumption and remains covert. To solve this problem, we first introduce a notion of combined-attackability to determine whether a closedloop system may reach an unsafe state after receiving attacks with resource constraints. We develop an algorithm to construct a corrupted supervisor under attacks, provide a verification method for combined-attackability in polynomial time based on a plant, a corrupted supervisor, and an attacker's initial resource, and propose a corresponding attack synthesis algorithm. The effectiveness of the proposed method is illustrated by an example.
The evolution of the electrical grid from its early centralized structure to today’s advanced "smart grid" reflects significant technological progress. Early grids, designed for simple power delivery from l...
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The evolution of the electrical grid from its early centralized structure to today’s advanced "smart grid" reflects significant technological progress. Early grids, designed for simple power delivery from large plants to consumers, faced challenges in efficiency, reliability, and scalability. Over time, the grid has transformed into a decentralized network driven by innovative technologies, particularly artificial intelligence (AI). AI has become instrumental in enhancing efficiency, security, and resilience by enabling real-time data analysis, predictive maintenance, demand-response optimization, and automated fault detection, thereby improving overall operational efficiency. This paper examines the evolution of the electrical grid, tracing its transition from early limitations to the methodologies adopted in present smart grids for addressing those challenges. Current smart grids leverage AI to optimize energy management, predict faults, and seamlessly integrate electric vehicles (EVs), reducing transmission losses and improving performance. However, these advancements are not without limitations. Present grids remain vulnerable to cyberattacks, necessitating the adoption of more robust methodologies and advanced technologies for future grids. Looking forward, emerging technologies such as Digital Twin (DT) models, the Internet of Energy (IoE), and decentralized grid management are set to redefine grid architectures. These advanced technologies enable real-time simulations, adaptive control, and enhanced human–machine collaboration, supporting dynamic energy distribution and proactive risk management. Integrating AI with advanced energy storage, renewable resources, and adaptive access control mechanisms will ensure future grids are resilient, sustainable, and responsive to growing energy demands. This study emphasizes AI’s transformative role in addressing the challenges of the early grid, enhancing the capabilities of the present smart grid, and shaping a secure
Traditional infrastructure inspection methods require specialized expertise and involve complex maintenance techniques. Currently, inspectors depend on auditory cues, particularly the sound produced by hammering, to s...
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Water resources are crucial natural assets that all living organisms rely upon. Water is essential for consumption, industrial processes, and farming activities. In recent years, human activities and natural disasters...
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