This research investigates the vulnerability and resilience of human cognitive processes in the context of rapidly advancing driving technologies susceptible to multi-modal cyber-attacks. By simulating scenarios where...
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Adopting high penetration levels of electric vehicles(EVs) necessitates the implementation of appropriate charging management systems to mitigate their negative impacts on power distribution networks. Currently, most ...
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Adopting high penetration levels of electric vehicles(EVs) necessitates the implementation of appropriate charging management systems to mitigate their negative impacts on power distribution networks. Currently, most of the proposed EV charging management techniques rely on the availability of high-bandwidth communication links. Such techniques are far from realization due to(1) the lack of utility-grade communication systems in many cases such as secondary(low-voltage) power distribution systems to which EVs are connected, rural areas, remote communities, and islands, and(2) existing fears and concerns about the data privacy of EV users and cyber-physical security. For these cases, appropriate local control schemes are needed to ensure the adequate management of EV charging without violating the grid operation requirements. Accordingly, this paper introduces a new communication-less management strategy for EV charging in droop-controlled islanded microgrids. The proposed strategy is autonomous, as it is based on the measurement of system frequency and local bus voltages. The proposed strategy implements a social charging fairness policy during periods when the microgrid distributed generators(DGs) are in short supply by allocating more system capacity to the EVs with less charging in the past. Furthermore, a novel communication-less EV load shedding scheme is incorporated into the management strategy to provide relief to the microgrid during events of severe undervoltage or underfrequency occurrences due to factors such as high loading or DG outages. Numerical simulations demonstrate the superiority of the proposed strategy over the state-of-the-art controllers in modulating the EV charging demand to counteract microgrid instability.
As a key factor influencing the quality of tobacco production and a crucial indicator for assessing tobacco leaf quality, the recognition of tobacco leaf maturity has garnered significant attention from scholars. Inte...
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The field of Human Activity Recognition (HAR) is growing significantly in several areas but little research focuses on cultural behavior. How machine learning can explain human activity as a promotional tool in unders...
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The heterogeneous fleet vehicle routing problem (HFVRP) is of great significance in logistics and transportation. This paper considers a crucial and challenging HFVRP variant, namely multi-objective fleet size and mix...
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The Electro-Hydrostatic Actuator(EHA)is a typical hydro-mechatronic control *** to the limited accuracy of measurement,inadequate knowledge,and vague judgments,hybrid uncertainties,including aleatory and epistemic unc...
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The Electro-Hydrostatic Actuator(EHA)is a typical hydro-mechatronic control *** to the limited accuracy of measurement,inadequate knowledge,and vague judgments,hybrid uncertainties,including aleatory and epistemic uncertainties,inevitably exist in the performance assessment of EHA *** methods ignored the hybrid uncertainties which can hardly obtain a satisfactory result while wasting a lot of time on the experimental *** overcome this drawback,a metamodeling method for hybrid uncertainty propagation of EHA systems is developed via an active learning Gaussian Process(GP)*** proposed method is bifurcated into three pillars:(A)Initializing the GP model and generating the optimum candidate sampling set by an Optimized Max-Minimize Distance(OMMD)algorithm,which aims to maximize the minimum distance between the added samples and original samples,(B)maximizing the learning function and generating new samples by a developed farthest or nearest judgment strategy,while updating the original GP model,and(C)judging the convergence by three uncertainty metrics,i.e.,the area metric,maximum variance metric,and the mean value metric.A numerical example is exemplified to evaluate the effectiveness and efficiency of the proposed ***,the EHA system of aircrafts is examined to show the application of the proposed method for high-dimensional *** effects of the uncertainties in the Proportional-Integral-Differential(PID)of the EHA system are also examined.
This paper introduces a methodology for parameterizing the DER A model using a novel smooth mathematical representation, simplifying the process and preserving accuracy in modeling inverter-based generator (IBG). The ...
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Integrating solar photovoltaic (PV), wind, and battery storage (BS) systems into the grid introduces significant power quality (PQ) challenges. In particular, the intermittent nature of solar PV and wind energy system...
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作者:
Liu, YifanXu, JianzhongZhu, YiyangTian, ZhaoxuanZhao, ChengyongLi, Gen
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources China
Energy Technology and Computer Science Section Department of Engineering Technology and Didactics Ballerup2750 Denmark
With the increasing integration of renewable energy into power systems, electromagnetic transient (EMT) simulation has become indispensable for accurate system analysis. However, the complexity of wind turbine (WT) mo...
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To solve the problem of mobile robots needing to adjust their pose for accurate operation after reaching the target point in the indoor environment,a localization method based on scene modeling and recognition has bee...
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To solve the problem of mobile robots needing to adjust their pose for accurate operation after reaching the target point in the indoor environment,a localization method based on scene modeling and recognition has been ***,the offline scene model is created by both handcrafted feature and semantic ***,the scene recognition and location calculation are performed online based on the offline scene *** improve the accuracy of recognition and location calculation,this paper proposes a method that integrates both semantic features matching and handcrafted features *** on the results of scene recognition,the accurate location is obtained through metric calculation with 3D *** experimental results show that the accuracy of scene recognition is over 90%,and the average localization error is less than 1 *** results demonstrate that the localization has a better performance after using the proposed improved method.
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