In this letter, we depart from the widely-used gradient descent-based hierarchical federated learning (FL) algorithms to develop a novel hierarchical FL framework based on the alternating direction method of multiplie...
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Microgrids(MGs)with high penetration of dis-tributed generators may cause congestion in the distribution net-work during *** address this issue,this paper proposes a two-time-scale congestion management scheme for mul...
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Microgrids(MGs)with high penetration of dis-tributed generators may cause congestion in the distribution net-work during *** address this issue,this paper proposes a two-time-scale congestion management scheme for multiple MGs integrated distribution ***-ahead hourly-scale dynamic congestion management(DCM)is formulated as a con-strained optimization problem,which can be solved by utilizing the proposed alternating iterative method,with the privacy of both the distribution network and MGs being *** sub-hourly-scale contract energy tracking aims at fully utilizing the controllable resources of the MGs to minimize the difference of the contract and actual exchanged energy between the MG and distribution *** coordination of the proposed two timescales of management schemes,the MGs integrated distribution networks can operate economically while avoiding the probable congestion predicament with high penetration of renewable *** studies with a i3-bus system MGs integrated distribution network demonstrated this proposed approach is effective to manage the congestion problem in the distribution network,while the energy tracking approach can improve the welfare of the MGs engaged in energy contracts ***-Alternating giterativemethod,congestion management,microgrids,renewable energy integration.
Green hydrogen has shown great potential to power microgrids as a primary source,whereas the resilient operation methodology under extreme events remains an open *** fill this gap,this letter establishes an operationa...
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Green hydrogen has shown great potential to power microgrids as a primary source,whereas the resilient operation methodology under extreme events remains an open *** fill this gap,this letter establishes an operational optimization strategy towards resilient hydrogen-powered *** frequency and voltage regulation characteristics of primary hydrogen sources under droop control and their electrical-chemical conversion process with nonlinear stack efficiency are accurately modeled by piecewise linear constraints.A resilience-oriented multi-time-slot stochastic optimization model is then formulated for an economic and robust operation under changing *** results show that the new formulation can leverage the primary hydrogen sources to achieve a resilience and safety-assured operation plan,supplying maximum critical loads while significantly reducing the frequency and voltage variations.
The importance of Model Predictive Control(MPC)has significant applications in the agricultural industry,more specifically for greenhouse’s control ***,the complexity of the greenhouse and its limited prior knowledge...
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The importance of Model Predictive Control(MPC)has significant applications in the agricultural industry,more specifically for greenhouse’s control ***,the complexity of the greenhouse and its limited prior knowledge prevent an exact mathematical description of the *** methods provide a promising solution to this issue through their capacity to identify the system’s comportment using the fit between model output and observed *** this paper,we introduce an application of Constrained Model Predictive Control(CMPC)for a greenhouse temperature and relative *** this purpose,two Multi Input Single Output(MISO)systems,using Numerical Subspace State Space System Identification(N4SID)algorithm,are firstly suggested to identify the temperature and the relative humidity comportment to heating and ventilation *** this sense,linear state space models were adopted in order to evaluate the robustness of the control *** the system is identified,the MPC technique is applied for the temperature and the humidity *** results show that the regulation of the temperature and the relative humidity under constraints was guaranteed,both parameters respect the ranges 15℃≤T_(int)≤30℃and 50%≤H_(int)≤70%*** the other hand,the control signals uf and uh applied to the fan and the heater,respect the hard constraints notion,the control signals for the fan and the heater did not exceed 0≤uf≤4.3 Volts and 0≤uh≤5 Volts,respectively,which proves the effectiveness of the MPC and the tracking ***,we show that with the proposed technique,using a new optimization toolbox,the computational complexity has been significantly *** greenhouse in question is devoted to Schefflera Arboricola cultivation.
It is well-known that lithium plating significantly reduces the capacity of Li-ion batteries, particularly at elevated charging rates, high state of charge (SoC), and low temperatures. This study presents a simplified...
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This paper revisits the problem of bumpless transfer control(BTC) for discrete-time nondeterministic switched linear systems. The general case of asynchronous switching is considered for the first time in the field of...
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This paper revisits the problem of bumpless transfer control(BTC) for discrete-time nondeterministic switched linear systems. The general case of asynchronous switching is considered for the first time in the field of BTC for switched systems. A new approach called interpolated bumpless transfer control(IBTC) is proposed, where the bumpless transfer controllers are formulated with the combination of the two adjacent modedependent controller gains, and are interpolated for finite steps once the switching is detected. In contrast with the existing approaches, IBTC does not necessarily run through the full interval of subsystems, as well as possesses the time-varying controller gains(with more flexibility and less conservatism) achieved from a control synthesis allowing for the stability and other performance of the whole switched system. Sufficient conditions ensuring stability and H_(∞) performance of the underlying system by IBTC are developed, and numerical examples verify the theoretical findings.
Wireless communications are particularly vulnerable to eavesdropping attacks due to their broadcast nature. To effectively deal with eavesdroppers, existing security techniques usually require accurate channel state i...
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This paper introduces an algorithm for beamforming systems by the aid of multidimensional harmonic retrieval(MHR).This algorithm resolves problems,removes limitations of sampling and provides a more robust beamformer....
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This paper introduces an algorithm for beamforming systems by the aid of multidimensional harmonic retrieval(MHR).This algorithm resolves problems,removes limitations of sampling and provides a more robust beamformer.A new sample space is created that can be used for estimating weights of a new beamforming called spatial-harmonics retrieval beamformer(SHRB).Simulation results show that SHRB has a better performance,accuracy,and applicability and more powerful eigenvalues than conventional beamformers.A simple mathematical proof is *** changing the number of harmonics,as a degree of freedom that is missing in conventional beamformers,SHRB can achieve more optimal outputs without increasing the number of spatial or temporal *** will demonstrate that SHRB offers an improvement of 4 dB in signal to noise ratio(SNR) in bit error rate(BER) of 10~(-4) over conventional *** the case of direction of arrival(DOA) estimation,SHRB can estimate the DOA of the desired signal with an SNR of-25 dB,when conventional methods cannot have acceptable response.
Global navigation satellite systems (GNSS) face significant challenges in urban and sub-urban areas due to non-line-of-sight (NLOS) propagation, multipath effects, and low received power levels, resulting in highly no...
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Ransomware attacks pose a significant threat to critical infrastructures,demanding robust detection *** study introduces a hybrid model that combines vision transformer(ViT)and one-dimensional convolutional neural net...
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Ransomware attacks pose a significant threat to critical infrastructures,demanding robust detection *** study introduces a hybrid model that combines vision transformer(ViT)and one-dimensional convolutional neural network(1DCNN)architectures to enhance ransomware detection *** common challenges in ransomware detection,particularly dataset class imbalance,the synthetic minority oversampling technique(SMOTE)is employed to generate synthetic samples for minority class,thereby improving detection *** integration of ViT and 1DCNN through feature fusion enables the model to capture both global contextual and local sequential features,resulting in comprehensive ransomware *** on the UNSW-NB15 dataset,the proposed ViT-1DCNN model achieved 98%detection accuracy with precision,recall,and F1-score metrics surpassing conventional *** approach not only reduces false positives and negatives but also offers scalability and robustness for real-world cybersecurity *** results demonstrate the model’s potential as an effective tool for proactive ransomware detection,especially in environments where evolving threats require adaptable and high-accuracy solutions.
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