In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a sma...
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In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a smarter and more reliable electricity *** consists of gas turbines and renewable energy sources such as photovoltaic systems and wind *** bidding strategies,prepared by MG operators,decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources(RES).But it is inefficient due to the very high sporadic characteristics of RES and the very high outage *** solve these issues,this study suggests non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)for an optimal bidding strategy considering pumped hydroelectric energy storage and DRP based on outage conditions and uncertainties of renewable energy *** uncertainty related to solar and wind units is modeled using lognormal and Weibull probability ***-based DRP is used,especially considering the time of outages along with the time of peak loads and prices,to enhance the reliability of MG and reduce costs and emissions.
Beam scanning for joint detection and communication in integrated sensing and communication(ISAC) systems plays a critical role in continuous monitoring and rapid adaptation to dynamic environments. However, the desig...
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Beam scanning for joint detection and communication in integrated sensing and communication(ISAC) systems plays a critical role in continuous monitoring and rapid adaptation to dynamic environments. However, the design of sequential scanning beams for target detection with the required sensing resolution has not been tackled in the *** bridge this gap, this paper introduces a resolution-aware beam scanning design. In particular, the transmit information beamformer, the covariance matrix of the dedicated radar signal, and the receive beamformer are jointly optimized to maximize the average sum rate of the system while satisfying the sensing resolution and detection probability requirements.A block coordinate descent(BCD)-based optimization framework is developed to address the non-convex design problem. By exploiting successive convex approximation(SCA), S-procedure, and semidefinite relaxation(SDR), the proposed algorithm is guaranteed to converge to a stationary solution with polynomial time complexity. Simulation results show that the proposed design can efficiently handle the stringent detection requirement and outperform existing antenna-activation-based methods in the literature by exploiting the full degrees of freedom(DoFs) brought by all antennas.
This paper presents a combined approach of fractional-order proportional-integral (FOPI) control with field-oriented control (FOC) for maximum torque per ampere (MTPA) tracking. The method maximizes the torque-to-ampe...
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Statistics is a necessary tool to asses the uncertainties in a measurement technique. In this way, we can determine the reliability of the technique and can aim to improve this. In measurement techniques where both th...
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To reduce system complexity and bridge the interface between electronic and photonic circuits,there is a high demand for a non-volatile memory that can be accessed both electrically and ***,practical solutions are sti...
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To reduce system complexity and bridge the interface between electronic and photonic circuits,there is a high demand for a non-volatile memory that can be accessed both electrically and ***,practical solutions are still lacking when considering the potential for large-scale complementary metal-oxide semiconductor compatible ***,we present an experimental demonstration of a non-volatile photonic-electronic memory based on a 3-dimensional monolithic integrated ferroelectric-silicon ring *** successfully demonstrate programming and erasing the memory using both electrical and optical methods,assisted by optical-to-electrical-to-optical *** memory cell exhibits a high optical extinction ratio of 6.6 dB at a low working voltage of 5 V and an endurance of 4×10^(4) ***,the multi-level storage capability is analyzed in detail,revealing stable performance with a raw bit-error-rate smaller than 5.9×10^(−2).This ground-breaking work could be a key technology enabler for future hybrid electronic-photonic systems,targeting a wide range of applications such as photonic interconnect,high-speed data communication,and neuromorphic computing.
I had the privilege and the pleasure to work closely with Stephen J. Pennycook for about twenty years, having a group of post-docs and Vanderbilt-University graduate students embedded in his electron microscopy group ...
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I had the privilege and the pleasure to work closely with Stephen J. Pennycook for about twenty years, having a group of post-docs and Vanderbilt-University graduate students embedded in his electron microscopy group at Oak Ridge National Laboratory, spending on average a day per week there. We combined atomic-resolution imaging of materials,electron-energy-loss spectroscopy, and density-functional-theory calculations to explore and elucidate diverse materials phenomena, often resolving long-standing issues. This paper is a personal perspective of that journey, highlighting a few examples to illustrate the power of combining theory and microscopy and closing with an assessment of future prospects.
作者：
Balakrishnan, AshutoshDe, SwadesWang, Li-ChunDelhi
Department of Electrical Engineering New Delhi India IIT Delhi
Department of Electrical Engineering Bharti School of Telecommunication New Delhi India
Department of Electrical and Computer Engineering Taiwan
Grid connected and solar powered base stations (BSs) acting as distributed energy sources are increasingly becoming a popular solution to mobile operators. These networks experience double stochasticity due to the spa...
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Recent advancements in artificial intelligence (AI) have shown potential solutions to acoustic source localization in three-dimensional space. This article proposes a new low-complex AI-based framework in the spherica...
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Recent advancements in artificial intelligence (AI) have shown potential solutions to acoustic source localization in three-dimensional space. This article proposes a new low-complex AI-based framework in the spherical harmonics (SH) domain for efficient direction of arrival (DOA) estimation. The SH coefficients are the key features for the DOA estimation and are obtained from the SH decomposition (SHD) of the spherical microphone array (SMA) recordings. Subsequently, the unified convolutional neural network (UCNN) model is trained to estimate the source azimuth and elevation from the phase and magnitude of the SH coefficient. Since the relation between the azimuth and elevation with phase and magnitude of the SH coefficient is subjective, a high volume of data are required to train the model. In this context, the symmetric properties of the SH basis function are explored to obtain the SH implicit symmetric coefficients (SH-ISCs) that split the 3-D space into octant classes. Within each octant, the phase and magnitude of the SH coefficients exhibit one-to-one correspondence with the source azimuth and elevation and execute the data redundancy. This work can be divided into two parts, a multiclass support vector machine (M-SVM) is investigated to obtain the octant classes from the SH-ISC in the first part. In the second part, the UCNN model is developed to estimate the DOA angles in each octant class. Further, the proposed technique is computationally efficient compared to the baseline learning algorithms in terms of computational and run-time complexity. Impact Statement—DOA estimation is an important task in signal processing that involves determining the angle of arrival of signals in an array of sensors or antennas. AI techniques, such as machine learning and deep learning, can significantly enhance DOA estimation by providing more accurate, efficient, robust, and adaptable solutions. AI algorithms can learn complex patterns and relationships in data, optimize fo
Cloud Computing (CC) is widely adopted in sectors like education, healthcare, and banking due to its scalability and cost-effectiveness. However, its internet-based nature exposes it to cyber threats, necessitating ad...
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Spiking Neural Networks (SNNs) can be a suitable alternative to deep artificial neural networks due to efficient computation and low-power event-driven information analysis. Nevertheless, SNN cannot compete with Artif...
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