Fall detection helps to provide medical assistance quickly and to avoid the aggravation of injuries. In this paper, we propose a new noninvasive and energy-efficient smart sensor for fall detection. The sensor is base...
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computing, Internet, digital devices, smart devices, and other technologies were leading to a new terminology known as cloud of things (CoT). Cloud of Things is a powerful technology used to analyze and store massive ...
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This paper studies the task scheduling strategy of cloud data center based on data warehouse. Combined with the characteristics of power data center, a multi-qos evaluation model for power data center is defined. In t...
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The adoption of renewable energy sources (RES) such as solar photovoltaic distributed generation (SPVDG) has been at its peak in the present decade owing to their positive impact on the environment and the grid. Howev...
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The adoption of renewable energy sources (RES) such as solar photovoltaic distributed generation (SPVDG) has been at its peak in the present decade owing to their positive impact on the environment and the grid. However, these sources' ratings and placement need to be optimally estimated before their accommodation in the power distribution system (PDS) to prevent increased power loss and voltage profile aberrations. In this article, SPVDG is integrated with battery energy storage systems (BESS) to compensate for the shortcomings of SPVDG, such as intermittency and uncertainty, and to reduce peak demand. This paper presented a novel hybrid algorithm, which is a combination of the enhanced elephant herding algorithm and the Jaya algorithm. This developed algorithm properly controls the searching algorithm from global exploration to local exploitation to obtain the near-global optimum solution. The problem formulation is centered on the optimal accommodation of SPVDG and BESS to alleviate the power loss and improve the voltage profile of the PDS. Further, the voltage limits, maximum current limits, and BESS charge-discharge constraints are validated throughout the optimization process. Moreover, the hourly variation of SPVDG generation and demand profile with seasonal impact is examined in this study. ieee 69 bus PDS is tested for the development of the presented work. The suggested algorithm demonstrated its effectiveness and accuracy when compared to different optimization approaches in the literature. (C) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CCBY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).
The penetration level of renewable energy (RE) including distributed generation (DG) integrated in the distribution network has been increasing in many countries. This follows widespread encouragement to use renewable...
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ISBN:
(纸本)9781665475013
The penetration level of renewable energy (RE) including distributed generation (DG) integrated in the distribution network has been increasing in many countries. This follows widespread encouragement to use renewable energy to minimize reliance on conventional power plants to achieve net zero emissions. Malaysian energy transition targets and carbon neutral goals set by the government, lower cost of ownership of solar PV systems, and more efficient government renewable energy initiatives including Net Energy Metering (NEM) 3.0, Green Investment Tax (GITA), Large Scale Solar (LSS), and most recently the Corporate Green Power Program (CGPP) have driven the rapid development of renewable energy in the country. However, the high penetration level of distributed generation including solar PV, mini- hydro, and bio-energy has introduced several technical impacts on the operation of the distribution network including increased fault levels, voltage limit violation, reverse power flow, distribution network losses, and transformer losses. This paper analyzes the technical impacts of the high penetration level of distributed generation in medium voltage (MV) substations of the distribution network using DigSILENT PowerFactory simulation software. From the results obtained through the simulation analysis, the impact factors of fault level, voltage limit violations, reverse power flow, distribution network losses, and transformer losses have been formulated. The optimal distributed generation penetration level in distribution networks is then determined based on the highest score value of the normalized impact factor from all penetration levels.
This study paper explores the critical topic of formal verification of smart contracts in distributed ledger technology (DLT) systems. Smart contracts, self-executing code running on blockchain platforms, have gained ...
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Underwater wireless sensor networks (UWSNs) have come to rely heavily on localization technology due to their usefulness in a wide variety of contexts. Multi-sensor underwater surveillance has been an important area o...
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LiDAR is rapidly emerging as a central sensor in many applications involving autonomous navigation. However, the execution of state-of-the-art neural models for the analysis of point clouds produced by LiDARs necessit...
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ISBN:
(纸本)9781665495127
LiDAR is rapidly emerging as a central sensor in many applications involving autonomous navigation. However, the execution of state-of-the-art neural models for the analysis of point clouds produced by LiDARs necessitates considerable computing power, energy and memory. As a consequence, realtime analysis - e.g., 3D object detection - on resource-constrained mobile platforms such as Unmanned Aerial Vehicles (UAV) is often impractical. In this paper, we evaluate the feasibility of real-time LiDAR-based object detection for UAVs using measures and data obtained from a real-world deployment. First, we demonstrate that state-of-the-art neural models for 3D object detection cannot be executed even in relatively powerful embedded computers suitable for airborne drones, such as the NVIDIA Jetson Nano. Then, we focus our attention on edge computing, where the UAV offloads the execution of the analysis model to a compute-capable device (an edge server) positioned at the network edge. The key challenge is that point clouds generated by LiDARs have a large size (1.2MB per point cloud frame). We evaluate the overall capture-to-output delay of a remote analysis loop experimentally for WiFi and using expected data rate for cellular LTE environments. Finally, we evaluate the performance of 3D object detection on available datasets for autonomous vehicles and emphasize the challenges posed by the ability of UAVs to move in the 3D space. With our LiDAR-UAV system, we achieved detections with averages of 86% accuracy, 71.6% precision, and 55.14% recall outputted with an average end-to-end delay of 1920ms.
With the access of numerous distributed generations such as wind turbines, photovoltaic generators, and energy storage devices, the composition and operation mode of the power grid are becoming increasingly complex, a...
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Small current grounding systems are widely used in medium and low voltage distribution networks. Distribution networks are prone to ground faults. It is very important to locate the fault quickly. The access to distri...
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