Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimized configuration of video surveillance layout for substation construction site for full coverage surveillance

Aiming at the problem that the layout of video sensor equipment on the construction site of substation mainly relies on the experience of engineers, it lacks the limitations of scientific method guidance and cannot perform full coverage monitoring in three-dimensional space. A video surveillance of substation construction site oriented to full coverage monitoring is proposed. Optimized configuration of the layout. First, the construction site is grid-processed, the area coverage is converted into grid-based coverage, and the visual domain model of video sensor equipment is proposed, thereby establishing an optimized mathematical model of collective coverage. Finally, through simulation experiments, a layout optimization configuration that can meet the full coverage of the monitoring area is obtained.
Carbon Emission Prediction of Thermal Power Plants Based on Machine Learning Techniques

Since the magnificent goal of Peak Carbon Dioxide Emissions and Carbon Neutrality was put forward in 2020, carbon emission reduction has attracted unprecedented attention. The power industry must fulfill its carbon emission reduction obligations as soon as possible. Thermal power plants are the main source of carbon emissions in the power industry, so finding out the key influencing factors of thermal-power-plant carbon emission and making accurate predictions are important measures to promote the low-carbon development of the power industry. Although some precise models have been proposed, most power plants cannot obtain all the parameters required by the precise models in the actual production practice, which limits their application. Machine learning technology accepts numerical data as input and establishes the mapping relationship between variables automatically, which results in loose requirements on data. This paper summarizes several key influencing factors of carbon dioxide emissions of thermal power plants that are easy to observe and establishes a prediction model of carbon dioxide emissions of thermal power plants based on eXtreme Gradient Boosting. In addition, we compare our method with two machine learning methods proposed in previous research and obtain a satisfactory result.
An Improved Dual-Buck with Common-Mode Leakage Current Suppression

In order to suppress the common-mode leakage current in non-isolated grid-tied inverter photovoltaic system and improve the reliability of it, an improved dual-buck inverter circuit topology is proposed. The circuit topology can effectively suppress the common mode current, improve the problem of low inductance utilization in the traditional dual-buck inverter circuit topology, and ensure the common ground of the high-frequency switching transistor source, which is conducive to the drive design. In addition, a modulation method based on carrier phase-shifted control is introduced, which can reduce the output ripple current of the inverter without increasing the switching frequency, which is conducive to improving the power density of the system. The operation principle and characteristics of the proposed topology are analyzed in detail, and the specific implementation scheme of the modulation method is given. The feasibility of the circuit topology and modulation method is verified by a 1kW principle prototype.
Fault and load flows analysis of electricity transmission and distribution system in Casanare (Colombia)

This article describes a simulation of the electrical local distribution and regional transmission system of Enerca S.A. E.S. P. at 34.5 kV and 115 kV, identifying the most critical circuits and substations. The company is located in one of the major petroleum production areas in Colombia, and because of a massive growth in this sector, the electrical company expanded its networks in a radial way. This expansion was improvised and poorly planned due to the accelerated need to meet the new demand, which resulted in stability, balance, voltage regulation, and system reliability problems. Load flow and fault analyses were carried out based on current load and demand predictions in the short and medium term. Twelve proposals were made for network and substation modernization that once implemented will significantly improve the service reliability.
FollowMe - A Pedestrian Following Algorithm for Agricultural Logistic Robots

In Industry 4.0 and Agriculture 4.0, there are logistics areas where robots can play an important role, for example by following a person at a certain distance. These robots can transport heavy tools or simply help collect certain items, such as harvested fruits. The use of Ultra Wide Band (UWB) transceivers as range sensors is becoming very common in the field of robotics, i.e. for localising goods and machines. Since UWB technology has very accurate time resolution, it is advantageous for techniques such as Time Of Arrival (TOA), which can estimate distance by measuring the time between message frames. In this work, UWB transceivers are used as range sensors to track pedestrians/operators. In this work we propose the use of two algorithms for relative localization, between a person and robot. Both algorithms use a similar 2-dimensional occupancy grid, but differ in filtering. The first is based on a Extended Kalman Filter (EKF) that fuses the range sensor with odometry. The second is based on an Histogram Filter that calculates the pedestrian position by discretizing the state space in well-defined regions. Finally, a controller is implemented to autonomously command the robot. Both approaches are tested and compared on a real differential drive robot. Both proposed solutions are able to follow a pedestrian at speeds of 0.1 m/s, and are promising solutions to complement other solutions based on cameras and LiDAR.
Compliance Checking Based Detection of Insider Threat in Industrial Control System of Power Utilities

Compare to outside threats, insider threats that originate within targeted systems are more destructive and invisible. More importantly, it is more difficult to detect and mitigate these insider threats, which poses significant cyber security challenges to an industry control system (ICS) tightly coupled with today’s information technology infrastructure. Currently, power utilities rely mainly on the authentication mechanism to prevent insider threats. If an internal intruder breaks the protection barrier, it is hard to identify and intervene in time to prevent harmful damage. Based on the existing in-depth security defense system, this paper proposes an insider threat protection scheme for ICSs of power utilities. This protection scheme can conduct compliance check by taking advantage of the characteristics of its business process compliance and the nesting of upstream and downstream business processes. Taking the Advanced Metering Infrastructures (AMIs) in power utilities as an example, the potential insider threats of violation and misoperation under the current management mechanism are identified after the analysis of remote charge control operation. According to the business process, a scheme of compliance check for remote charge control command is presented. Finally, the analysis results of a specific example demonstrate that the proposed scheme can effectively prevent the consumers’ power outage due to insider threats.
Transient Extraction Transform Based Fault Location Method with Enhanced Accuracy

The fast determination of internal or external fault for the VSC-MTDC is essential for its safety and continuous operation. As very limited time is permitted in an internal fault, transient-based protection elements are widely applied to locate the fault in a very small-time window. However, with such a short time window, location methods based on the wavelet transform or the mathematical morphology show limited performance balancing the resolution in the time and frequency do-mains. In recent years, there has been a novel time-frequency domain analysis method, naming the transient extraction trans-form (TET), with high accuracy in both domains. In this paper, a TET-based fast fault-location method is proposed with enhanced accuracy. Comparison studies are made to highlight the performance of such a method against internal faults for the VSC-MTDC.
A proposed flicker meter test protocol

This paper describes work underway by the Cigre C4.05/CIRED 2/UIE PQ joint working group on voltage quality to develop a test protocol for flicker meters designed according to the IEC 61000-4-15 standard. It is intended to provide a systematic method suitable for use by manufacturers, end users, independent test laboratories and other certification bodies to determine if flicker meters meet the IEC design specifications for a wide range of fluctuating voltage conditions that have been observed in power systems. The test protocol should be valid for incandescent lamp characteristics defined in 61000-4-15 and its amendments whether it is operated at 50 Hz or 60 Hz. This work was started after reports from flicker meter users that meters from different vendors sometimes provided different results when connected to the same signals. This situation was confirmed when formal tests were performed by the Electric Power Research Institute (EPRI) at their Power Electronic Application Center (PEAC).
Classification of Power Quality Disturbance Signals Based on Weighting Random Forest

With the growing penetration of renewable power generation, the problem of power quality disturbances is becoming increasingly serious. The correct classification of power quality disturbances is a prerequisite and basis for managing and controlling power quality problems. Random forest is a classification method with the same weights of each classifier, which may cause low accuracy in classification. Therefore, this paper proposes a method to change the weight according to the accuracy and similarity of sub-decision trees, which can solve the overfitting problem. Firstly, the signals are preprocessed by Fast Independent Component Analysis (FastICA). Furthermore, the windowed short-time Fourier transform (STFT) is used to extract the features from the denoised signals. Moreover, four STFT features and other four statistical features are classified by weighting random forest. The weights of sub-decisions tree are changed by the classification accuracy and similarity of decision trees. Finally, numerical and simulated experiments have been carried out based on preprocessed disturbance signals from the renewable energy systems. The results illustrate the accuracy and effectiveness of the proposed method.
Research and Optimization of Shielding Structure for Inductive Power Transfer System

This paper explores the effect of the shielding plate in the inductive power transfer (IPT) pads, and identify its impact on leakage magnetic field and pads losses. The 3-D finite-element analysis method is used to optimize the structure of the shielding plate. The shielding effectiveness is investigated in terms of thickness of the shielding plate, air-gap distance between the shielding plate and the ferrite plate, covering area and geometry of the shielding plate. The result shows that the shielding structure plays dominant role in leakage magnetic field and pad losses. By using the optimized shielding structure, both the leakage magnetic field in the vicinity of the WPT system and the power loss in the transmission pads are reduced, which provides a reference of shielding structure design for IPT systems.
Analysis and Modelling of User Behaviors’ Impact on Load Characteristics

In the context of China's economic and social transformation and upgrading and the new round of energy revolution, the behavior characteristics of power users will change, thus affecting the load characteristics of the power grid. This paper identified key influencing factors of user behavior from the perspectives of electric vehicles ("EV"), demand side response and distributed generation ("DG"), established the mechanism and model of user behavior affecting load characteristics, and took a region as a typical case to predict and simulate the comprehensive impact. The simulation results show that EV and demand side response will change the peak-valley difference rate of the load curve. With the continuous increase of the DG scale, the peak-valley period of the power grid load curve will change and gradually show the characteristics of duck curve. The methods and conclusions proposed in this paper have important reference significance for studying and judging the future load change trend.
An Optimization Method of Virtual Synchronous Generators Parameter Design Based on Power Equivalent Model

For the power electronic grid-connected inverter controlled by the virtual synchronous generator(VSG), the tuning of control parameters is studied to improve the control performance of the system. First, on the basis of introducing the operating principle of synchronverter, a parameter conversion model based on power equivalent is established. Then, based on the transfer function of the active/frequency and reactive/voltage control loops in the model, the influence of the control parameters such as moment of inertia, damping coefficient on the stability, steady-state and dynamic performance of the system is studied by using the pole-zero distribution diagrams, the Bode diagrams and the time-domain analysis methods. And according to performance indicators such as steady-state error and adjustment time, the control parameters are tuned, which improves the response speed of the system and ensures the stability of the system. Finally, the feasibility of the theoretical analysis is verified by simulation.
Optimization Strategy of Composite Charging Station with Energy Storage for Fast Charging Demand of Electric Vehicles

The fast charging station for electric vehicles (EVs) is developing towards the direction of integration and compounding along with the development of renewable energy. This paper proposes an optimization strategy of composite charging stations (CCSs) with energy storage for fast charging demand of EVs. The strategy consists of two stages, the first stage is path planning for EVs and the second stage is optimal dispatching for CCSs based on the result of the first stage. In the first stage, the comprehensive path planning model for EVs is established based on the time cost and economic cost of EVs. Different EV decision results bring different charging loads and traffic flows. Therefore, in the second stage, a comprehensive benefit optimization model for CCSs is built through dispatching the energy storage of CCSs. The comprehensive benefit optimization model aims at optimizing the economic benefits of CCSs, security benefits of power grid and utilization benefits of road network. Finally, the proposed strategy is verified by an example of 18 km×18 km road network with four CCSs. The experimental results show that the proposed strategy can effectively reduce the comprehensive cost of EVs and improve the overall benefits of CCSs.1
Reference Architecture for Running Computationally Intensive Physics-Based Digital Twins of Heavy Equipment in a Heterogeneous Execution Environment

Physics-based digital twins for heavy equipment provide a powerful tool for improving operation and maintenance activities. In contrast to data-driven models, they present more explainable and confident results but require more computational power. Besides the problem of physics-based digital twins creation, there is a task of managing their lifecycle, including their execution, maintenance, storage, and updating. The features distinguishing this kind of digital twins are the mobility of the real counterpart, operation in remote locations, long lifecycle, information sensitivity, and gaps in information technology awareness among the equipment owners and users. This paper presents a methodology and reference architecture for a set of interconnected systems capable of running digital twins of heavy equipment in such conditions. A data model for preserving digital twin-related information for decades of machine operation is described. Operating-system-level virtualization technologies are used to run digital twins in a heterogeneous execution environment. An example of the reference architecture implementation is presented for the physics-based digital twins of a mobile log crane. The experimental part of the paper includes a comparison of computing time for different types of digital twins in different execution environments. It highlights the peculiarities related to running physics-based digital twins in containers. Experiments were performed using the Amazon cloud platform, an edge computing system represented by a single-board microcomputer based on ARM architecture, and a virtual machine on a desktop personal computer. Experimental results show that physics-based digital twins for the analysis of the multi-body dynamics can be run within the proposed architecture with real-time performance in all three types of execution environments. The paper demonstrates the practical implementation of physics-based digital twins for heavy equipment and defines directions for future research in this field.
MO-PSO Based Bi-level Multi-objective Optimal Configuration of Energy Storage System in Distribution Network

This paper considers the planning effectiveness and operational efficiency of battery energy storage systems (BESSs). A multi-objective particle swarm optimization (MOPSO) algorithm is proposed to solve the optimal solution of BESSs charging and discharging operation strategy; the outer layer aims to minimize the investment and operation cost of BESSs, voltage fluctuation and load fluctuation of distribution network. MOPSO algorithm solves the Pereto non-dominated solution set of the location-determined-volume planning scheme. The proposed algorithm achieves a balance between local exploration and global search, and effectively obtains high-quality solutions. Finally, the simulation results based on the IEEE-33 node system show that compared with the traditional multi-objective optimization algorithm, the proposed algorithm can obtain a more widely distributed and uniform Pareto front, which not only realizes the optimal investment benefit of BESSs, but also realizes the distribution of power distribution. The grid voltage quality and power stability are also significantly better than other algorithms.
A 28-GHz-Band GaN HEMT MMIC Doherty Power Amplifier Designed by Load Resistance Division Adjustment

A 28-GHz-band GaN HEMT MMIC Doherty power amplifier has been developed by using 0.15-µm GaN HEMT MMIC technology. The Doherty amplifier was designed by adaptively adjusting a load resistance division to a carrier amplifier (CA) and a peaking amplifier (PA) according to an output power balance between the CA and PA. The fabricated GaN HEMT MMIC Doherty amplifier exhibited a maximum drain efficiency of 54% and a maximum power-added efficiency of 44% at 29.1 GHz, with a saturation output power of 30 dBm. In addition, a drain efficiency of 33% was achieved at 29.1 GHz on a 9-dB output back-off condition.
Design of Terahertz InP pHEMT Using Machine Learning Assisted Global Optimization Techniques

This paper presents an optimal design of terahertz InP-based pseudomorphic high electron mobility transistors (pHEMT) powered by an artificial intelligence (AI) technique. Unlike the traditional physics-based design optimization methods, the new technique employs a machine learning-assisted global optimization algorithm. A state-of-the-art commercial pHEMT operating at millimeter-wave frequencies was used to calibrate the physics-based model. Based on the pHEMT, the proposed machine learning-assisted optimization method was implemented with the constraint of gate length, i.e., 100 nm. The simulation results show significant improvement in terms of cut-off frequency, i.e., 57%, and maximum oscillation frequency, i.e., 30%, compared to the commercial design. To the best of our knowledge, this is the first time to employ machine learning-assisted global optimization techniques to pHEMT design, showing high potential in terms of numerical simulation and device design for ultrafast semiconductor devices.
CMOS Automotive Radar Sensors: mm-Wave Circuit Design Challenges

This brief gives an overview of recent advancements in CMOS automotive radar sensors, focusing on the most critical circuit design at mm-wave frequencies. Highly scaled CMOS technologies enable very low-power consumption, reduced costs, and higher data processing capacity and integration compared to state-of-the-art SiGe BiCMOS chip-set solutions commonly adopted in commercial products. The very bottleneck is still represented by the radio front-end due to the challenging requirements of long-range radars. Circuit topologies and design tradeoffs are here discussed with reference to critical building blocks of the mm-wave radar front-end, reporting circuit implementations for a 77-GHz long-range radar sensor in a 28-nm fully-depleted silicon-on-insulator CMOS technology.
Identifying factors for evaluating software project proposals

One vital aspect of software project management is the initial evaluation of project proposals. Many authors have proposed varying sets of criteria for information technology (IT) software project evaluation. There is the need to develop a common framework for evaluating software projects, based on a manageable set of criteria. In this paper, we identified 83 software project proposal evaluation variables from literature and direct interviews with project evaluators; 31 variables were extracted under ten constructs using exploratory factor analysis. Product characteristics, user characteristics and vendor experience were found to be very crucial in software project proposal evaluation. The parameters identified in this work could serve as a basis for the development of a software system for evaluating software project proposals.
Integration planning of 5G network and smart distribution network

The characteristics of wide area coverage and deep coverage of 5G network can better promote the optimized operation of smart distribution network, while smart distribution network can provide a way to reduce cost and increase efficiency for 5G network operation. It is urgent to study the integration planning scheme of 5G network and smart distribution network to achieve benign two-way interaction between the two networks. This paper analyzes the integration of two networks from two aspects: 5G network improves the operation performance of smart distribution network and smart distribution network contributes to the promotion and construction of 5G network. On this basis, the key elements of the integration of 5G network and smart distribution network are sorted out, including energy elements, information elements and resource elements, and the integration planning of smart distribution network integrating 5G network is proposed. It is realized from three perspectives: site layout planning based on power and energy balance, cooperative planning of two networks and joint construction and sharing planning of 5G network infrastructure and smart distribution network facilities.