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power factor Estimation of Distributed Energy Resources Using Voltage Magnitude Measurements

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Journal of Modern power Systems and Clean Energy 2021年第4期9卷 859-869页

作者： Samuel Talkington Santiago Grijalva Matthew J.Reno School of Electrical and Computer Engineering Georgia Institute of TechnologyAtlantaGA 30318USA Electric power Systems Research Department Sandia National LaboratoriesAlbuquerqueNM 87123USA

This paper presents a new method for the estimation of the injection state and power factor of distributed energy resources (DERs) using voltage magnitude measurements only. A physics-based linear model is used to develop estimation heuristics for net injections of real and reactive power at a set of buses under study, allowing a distribution engineer to form a robust estimate for the operating state and the power factor of the DER at those buses. The method demonstrates and exploits a mathematical distinction between the voltage sensitivity signatures of real and reactive power injections for a fixed power system model. Case studies on various test feeders for a model of the distribution circuit and statistical analyses are presented to demonstrate the validity of the estimation method. The results of this paper can be used to improve the limited information about inverter parameters and operating state during renewable planning, which helps mitigate the uncertainty inherent in their integration.

关键词： Decentralized power system control detection and estimation power factor sparse approximation

Unexpected low thermal conductivity and large power factor in Dirac semimetal Cd3As2

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Chinese Physics B 2016年第1期25卷 378-383页

作者：张成周通梁斯航曹钧植袁翔刘彦闻沈瑶王奇思赵俊杨中芹修发贤 State Key Laboratory of Surface Physics and Department of Physics Fudan UniversityShanghai 200433China Collaborative Innovation Center of Advanced Microstructures Fudan UniversityShanghai 200433China Key Laboratory for Computational Physical Sciences(MOE) Fudan UniversityShanghai 200433China

Thermoelectrics has long been considered as a promising way of power generation for the next decades. So far, extensive efforts have been devoted to the search of ideal thermoelectric materials, which require both high electrical conductivity and low thermal conductivity. Recently, the emerging Dirac semimetal Cd3As2, a three-dimensional analogue of graphene, has been reported to host ultra-high mobility and good electrical conductivity as metals. Here, we report the observation of unexpected low thermal conductivity in Cd3As2, one order of magnitude lower than the conventional metals or semimetals with a similar electrical conductivity, despite the semimetal band structure and high electron mobility. The power factor also reaches a large value of 1.58 mW.m 1 .K-2 at room temperature and remains non-saturated up to 400 K. Corroborating with the first-principles calculations, we find that the thermoelectric performance can be well-modulated by the carrier concentration in a wide range. This work demonstrates the Dirac semimetal Cd3As2 as a potential candidate of thermoelectric materials.

关键词： Dirac semimetal thermal conductivity power factor thermoelectric material

power factor Improvement of AC-DC Converter Based on Separately Excited DC Motor Using Passive Filter

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Open Journal of Energy Efficiency 2016年第3期5卷 71-77页

作者： Shazia Baloch Mukhtiar Ahmed Mahar Raza Haider Shakeel Ahmed Electrical Engineering Department Balochistan University of Engineering and Technology Khuzdar Pakistan Electrical Engineering Department Mehran University of Engineering and Technology Jamshoror Pakistan Civil Engineering Department Balochistan University of Engineering and Technology Khuzdar Pakistan

In industries DC motor drives are very essential due to their high performance applications such as its reliability, ease of control, low cost and simplicity. And speed control of these motors is very easy due to power electronic AC-DC converters. These power electronic converters are with prominent low power factor and higher Total Harmonic Distortion (THD). These converters operate only for short time resulting non-sinusoidal waveform. This problem of harmonic distortion can be mitigated by reshaping the non-sinusoidal waveform to pure sine wave. Different wave shaping techniques have been developed by using different filters among which one is tuned passive filter. This paper proposed power factor improvement and harmonic mitigation of AC-DC converters based on separately excited DC motor using tuned passive filter. In this context experimental model is designed and results are analyzed by power quality analyzer.

关键词： DC Motors AC-DC Converters power factor Total Harmonic Distortion Passive Filters

Economic Improvement of power factor Correction: A Case Study

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Journal of power and Energy Engineering 2021年第6期9卷 1-11页

作者： Kassem Wahab Mohamad Rahal Roger Achkar Department of Computer and Communications Engineering Faculty of Engineering American University of Science and Technology Beirut Lebanon

power factor (PF) is simply an expression of energy efficiency, which is always expressed in terms of percentage. Technically, PF is a ratio of real power in Kilowatts to the apparent power, which is always expressed in kilovolts amperes. In AC power analysis, power is always expressed in three ways, the real power (P), reactive power (Q), and the apparent power (S). The real power is the work useful power, while the reactive power is the wasted power in the 3-phase AC system, and the apparent power is the vectorial sum of the two powers. The increase of reactive power will reduce the presence of real power, thus making the power to be more expensive. In this paper, we will analyze the importance of improving the power factor by applying a bank of capacitors to a case study in Lebanon. Analysis of the economic improvement in the application of power factor correction is carried out. The result shows a reduction of 12 percent in the total cost.

关键词： power factor Reactive power kVAR Inductive Apparent power Active power

Design and Construction of A Single-Phase power factor Meter

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Electrical Science & Engineering 2020年第2期2卷 11-14页

作者： A.A.Mukaila I.Olugbemi E.E.Sule Department of Electrical and Electronic Engineering The Federal University of Technology AkureNigeria

It is known that the power consumption and efficiency of an equipment owes directly to its power factor.The lower the power factor of the equipment the more the energy consumption of such equipment and vice-versa.Hence,the need to develop an equipment to measure accurately the operating power factor of domestic and industrial equipment and appliances[1].The operating principle of this power factor meter design is based on Zero Crossing detection principle,the principle is utilized using Arduino Nano,instrument transformers,LM324 operational amplifier,generic resistor,generic XOR Gate 7488 and 2X16LCD.The input current and voltage signal is taken by the transformers and sent to the op-amp which carries out the zero crossing detection in order to get the time difference after which the microcontroller does the calculation to determine the power factor and the deficit reactive power which is then displayed on an interface[2].

关键词： Arduino nano Zero crossing power factor Inductive load Capacitive load

Realizing high thermoelectric performance via selective resonant doping in oxyselenide BiCuSeO

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Nano Research 2023年第1期16卷 1679-1687页

作者： Yue-Xing Chen Wenning Qin Adil Mansoor Adeel Abbas Fu Li Guang-xing Liang Ping Fan Muhammad Usman Muzaffar Bushra Jabar Zhen-hua Ge Zhuang-hao Zheng F1 Shenzhen Key Laboratory of Advanced Thin Films and Applications Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong ProvinceCollege of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen 518060China Faculty of Materials and Manufacturing Beijing University of TechnologyBeijing 100124China International Center for Quantum Design of Functional Materials(ICQD) Hefei National Laboratory for Physical Sciences at Microscale(HFNL)and CAS Center for Excellence in Quantum Information and Quantum PhysicsUniversity of Science and Technology of ChinaHefei 230026China Faculty of Materials Science and Engineering Kunming University of Science and TechnologyKunming 650093China

Tuning the charge carrier concentration is imperative to optimize the thermoelectric(TE)performance of a material.For BiCuSeO based oxyselenides,doping efforts have been limited to optimizing the carrier concentration.In the present work,dual-doping of In and Pb at Bi site is introduced for p-type BiCuSeO to realize the electric transport channels with intricate band characteristics to improve the power factor(PF).Herein,the impurity resonant state is realized via doping of resonant dopant In over Pb,where Pb comes forward to optimize the Fermi energy in the dual-doped BiCuSeO system to divulge the significance of complex electronic structure.The manifold roles of dual-doping are used to adjust the elevation of the PF due to the significant enhancement in electrical properties.Thus,the combined experimental and theoretical study shows that the In/Pb dual doping at Bi sites gently reduces bandgap,introduces resonant doping states with shifting down the Fermi level into valence band(VB)with a larger density of state,and thus causes to increase the carrier concentration and effective mass(m*),which are favorable to enhance the electronic transport significantly.As a result,both improved ZTmax=0.87(at 873 K)and high ZTave=0.5(at 300–873 K)are realized for InyBi(1−x)−yPbxCuSeO(where x=0.06 and y=0.04)system.The obtained results successfully demonstrate the effectiveness of the selective dual doping with resonant dopant inducing band manipulation and carrier engineering that can unlock new prospects to develop high TE materials.

关键词： thermoelectric material BiCuSeO dual-doping power factor figure of merit

Efficient Single-Stage Bridgeless AC to DC Converter Using Grey Wolf Optimization

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Computer Systems Science & Engineering 2022年第11期43卷 487-499页

作者： Prema Kandasamy K.Prem Kumar Department of Electrical and Electronics Engineering Thangavelu Engineering CollegeChennai-600097India Department of Electrical and Electronics Engineering Rajalakshmi Engineering CollegeChennai-602105India

Bridgeless single-stage converters are used for efficient(alternative current)AC-(direct current)DC conversion.These converters control generators,likeelectromagnetic meso-and micro-scale generators with low voltage.power factorcorrection helps increase the factor of the power supply.The main advantage ofthe power factor is it shapes the input current for increasing the real power of theAC supply.In this paper,a two-switch bridgeless rectifier topology is designedwith a power factor correction capability.For the proposed converter topologyto have good power quality parameters,the closed loop scheme,which uses thegrey wolf optimization(GWO)algorithm,is implemented.The successes ofGWO encourage this research to implement GWO in the topology.The performanceof the proposed topology is analyzed under different load conditions.Simulation is carried out using the MATLAB/Simulink environment,and theresults are compared with those of conventional(proportional integral derivative)PID and(particle swarm optimization)PSO controllers.To validate the simulation results,a 350-W hardware prototype is implemented,and the voltage ripple,efficiency,and power factor under different load conditions are analyzed and tabulated.The comparative study clearly indicates that the proposed convertertopology with a closed loop control scheme using the GWO algorithm improves the power factor to 0.9732 and reduces the voltage ripple to 0.12%with a conversion efficiency of 98.25%.

关键词： Bridgeless AC converter DC converter GWO controller power factor

SMOGN,MFO,and XGBoost Based Excitation Current Prediction Model for Synchronous Machine

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Computer Systems Science & Engineering 2023年第9期46卷 2687-2709页

作者： Ping-Huan Kuo Yu-Tsun Chen Her-Terng Yau Department of Mechanical Engineering National Chung Cheng UniversityChiayi62102TaiwanChina Advanced Institute of Manufacturing with High-Tech Innovations(AIM-HI) National Chung Cheng UniversityChiayi62102TaiwanChina

The power factor is the ratio between the active and apparent power,and it is available to determine the operational capability of the intended circuit or the parts.The excitation current of the synchronous motor is an essential parameter required for adjusting the power factor because it determines whether the motor is under the optimal operating status.Although the excitation current should predict with the experimental devices,such a method is unsuitable for online real-time prediction.The artificial intelligence algorithm can compensate for the defect of conventional measurement methods requiring the measuring devices and the model optimization is compared during the research process.In this article,the load current,power factor,and power factor errors available in the existing dataset are used as the input parameters for training the proposed artificial intelligence algorithms to select the optimal algorithm according to the training result,for this algorithm to have higher accuracy.The SMOGN(Synthetic Minority Over-Sampling Technique for Regression with Gaussian Noise)is selected for the research by which the data and the MFO(Moth-flame optimization algorithm)are created for the model to adjust and optimize the parameters automatically.In addition to enhancing the prediction accuracy for the excitation current,the automatic parameter adjusting method also allows the researchers not specializing in the professional algorithm to apply such application method more efficiently.The final result indicated that the prediction accuracy has reached“Mean Absolute Error(MAE)=0.0057,Root Mean Square Error(RMSE)=0.0093 andR2 score=0.9973”.Applying this method to themotor control would be much easier for the power factor adjustment in the future because it allows the motor to operate under the optimal power status to reduce energy consumption while enhancing working efficiency.

关键词： Synchronous machine power factor excitation current active power apparent power

Accurate and explainable machine learning for the power factors of diamond-like thermoelectric materials

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Journal of Materiomics 2022年第3期8卷 633-639页

作者： Zhe Yang Ye Sheng Cong Zhu Jianyue Ni Zhenyu Zhu Jinyang Xi Wu Zhang Jiong Yang Materials Genome Institute Shanghai UniversityShanghai200444China School of Computer Engineering and Science Shanghai UniversityShanghai200444China School of Mechanics and Engineering Science Shanghai UniversityShanghai200444China

The application of machine learning(ML)-based methods to the study of thermoelectric(TE)materials is promising.Although conventional ML algorithms can achieve high prediction performance,their lack of interpretability severely obstructs researchers from extracting material-oriented insights from ML models.In this work,high ML-based prediction performance was achieved with respect to TE power factors(PFs),and the results were well understood by the SHapley Additive exPlanations(SHAP),a method to identify the correlations between targets and descriptors.We designed a robust PF prediction model for diamond-like compounds via a stacking technique,and the model achieved a coefficient of determination value above 0.95 on the test set.From the SHAP analysis,the PFs were negatively correlated with electronegativity and positively correlated with the descriptor“volume per atom”based on the previously reported dataset.TE domain knowledge was adopted to understand these correlations.This work shows that ML models can achieve high accuracy while exhibiting good interpretability,making them useful for materials scientists.

关键词： Machine learning Thermoelectric materials Interpretability power factor