scholarly journals Noninvasive Load Identification Method Based on Feature Similarity

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Hongyan Li ◽  
Xianfeng Ding ◽  
Dan Qu ◽  
Jiang Lin
Keyword(s):  
Reactive Power ◽  
Electrical Equipment ◽  
Original Data ◽  
Load Identification ◽  
Device Identification ◽  
Power Load ◽  
Similarity Model ◽  
Feature Similarity ◽  
Low Efficiency ◽  
Feature Database

The traditional power load identification is greatly restricted in application because of its high cost and low efficiency. In this paper, the similarity model is established to realize the noninvasive load identification of power by determining the feature database for the equipment. Firstly, the wavelet decomposition method and the wavelet threshold processing method are used to remove abnormal points and reduce noise of the original data, respectively. Secondly, the transient and steady-state characteristics of electrical equipment (active power and reactive power, harmonic current, and voltage-current trajectory) are extracted, and the feature database for the equipment is established. Thirdly, the feature similarity is defined to describe the similarity degree of any two devices under a certain feature, and the similarity model of automatic recognition of a single device is established. Finally, the device identification and calculation of power consumption are carried out for the part of data in annex 2 of question A in the 6th “teddy cup” data mining challenge competition.

scholarly journals Calculation of the economy of electric energy in industrial electrical supply systems

2020 ◽  
Vol 22 (2) ◽  
pp. 65-74
Author(s):  
E. I. Gracheva ◽  
A. N. Gorlov ◽  
Z. M. Shakurova
Keyword(s):  
Power Supply ◽  
Energy Savings ◽  
Reactive Power ◽  
Electric Energy ◽  
Electrical Equipment ◽  
Total Power ◽  
Load Factor ◽  
Advantages And Disadvantages ◽  
Industrial Enterprises ◽  
Supply Systems

The article examines the main features of the layout of electrical equipment for shop networks of internal power supply with the definition of indicators for a group of shop customers connected to a single power center, affecting the choice of the structure of schemes for shop network sites. The parameters characterizing the circuit topology are revealed. A study is presented of the influence of the load factor of workshop transformers on their reactive power factor, it is proved by calculation by technical and economic criteria the feasibility of replacing a workshop transformer with two with a lower total power. The calculation of energy savings in the in-plant power supply systems. The type of dependences tgφ of transformers ТМ and ТСЗ with various rated powers in the function of loading transformers is established. The most significant factors of the growth of idle power losses during operation are presented. With determination of losses of active and reactive power and electricity in transformers and losses of active power in a high voltage distribution network A feasibility study was carried out on the options for internal power supply schemes with two transformers of lower power installed instead of one, and the feasibility of such a replacement to increase the efficiency of the equipment was proved and the estimated payback period for the investment capital was determined. A comparative analysis of the studied power supply schemes of industrial enterprises with the identification of their advantages and disadvantages.

scholarly journals The Method of Joint Compensation of Reactive Power, Load Balancing and Filtering Harmonics Currents of an Asymmetric Nonlinear Load Connected in a Triangle

2020 ◽  
pp. 455-461
Author(s):  
Mikhail A. Sherkunkov ◽  
Stepan G. Tiguntsev
Keyword(s):  
Load Balancing ◽  
Reactive Power ◽  
Low Voltage ◽  
Power Transformer ◽  
Nonlinear Load ◽  
Harmonic Currents ◽  
Power Load ◽  
Non Linear ◽  
Asymmetric Load ◽  
Partial Compensation

This article explores the method of joint suppression of harmonic currents, balancing currents and partial compensation of the reactive power of a non-linear asymmetric load connected in a triangle using a device installed on the low voltage side of a power transformer

Harmonic Analyses of Power Grid in Large-Capacity Groups of AC-DC-AC Frequency Speed Drag System

2013 ◽  
Vol 448-453 ◽  
pp. 1988-1993
Author(s):  
Ji Zhong Wang ◽  
Chao Nan Tong ◽  
Rui Li
Keyword(s):  
Power Supply ◽  
Pulse Width Modulation ◽  
Reactive Power ◽  
Power Grid ◽  
Harmonic Distortion ◽  
Power Load ◽  
Grid Side ◽  
Lc Filter ◽  
Harmonic Analyses ◽  
The Impact

Based on the synchronous machine in AC-DC-AC Frequency speed drag System, a new power supply method of phase shifting combination is proposed by a detailed study of the impact in the power grid harmonics. With regard to the main Motor drive system of hot-rolling finishing mills, a large number of varying parameters quantitative analysis is made respectively for power load, LC filter, pulse-width modulation circuit and transformer, in which the grid side harmonic rate and waveform distortion rate is focused on. The simulation results show that the power supply method with reasonable parameters design of the drag system can be drastically reduce the grid side harmonic interference that the total harmonic distortion is suppressed within 4.0%. Results of this study provides an effective method for the design of the factory drag system, reactive power compensation system as well as fault diagnosis of electric drag system.

scholarly journals A Primal Analysis System of Brain Neurons Data

2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Dong-Mei Pu ◽  
Da-Qi Gao ◽  
Yu-Bo Yuan
Keyword(s):  
Human Brain ◽  
Original Data ◽  
Type Number ◽  
Brain Neurons ◽  
Basic Procedure ◽  
Analysis System ◽  
Neuron Growth ◽  
Feature Database ◽  
Primal System

It is a very challenging work to classify the 86 billions of neurons in the human brain. The most important step is to get the features of these neurons. In this paper, we present a primal system to analyze and extract features from brain neurons. First, we make analysis on the original data of neurons in which one neuron contains six parameters: room type,X,Y,Zcoordinate range, total number of leaf nodes, and fuzzy volume of neurons. Then, we extract three important geometry features including rooms type, number of leaf nodes, and fuzzy volume. As application, we employ the feature database to fit the basic procedure of neuron growth. The result shows that the proposed system is effective.

scholarly journals Load Identification Using Harmonic Based on Probabilistic Neural Network

2019 ◽  
Vol 7 (1) ◽  
pp. 71-82
Author(s):  
Dimas Okky Anggriawan ◽  
Aidin Amsyar ◽  
Eka Prasetyono ◽  
Endro Wahjono ◽  
Indhana Sudiharto ◽  
...  
Keyword(s):  
Neural Network ◽  
Fourier Transform ◽  
Probabilistic Neural Network ◽  
Harmonic Distortion ◽  
Electrical Equipment ◽  
High Accuracy ◽  
Current Sensor ◽  
Harmonic Load ◽  
Load Identification ◽  
Current Waveform

Due to increase power quality which are caused by harmonic distortion it could be affected malfunction electrical equipment. Therefore, identification of harmonic loads become important attention  in the power system. According to those problems, this paper proposes a Load Identification using harmonic based on probabilistic neural network (PNN). Harmonic is obtained by experiment using prototype, which it consists of microcontroller and current sensor. Fast Fourier Transform (FFT) method to analyze of current waveform on loads become harmonic load data. PNN is used to identify the type of load. To load identification, PNN is trained to get the new weight. Testing is conducted To evaluate of the accuracy of the PNN from combination of four loads. The results demonstrate that this method has high accuracy to determine type of loads based on harmonic load

scholarly journals OPTIMIZE THE PERFORMANCE OF ELECTRICAL EQUIPMENT IN GAS SEPARATION STATIONS (DEGASSING STATION DS ) AND ELECTRICAL SUBMERSIBLE PUMPS OF OIL EQUIPMENT FOR OIL RUMAILA FIELD

2019 ◽  
Vol 21 (1-2) ◽  
pp. 141-145 ◽  
Author(s):  
Majid Abdulhameed Abdulhy Al-Ali ◽  
V. Yu. Kornilov ◽  
A. G. Gorodnov
Keyword(s):  
Power Factor ◽  
Reactive Power ◽  
Low Voltage ◽  
Voltage Drop ◽  
Reducing Power ◽  
Electrical Equipment ◽  
Voltage Regulation ◽  
Total Power ◽  
Electrical Submersible Pumps ◽  
Energy Compensation

Annotation: There are various types of electrical equipment used in the extraction of oil at the Rumaila field, with an average voltage of 11 kV and a low voltage of 0.4 kV. The most common elements in this class are transformers and reactors, engines and gas discharge lamps. All of this equipment consumes reactive power and reduces the value of the power factor. (Power factor is the ratio of kW to kVA). The closer the power factor to the maximum possible value of 1, the greater the benefit for the consumer and supplier. In case of low power factor, the current will be increased, and this high current will lead to (large line losses, an increase in the nominal total power of kVA and overhaul dimensions of electrical equipment, deterioration in voltage regulation process and an increase in voltage drop, a decrease in efficiency).Power factor improvement allows the use of smaller transformers, switchgear and cables, etc. as well as reducing power losses and voltage drop in an installation. Improving the power factor of an installation requires a bank of capacitors which acts as a source of reactive energy. These arrangements provide reactive energy compensation. In Rumila, An improvement of the power factor of an installation presents several technical and economic advantages, notably in the reduction of electricity bills, we save (685.854.007 Iraqi Dinar= 550.000 $) for one month . All this work takes 6 to 12 month.

scholarly journals Estimating PV Power from Aggregate Power Measurements within the Distribution Grid

2019 ◽  
Author(s):  
Evangelos Vrettos ◽  
Emre Kara ◽  
Emma Stewart ◽  
Ciaran Roberts
Keyword(s):  
Power Generation ◽  
Objective Function ◽  
Reactive Power ◽  
Active Power ◽  
Real Field ◽  
Time Varying ◽  
Distribution Grid ◽  
Pv Systems ◽  
Power Load ◽  
Power Measurements

The increased integration of photovoltaic (PV) systems in distribution grids reduces visibility and situational awareness for utilities, because the PV systems’ power production is usually not monitored by them. To address this problem, a method called Contextually Supervised Source Separation (CSSS) has been recently adapted for real-time estimation of aggregate PV active power generation from aggregate net active and reactive power measurements at a point in a radially configured distribution grid (e.g., substation). In its original version, PV disaggregation is formulated as an optimization problem that fits linear regression models for the aggregate PV active power generation and true substation active power load. This paper extends the previous work by adding regularization terms in the objective function to capture additional contextual information such as smoothness, by adding new constraints, by introducing new regressors such as ambient temperature, and by investigating the use of time-varying regressors. Furthermore, we perform extensive parametric analysis to inform tuning of the objective function weighting factors in a way that maximizes performance and robustness. The proposed PV disaggregation method can be applied to networks with either a single PV system (e.g., MW scale) or many distributed ones (e.g., residential scale) connected downstream of the substation. Simulation studies with real field recorded data show that the enhancements of the proposed method reduce disaggregation error by 58% in winter and 35% in summer compared with previous CSSS-based work. When compared against a commonly used transposition model based approach, the reduction in disaggregation error is more pronounced (78% reduction in winter and 45% in summer). Additional simulations indicate that the proposed algorithm is applicable also for PV systems with time-varying power factors. Overall, our results show that – with appropriate modeling and tuning – it is possible to accurately estimate the aggregated PV active power generation of a distribution feeder with minimal or no additional sensor deployment.

scholarly journals Neural Network-Based Study about Correlation Model between TCM Constitution and Physical Examination Indexes Based on 950 Physical Examinees

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yue Luo ◽  
Bing Lin ◽  
Shuting Zhao ◽  
Li He ◽  
Chuanbiao Wen
Keyword(s):  
Neural Network ◽  
Physical Examination ◽  
Network Model ◽  
Test Group ◽  
Network Models ◽  
Training Group ◽  
Original Data ◽  
Correlation Model ◽  
Learning Group ◽  
Low Efficiency

Purpose. To establish the correlation model between Traditional Chinese Medicine (TCM) constitution and physical examination indexes by backpropagation neural network (BPNN) technology. A new method for the identification of TCM constitution in clinics is proposed, which is trying to solve the problem like shortage of TCM doctor, complicated process, low efficiency, and unfavorable application in the current TCM constitution identification methods. Methods. The corresponding effective samples were formed by sorting out and classifying the original data which were collected from physical examination indexes and TCM constitution types of 950 physical examinees, who were examined at the affiliated hospital of Chengdu University of TCM. The BPNN algorithm was implemented using the C# programming language and Google’s AI library. Then, the training group and the test (validation) group of the effective samples were, respectively, input into the algorithm, to complete the construction and validation of the target model. Results. For all the correlation models built in this paper, the accuracy of the training group and the test group of entire physical examination indexes-constitutional-type network model, respectively, was 88% and 53%, and the error was 0.001. For the other network models, the accuracy of the learning group and the test group and error, respectively, was as follows: liver function (31%, 42%, and 11.7), renal function (41%, 38%, and 6.7), blood routine (56%, 42%, and 2.4), and urine routine (60%, 40%, and 2.6). Conclusions. The more the physical examination indexes are used in training, the more accurate the network model is established to predict TCM constitution. The sample data used in this paper showed that there was a relatively strong correlation between TCM constitution and physical examination indexes. Construction of the correlation model between physical examination indexes and TCM constitution is a kind of study for the integration of Chinese and Western medicine, which provides a new approach for the identification of TCM constitution, and it may be expected to avoid the existing problem of TCM constitution identification at present.

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