scholarly journals Method for calculating the resistance of an asynchronous squirrel cage motor according to passport data and estimation of its error

2021 ◽  
Vol 29 (3) ◽  
pp. 98-110
Author(s):  
Viktor I. Kotenev ◽  
Alexander D. Stulov
Keyword(s):  
Reactive Power ◽  
Total Error ◽  
Small Error ◽  
Algebraic Equations ◽  
Maximum Torque ◽  
Active Resistance ◽  
Squirrel Cage ◽  
Electromagnetic Power ◽  
Passport Data ◽  
Nominal Mode

A simpler method is proposed for determining the resistances of an induction motor (total inductive resistance, active resistance of the stator and reduced active resistance of the rotor) according to reference data. Three algebraic equations are obtained from the equations of reactive power dissipation and electromagnetic power in the nominal mode and the equation of electromagnetic power in the critical mode: the first is relative to three resistances, the second is the equation of the dependence of the active resistance of the stator relative to the total inductive resistance, and the third is the active resistance of the rotor relative to the total inductive resistance. An iterative method is proposed for solving this system of equations, which gives a small error already at the second step of the calculations. When assessing the error of the method, the specified values ​​of the electromagnetic power and the multiplicity of the maximum torque were used, which are expressed relative to the reference resistances of the control motors. An estimate is given of the total error from the imperfection of the method and the discrepancy between the reference values ​​of the multiplicity of the maximum torque and power on the motor shaft with their refined values ​​calculated from the resistances from the reference book. Based on the calculated resistances in the nominal mode, the dependences of the active and inductive resistances of the motor are constructed using an accurate and approximate method.

Operation and control of a stand-alone power system with integrated multiple renewable energy sources

2021 ◽  
pp. 0309524X2110241
Author(s):  
Nindra Sekhar ◽  
Natarajan Kumaresan
Keyword(s):  
Renewable Energy ◽  
Reactive Power ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Solar Pv ◽  
Power Requirement ◽  
Squirrel Cage ◽  
Hysteresis Controller ◽  
Squirrel Cage Induction Generator ◽  
And Control

To overcome the difficulties of extending the main power grid to isolated locations, this paper proposes the local installation of a combination of three renewable energy sources, namely, a wind driven DFIG, a solar PV unit, a biogas driven squirrel-cage induction generator (SCIG), and an energy storage battery system. In this configuration one bi-directional SPWM inverter at the rotor side of the DFIG controls the voltage and frequency, to maintain them constant on its stator side, which feeds the load. The PV-battery also supplies the load, through another inverter and a hysteresis controller. Appropriately adding a capacitor bank and a DSTATCOM has also been considered, to share the reactive power requirement of the system. Performance of various modes of operation of this coordinated scheme has been studied through simulation. All the results and relevant waveforms are presented and discussed to validate the successful working of the proposed system.

scholarly journals Reactive power compensation in squirrel cage rotor type of three-phase induction motors

2020 ◽  
Vol 830 ◽  
pp. 032035
Author(s):  
G Tjahjono ◽  
F G Ray ◽  
I Fahmi ◽  
C P Tamal ◽  
R H Modok ◽  
...  
Keyword(s):  
Reactive Power ◽  
Induction Motors ◽  
Reactive Power Compensation ◽  
Squirrel Cage ◽  
Three Phase ◽  
Cage Rotor ◽  
Rotor Type

scholarly journals Effect of vocabulary mapping for conditions on phenotype cohorts

2018 ◽  
Vol 25 (12) ◽  
pp. 1618-1625 ◽  
Author(s):  
George Hripcsak ◽  
Matthew E Levine ◽  
Ning Shang ◽  
Patrick B Ryan
Keyword(s):  
Knowledge Engineering ◽  
Total Error ◽  
False Negative ◽  
International Classification Of Diseases ◽  
Error Rates ◽  
Small Error ◽  
Snomed Ct ◽  
Order Of Magnitude ◽  
Systematized Nomenclature Of Medicine ◽  
Gold Standards

Abstract Objective To study the effect on patient cohorts of mapping condition (diagnosis) codes from source billing vocabularies to a clinical vocabulary. Materials and Methods Nine International Classification of Diseases, Ninth Revision, Clinical Modification (ICD9-CM) concept sets were extracted from eMERGE network phenotypes, translated to Systematized Nomenclature of Medicine - Clinical Terms concept sets, and applied to patient data that were mapped from source ICD9-CM and ICD10-CM codes to Systematized Nomenclature of Medicine - Clinical Terms codes using Observational Health Data Sciences and Informatics (OHDSI) Observational Medical Outcomes Partnership (OMOP) vocabulary mappings. The original ICD9-CM concept set and a concept set extended to ICD10-CM were used to create patient cohorts that served as gold standards. Results Four phenotype concept sets were able to be translated to Systematized Nomenclature of Medicine - Clinical Terms without ambiguities and were able to perform perfectly with respect to the gold standards. The other 5 lost performance when 2 or more ICD9-CM or ICD10-CM codes mapped to the same Systematized Nomenclature of Medicine - Clinical Terms code. The patient cohorts had a total error (false positive and false negative) of up to 0.15% compared to querying ICD9-CM source data and up to 0.26% compared to querying ICD9-CM and ICD10-CM data. Knowledge engineering was required to produce that performance; simple automated methods to generate concept sets had errors up to 10% (one outlier at 250%). Discussion The translation of data from source vocabularies to Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT) resulted in very small error rates that were an order of magnitude smaller than other error sources. Conclusion It appears possible to map diagnoses from disparate vocabularies to a single clinical vocabulary and carry out research using a single set of definitions, thus improving efficiency and transportability of research.

scholarly journals Determination of Minimum Reactive Power Compensation for the Stable Operation of Type-1 WTG in Grid-Connected Mode

2020 ◽  
Vol 8 (5) ◽  
pp. 4656-4660
Keyword(s):  
Wind Farm ◽  
Reactive Power ◽  
Reactive Power Compensation ◽  
Induction Generator ◽  
Stable Operation ◽  
Squirrel Cage ◽  
Squirrel Cage Induction Generator ◽  
Reactive Power Compensator ◽  
The Impact

The current energy demand scenario leads to tremendous increase in the renewable energy sector, but the integration of these renewable causes various stability issues of the system. Increasing share Wind energy has several shortages due to its energy harnessed from the wind. These shortages can be improved by compensating reactive power into the wind plant. The wind farm consist of fixed speed squirrel cage Induction generator absorbs reactive power from the grid for stable operation and it can be injected using reactive power compensator. In this context, the main aim of the research is to find the minimum reactive power compensation required for stable operation for different rating of Type-1 WTG in grid connected mode. In this paper, a detailed model of constant speed Squirrel Cage Induction Generator is carried out in MATLAB/SIMULINK-2017a to analyze the need of reactive power compensation to maintain voltage and frequency stability of the system during normal condition. The work also focuses on to investigate the impact of induction generator inertia level on compensation level. The modified IEEE 5-bus radial distribution system is used to conduct these investigations and the simulation results clearly show that: (1) The necessity and minimum additional reactive power support to the wind farm to improve and maintain stability of the system; (2) the inertia level of wind farm and reactive power compensator level both are independent each other.

scholarly journals Classification and Detection of Faults in Induction Motor using Dwt with Deep Learning Methods under the Time-Varying and Constant Load Conditions

2019 ◽  
Vol 8 (3) ◽  
pp. 1413-1418
Keyword(s):  
Neural Network ◽  
Induction Motor ◽  
Reactive Power ◽  
Induction Machine ◽  
Load Condition ◽  
Constant Load ◽  
Discrete Wavelet ◽  
Time Varying ◽  
Squirrel Cage ◽  
Three Phase

This article proposed a method to detect the faults in multi-winding induction motor using Discrete Wavelet transform combined with Deep Belief Neural Network (DBNN). This technique relies on the instantaneous reactive power signal decomposition, from which detail coefficients and wavelet approximations are extracted which are termed as features. In order to obtain a robust diagnosis, this article proposed to classify the feature vectors extracted from DWT analysis of power signals using DBNN (Deep Belief Neural Network) to distinguish the motors state. Subsequently, in order to validate the proposed approach, a three phase squirrel cage induction machine is simulated under MATLAB software. To check the effectiveness of the proposed method of fault diagnosis the motor is simulated in different simulation environments like time varying load and constant load condition. Promising results were obtained and the performance of DBNN i.e. 99.75% accuracy. The proposed algorithm is compared with various other state-of-art methods and the comparison proves its robustness in diagnosing the fault in motors.

Micro-Grid Stability in Gapa Island Using Reactive Power Control of STATCOM (Case Study)

2014 ◽  
Vol 905 ◽  
pp. 411-415
Author(s):  
Do Heon Lee ◽  
Dong Wan Kim ◽  
Eel Hwan Kim
Keyword(s):  
Reactive Power ◽  
Control Method ◽  
Storage System ◽  
Synchronous Generator ◽  
Energy Storage System ◽  
Static Synchronous Compensator ◽  
Squirrel Cage ◽  
Micro Grid ◽  
Squirrel Cage Induction Generator ◽  
Battery Energy

This paper proposes a installation of a static synchronous compensator (Statcom) used battery energy storage system (BESS) for compensting the reactive power of the micro-grid in Gapa island. At present, the micro-grid in Gapa island has two squirrel cage induction generator (SCIG), and it consums a lot of the reactive power. To reduce the capacity of the Statcom, a SCIG is replaced by a permanent magnet synchronous generator (PMSG). The simulation will be carried out in two cases: (i) real system with two SCIGs; (ii) modified system with one SCIG, one PMSG and the Statcom. With the statcom, the reactive power is compensated and the grid voltage is stable. The simulation results will valuate the effectiveness of the proposed control method.

scholarly journals Guaranteed a posteriori error bounds for low-rank tensor approximate solutions

2020 ◽  
Author(s):  
Sergey Dolgov ◽  
Tomáš Vejchodský
Keyword(s):  
Total Error ◽  
Approximation Error ◽  
Approximate Solutions ◽  
Posteriori Error ◽  
Energy Norm ◽  
Low Rank ◽  
Algebraic Equations ◽  
Lagrange Equations ◽  
Rank Tensor ◽  
Linear Algebraic Equations

Abstract We propose a guaranteed and fully computable upper bound on the energy norm of the error in low-rank tensor train (TT) approximate solutions of (possibly) high-dimensional reaction–diffusion problems. The error bound is obtained from Euler–Lagrange equations for a complementary flux reconstruction problem, which are solved in the low-rank TT representation using the block alternating linear scheme. This bound is guaranteed to be above the energy norm of the total error, including the discretization error, the tensor approximation error and the error in the solver of linear algebraic equations, although quadrature errors, in general, can pollute its evaluation. Numerical examples with the Poisson equation and the Schrödinger equation with the Henon–Heiles potential in up to 40 dimensions are presented to illustrate the efficiency of this approach.

scholarly journals SIMULASI ALIRAN DAYA PADA SISTEM TENAGA LISTRIK DI GARDU INDUK GANDUL PT. PLN (PERSERO) MENGGUNAKAN SOFTWARE MATLAB POWER SYSTEM ANALYSIS TOOLBOX (PSAT) 2.1.7 DENGAN METODE NEWTON RAPHSON

2020 ◽  
Vol 5 (1) ◽  
pp. 14-20
Author(s):  
Endiansyah Pradana ◽  
Rif’an Muhammad ◽  
Imam Arif Raharjo
Keyword(s):  
Power System ◽  
Power Flow ◽  
System Analysis ◽  
Reactive Power ◽  
Flow Simulation ◽  
Numerical Data ◽  
Small Error ◽  
Active Power ◽  
Simulation Software ◽  
Power System Analysis

ABSTRACT This study aims to determine the results of the simulation of the power flow transformer 4 10 buses in the Gandul Substation of PT. PLN (Persero) with MATLAB Power System Analysis Toolbox (PSAT) 2.1.7. To find out the results of a comparison of the simulation of the flow of power 4 transformer 10 buses in the Gandul substation PT. PLN (Persero) MATLAB PSAT 2.1.7 software with ETAP software 12.6.Data analysis technique used in this study is quantitative descriptive analysis method. Descriptive will only describe the state of a symptom that has been recorded and then processed according to its function. Descriptive statistics are statistics that have the task of organizing and analyzing numerical data, in order to provide a regular, concise and clear picture of a phenomenon, event or situation, so that certain understandings or meanings can be drawn.The results of research on power flow at the Gandul substation PT. PLN (Persero) uses MATLAB Power System Analysis Toolbox (PSAT) 2.1.7 simulation of power flow with MATLAB PSAT 2.1.7 software completed at Power Flow Completed 0.066 s with a number of 2 iterations, iteration 1 shows Maximum Convergency Error 0.0011257 and iteration 2 shows Maximum Convergency Error 1.2621e-06. While the result of the simulation software ETAP 12.6 the number of oterations completed in iteration 3.The results of power flow simulation software MATLAB PSAT 2.1.7 and ETAP 12.6 on Active Power (MW) have a fairly big error, which is 11.5%. The largest error value generated is 11.5%, namely the feeder Sheen and Niece. Then, the results of power flow simulation software MATLAB PSAT 2.1.7 and ETAP 12.6 on Reactive Power (MVar) have a fairly big error, which is 24.4%. The largest error value generated is 24.4%, which is found in Canggah feeders. And the results of power flow simulation software MATLAB PSAT 2.1.7 and ETAP 12.6 against voltage (kV) have a fairly small error. Almost every feeder has the same error from the Rainbow feeder to the niece.The conclusion in this study is the results of power flow simulation with MATLAB Power System Analysis Toolbox 2.1.7 show the value of Active Power of 15.1362 MW and Reactive Power of 10.0349 MVar. Meanwhile, the results of power flow simulation with ETAP 12.6 software show the value of Active Power of 15.3720 MW and Reactive Power of 10.3510 MVar.   ABSTRAK Penelitian ini bertujuan Untuk mengetahui hasil dari simulasi aliran daya Trafo 4 10 bus di Gardu Induk Gandul PT. PLN (Persero) dengan software MATLAB Power System Analysis Toolbox (PSAT) 2.1.7. Untuk mengetahui hasil perbandingan simulasi aliran daya Trafo 4 10 bus di Gardu Induk Gandul PT. PLN (Persero) software MATLAB PSAT 2.1.7 dengan software ETAP 12.6. Teknik analisis data yang digunakan pada penelitian ini adalah metode analisis desktriptif kuantitatif. Deskriptif hanya akan mendeskripsikan keadaan suatu gejala yang telah direkam kemudian diolah sesuai dengan fungsinya. Statistik deskriptif adalah statistik yang mempunyai tugas mengorganisasi dan menganalisa data angka, agar dapat memberikan gambaran secara teratur, ringkas dan jelas, mengenai suatu gejala, peristiwa atau keadaan, sehingga dapat ditarik pengertian atau makna tertentu. Hasil penelitian aliran daya di gardu induk Gandul PT. PLN (Persero) menggunakan software MATLAB Power System Analysis Toolbox (PSAT) 2.1.7 simulasi aliran daya dengan software MATLAB PSAT 2.1.7 selesai pada Power Flow Completed 0.066 s dengan jumlah 2 iterasi, iterasi 1 menunjukkan Maximum Convergency Error 0.0011257 dan iterasi 2 menunjukkan Maximum Convergency Error 1.2621e-06. Sedangkan hasil simulasi software ETAP 12.6 jumlah iterasi selesai pada iterasi 3. Hasil simulasi aliran daya software MATLAB PSAT 2.1.7 dan ETAP 12.6 pada Daya Aktif (MW) mempunyai error yang cukup besar, yaitu 11.5%. Nilai error terbesar yang dihasilkan sebesar 11.5% yaitu pada penyulang Kemilau dan Keponakan. Lalu, hasil simulasi aliran daya software MATLAB PSAT 2.1.7 dan ETAP 12.6 pada Daya Reaktif (MVar) mempunyai error yang cukup besar, yaitu 24.4%. Nilai error terbesar yang dihasilkan sebesar 24.4%, yaitu terdapat pada penyulang Keponakan. Dan hasil simulasi aliran daya software MATLAB PSAT 2.1.7 dan ETAP 12.6 terhadap tegangan (kV) mempunyai error yang cukup kecil. Hampir setiap penyulang mempunyai error yang sama dari penyulang Pelangi hingga Keponakan. Kesimpulan dalam penelitian ini yaitu Hasil simulasi aliran daya dengan software MATLAB Power System Analysis Toolbox 2.1.7 menunjukkan nilai Daya Aktif sebesar 15.1362 MW dan Daya Reaktif sebesar 10.0349 MVar. Sedangkan, hasil simulasi aliran daya dengan software ETAP 12.6 menunjukkan nilai Daya Aktif sebesar 15.3720 MW dan Daya Reaktif sebesar 10.3510 MVar.

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