A Comparative simulation on the grounding grid system of a wind turbine with FEA software

Balci, Selami; Helvaci, Ömerhan

doi:10.30521/jes.613724

Cited by 4 publications

(6 citation statements)

References 16 publications

(22 reference statements)

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“…In the analysis settings stage, simulation conditions are determined for solution setup. According to the data obtained as a result of the analysis, reports such as numerical values, 2D/3D graphics and electromagnetic field drawings are obtained [17][18][19]. [17][18][19].…”

Section: Electromagnetic Modeling With Fea Softwarementioning

confidence: 99%

“…One of the software using FEA is Maxwell 2D/3D of ANSYS. Thus, the electromagnetic analysis can be performed during the development of permanent magnet alternators [15][16][17][18][19][20][21][22][23]. Before the prototype stage, the simulation studies with the electromagnetic analysis Maxwell software revealed that more realistic modeling was provided and the validity of the data obtained.…”

Section: Introductionmentioning

confidence: 99%

“…Before the prototype stage, the simulation studies with the electromagnetic analysis Maxwell software revealed that more realistic modeling was provided and the validity of the data obtained. In addition, the co-simulation facility provides both a power electronics circuit and a suitable opportunity for the performance testing together with electromagnetic modeling [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

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The electromagnetic modeling and the co-simulation of a direct drive axial flux permanent magnet synchronous generator

Akın

Balci

2020

Journal of Energy Systems

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Direct drive (gearless) axial flux permanent magnet synchronous generators (AFPMSG) are designed as multi-pole for use in vertical axis wind turbines. In particular, there are multi-pole core/coreless stator structures with axial flux for use in vertical axis wind turbines (WT) that can be designed in a compact structure at low wind speeds. In this study, the parametric simulation studies have been carried out according to rotor mechanical speeds with certain linear steps depending on different wind speed scenarios for an AFPMSG designed with 16-pole and cored stator for 5 kVA rated power with the finite element analysis (FEA) software. According to the analysis results obtained, the performance of the generator is reported and current, voltage, power losses and the flux distribution are investigated. In addition, the DC link voltage at the output of the DC-DC boost converter circuit due to wind speed changes is adaptively controlled for AFPMSG, which is co-simulated with the power electronics interface used at the generator output. Thus, both power electronics circuit performance and generator side have been simulated simultaneously with electromagnetic modeling. Therefore, the performance of the designed AFPMSG, which is modeled in three dimensions (3D) before the prototype stage, can be determined under more realistic conditions.

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Section: Electromagnetic Modeling With Fea Softwarementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The electromagnetic modeling and the co-simulation of a direct drive axial flux permanent magnet synchronous generator

Akın

Balci

2020

Journal of Energy Systems

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“…Today, electrical energy, as an indispensable type of energy, is vital in daily life, and possibly electrical and insulation faults that may occur during the use of electrical energy can pose a danger to the life of living things. Therefore, various protection measures such as grounding, insulation, and the use of low voltage must be taken to protect the life of living things and the system in electrical installations [1]. Grounding systems, an extremely safe protection measure, are the critical components of the protection system against lightning and fault currents of facilities, substations, transmission, and distribution lines in general electrical installations.…”

Section: Introductionmentioning

confidence: 99%

An Artificial Neural Network Model Based on Experimental Measurements for Estimating the Grounding Resistance

Kayabaşı

Yildiz

Balci

2022

Advances in Artificial Intelligence Research

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In grounding systems established in rocky and sandy lands where contact resistance with metal electrodes is high, contact resistance is generally the most critical parameter that changes the total grounding resistance value. Therefore, the nonlinear variation of the earth contact resistance according to the soil type cannot be taken into account in determining the grounding resistance with the traditional mathematical formulas given theoretically. This reduces the accuracy of grounding resistance determination. In this study, experimental measurements were made according to soil types and a data set was created. Then, to estimate the total grounding resistance of complex grounding systems, a classification was made using the multi-layer sensor (MLP) type ANN algorithm and the successful results were reported. Thus, according to the data set prepared based on experimental measurements, the proposed general classification algorithm approach can be applied to any grounding system. It presents a different technique from the previous literature as a pre-feasibility study for estimating the grounding resistance, especially before the grounding system installation, which is an early stage of the design process.

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“…Thus, there are different methods for analyzing energy data from wind energy sources and parameter estimation. It is desirable that the error rate is at the lowest values in parameter estimation operations, and in recent years, the most accurate and fastest data processing can be achieved with hardware and software developments in computer technology [15,16].…”

Section: Introductionmentioning

confidence: 99%

Analysis and Applicability of Mersin Region Wind Speed Data with Artificial Neural Networks

Akkaya

Gültekin

Sabancı

et al. 2020

Nevşehir Bilim Ve Teknoloji Dergisi

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In this study, wind speed data were analyzed in order to provide energy to the heating and electrical systems of a house with renewable energy sources in Mersin-Mut region. Three-year wind speed data is taken from the Turkey General Directorate of Meteorology in the region. Annual estimation was made with artificial neural networks using 28-day wind speed data for the studied area. Some of the wind data were used for training of the neural network, and some were used for testing. In the artificial neural network model, the most successful model was obtained by changing the number of neurons in the hidden layer. In the analysis made using eight neurons in the hidden layer, the lowest MAE and RMSE error values were calculated.While the number of neurons was eight, MAE and RMSE values were obtained as 0.4056 and 0.5403, respectively. In addition, analysis of wind data with WAsP software has been carried out for this region. Thus, the average instantaneous wind speed was determined according to the analysis studies.

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A Comparative simulation on the grounding grid system of a wind turbine with FEA software

Cited by 4 publications

References 16 publications

The electromagnetic modeling and the co-simulation of a direct drive axial flux permanent magnet synchronous generator

The electromagnetic modeling and the co-simulation of a direct drive axial flux permanent magnet synchronous generator

An Artificial Neural Network Model Based on Experimental Measurements for Estimating the Grounding Resistance

Analysis and Applicability of Mersin Region Wind Speed Data with Artificial Neural Networks

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