Design and Analysis Considering Magnet Usage of Permanent Magnet Synchronous Generator Using Analytical Method

In this study, the characteristic analysis of a permanent magnet synchronous generator was performed using the analytical method, and the validity of the analytical method was compared with that of the finite element method (FEM). For the initial design, the rotor size was selected using the torque per rotor volume method, and the stator size was selected according to the saturation of the stator iron core. In addition, fast Fourier transform analysis was performed to determine the appropriate magnet thickness point, and it was confirmed that the open circuit and armature reaction magnetic flux densities were consistent with the FEM analysis results. Based on the analytical method, the generator circuit constants (phase resistance, back EMF, and inductance) were derived to construct an equivalent circuit. By applying the equivalent circuit method to the derived circuit constants, the accuracy of the equivalent circuit method was confirmed by comparing the FEM and experimental results.

Perancangan Permanent Magnet Synchronous Generator Kapasitas 22 KVA Menggunakan Metode Finite Element Method

Software berbasis Finite Element Method (FEM) dapat digunakan untuk perancangan generator dikarenakan mampu membuat suatu model generator dengan menampilkan bentuk, cara kerja dan medan magnet pada generator. Kelebihan lainnya yaitu dapat menampilkan energi listrik yang dihasilkan oleh generator dalam bentuk kurva karakteristik tegangan, arus, daya masukan, daya keluaran, torsi dan efisiensi generator. Rancangan dibuat dengan menggunakan kombinasi pemodelan 12 slot 8 pole (12S8P). Tujuan penelitian ini adalah menganalisa hasil perbandingan pengujian rancangan generator sinkron magnet permanent dengan dilakukan pengujian simulasi variasi beban pada generator. Hasil uji simulasi berbeban dilakukan analisa dengan melihat grafik besaran tegangan, arus, torsi, daya masukan, daya keluaran dan efisiensi pada generator. Generator dengan output efisiensi terbesar pada perancangan 12 slot 8 Pole sebesar 94 % dengan tegangan output sebesar 445,01 V, arus sebesar 63,58 A torsi sebesar 232,88 Nm, daya masukan sebesar 21948,29 Watt, daya keluaran sebesar 20525,16 Watt. Oleh karena itu variasi beban pada perancangan generator mempengaruhi nilai dari hasil keluaran generator tersebut.

New application of artificial neural network-based direct power control for permanent magnet synchronous generator

Purpose. This article proposes a new strategy for Direct Power Control (DPC) based on the use of Artificial Neural Networks (ANN-DPC). The proposed ANN-DPC scheme is based on the replacement of PI and hysteresis regulators by neural regulators. Simulation results for a 1 kW system are provided to demonstrate the efficiency and robustness of the proposed control strategy during variations in active and reactive power and in DC bus voltage. Methodology. Our strategy is based on direct control of instant active and reactive powers. The voltage regulator and hysteresis are replaced by more efficient and robust artificial neuron networks. The proposed control technique strategy is validated using MATLAB / Simulink software to analysis the working performances. Results. The results obtained clearly show that neuronal regulators have good dynamic performances compared to conventional regulators (minimum response time, without overshoots). Originality. Regulation of continuous bus voltage and sinusoidal currents on the network side by using artificial neuron networks. Practical value. The work concerns the comparative study and the application of DPC based on ANN techniques to achieve a good performance control system of the permanent magnet synchronous generator. This article presents a comparative study between the conventional DPC control and the ANN-DPC control. The first strategy based on the use of a PI controller for the control of the continuous bus voltage and hysteresis regulators for the instantaneous powers control. In the second technique, the PI and hysteresis regulators are replaced by more efficient neuronal controllers more robust for the system parameters variation. The study is validated by the simulation results based on MATLAB / Simulink software.