원문정보
초록
영어
This paper presents the Wind Energy Conversion System (WECS) combining Permanent Magnet Synchronous Generator (PMSG) with PSO-RNN controller. The proposed hybrid technique uses Particle Swarm Optimization (PSO) algorithm along with Recurrent Neural Network (RNN) which generates the optimal dc reference current. The proposed Maximum Power Point Tracking (MPPT) algorithm finds the maximum operating point from the power curve which is based on the dc link voltage and current. The proposed hybrid technique is simulated using Matlab / simulink and the performance of the WECS is evaluated and compared with Proportional Integral (PI) and RNN methods. The errors in Power Coefficient, Tip Speed Ratio, DC link voltages and Average Power are evaluated.
목차
1. Introduction
2. Overview of WTGS
2.1. Model of Wind Turbine
2.2. Modeling of PMSG:
3. Proposed Controller for Optimizing MPPT Control Technique in WTGS
3.1. Organization of Proposed System Structure
3.2. Optimizing dc Voltage in the Wind Generation System using PSO Algorithm
3.3. Process for Recurrent Neural Network Training
4. Results and Discussion
4.1. Performance Analysis and Evaluation Metric
5. Conclusion
References