Abstract

This article proposes a control system for a ship power station using a doubly-fed-induction generator (DFIG). Firstly, the author analyzes the characteristics of the power generation system using DFIG based on the rotor sync signal technique and then proposes a control system for adjusting the active and reactive power of the generator supplied to the grid. The advantage of the rotor sync technique is that two control channels of active and reactive power are independent. It is favorable for the author proposes the Fuzzy-PID controller for each control channel. The result is that active and reactive power always follow the desired values in a fast response time. Thus, the author applies this proposed system for automatic load division in a parallel power grid on the ship. The entire generator system has well ensured the load distribution between the shaft-generator and the grid in the case of changes in load consumption and rotor speed of the generator.

Highlights

  • The shaft generator system on the ship was first introduced in 1982

  • The results show that the active and reactive powers of doubly-fed-induction generator (DFIG) 2 fed into the grid always follow the desired values (70% power of the load) with a short transition time

  • Considering some of the previous research on controlling the active power and reactive power of DFIG fed into the grid [26, 27], the results show that the min transition time is about 0.05s

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Summary

INTRODUCTION

The shaft generator system on the ship was first introduced in 1982. After a short time, the company MAN B&W has studied its application possibilities. The author proposes a new model of shaft generator using DFIG based on the rotor sync signal as Figure 3. It includes: The main machine has the role of pulling the propeller. The first channel controls the d component rotor current of DFIG2 (2isd), with its input is coefficient GP, and its output is the 2isd (proportion with the active power P). Based on the characteristic of the object, the author chose a triangle shape Because this shape presents the relationship between the Fuzzy set with each input value clearly and it is easy to program in the controller.

The inference laws of fuzzy controller
Findings
CONCLUSION
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