Design of Wind Turbine Output Voltage Control Systems in Multi-Input Buck Converter Using Fuzzy Logic Control for Battery Charging

This paper presents the details of design and implementation of DC-DC Buck converter as solar charger. This converter is designed for charging a battery with a capacity of 100 Ah (Ampere Hours) which has a charging voltage of 27.4 volts. The constant voltage method is selected on battery charging with the specified set point. To ensure the charging voltage is always on the set point, the duty cycle control of buck converter is set using Fuzzy Logic Control (FLC). The design implementation has been tested on PV (photovoltaic) with 540WP capacity. Based on the test results, this method is quite well implemented on the problem charger

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Analysis and Control of Fault Ride-Through Capability Improvement for Wind Turbine Based on a Permanent Magnet Synchronous Generator Using an Interval Type-2 Fuzzy Logic System

Energies ◽

10.3390/en12122289 ◽

2019 ◽

Vol 12 (12) ◽

pp. 2289 ◽

Cited By ~ 3

Author(s):

Altan Gencer

Keyword(s):

Fuzzy Logic ◽

Wind Turbine ◽

Control Systems ◽

Fuzzy Logic Control ◽

Synchronous Generator ◽

Permanent Magnet Synchronous Generator ◽

Logic Control ◽

Fault Ride Through ◽

Interval Type

Recently, wind energy conversion systems in renewable energy sources have attracted attention due to their effective application. Wind turbine systems have a complex structure; however, traditional control systems are inadequate in answering the demands of complex systems. Therefore, expert control systems are applied to wind turbines, such as type-1 and interval type-2 fuzzy logic control (IT-2 FLC) systems. An IT-2 FLC system is used to solve the complexity of the wind turbine system and increases the efficiency of the wind turbine. This paper proposes a new control approach using the IT-2 FLC method applied to a wind turbine based on a permanent magnet synchronous generator (PMSG) to improve the transient stability during grid faults. An IT-2 FLC was designed to enhance the fault ride-through performance of a wind turbine and was implemented to control the machine side converter and grid side converter of a wind turbine. The proposed algorithm performance of a wind turbine based on a PMSG was investigated for different types of grid fault. The analysis results verify that the interval type-2 fuzzy logic control system is robustly utilized under different operational conditions.

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Implementation of Fuzzy Logic Control on Battery Charging System

ACMIT Proceedings ◽

10.33555/acmit.v3i1.34 ◽

2019 ◽

Vol 3 (1) ◽

pp. 118-126 ◽

Cited By ~ 1

Author(s):

Prihangkasa Yudhiyantoro

Keyword(s):

Complex System ◽

Fuzzy Logic ◽

Fuzzy Logic Control ◽

Expert Knowledge ◽

Experimental Result ◽

Rule Base ◽

Battery Charging ◽

Charging System ◽

Logic Control ◽

Charging Control

This paper presents the implementation fuzzy logic control on the battery charging system. To control the charging process is a complex system due to the exponential relationship between the charging voltage, charging current and the charging time. The effective of charging process controller is needed to maintain the charging process. Because if the charging process cannot under control, it can reduce the cycle life of the battery and it can damage the battery as well. In order to get charging control effectively, the Fuzzy Logic Control (FLC) for a Valve Regulated Lead-Acid Battery (VRLA) Charger is being embedded in the charging system unit. One of the advantages of using FLC beside the PID controller is the fact that, we don’t need a mathematical model and several parameters of coefficient charge and discharge to software implementation in this complex system. The research is started by the hardware development where the charging method and the combination of the battery charging system itself to prepare, then the study of the fuzzy logic controller in the relation of the charging control, and the determination of the parameter for the charging unit will be carefully investigated. Through the experimental result and from the expert knowledge, that is very helpful for tuning of the embership function and the rule base of the fuzzy controller.

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