Rekabentuk penstabil sistem kuasa saraf - kabur bersepadu berkomputer untuk set alternator mikro

• Main Author: Jamaan, Saiful
• Format: Thesis
• Language: English
• Published: 2009
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/id/eprint/16995/1/SaifulJamaanPFKE2008.pdf; http://eprints.utm.my/id/eprint/16995/
• Institution: Universiti Teknologi Malaysia

A Power System Stabilizer is a control system that is used to reduce low frequency oscillation which occurs in a system interconnection that is caused by disturbances. Control methodology; Fuzzy Logic, Neural Network, Self tuning Proportional Integral Differential, Fuzzy Logic Proportional Integral Differential, and Fuzzy Logic which is tuned by neural network system had been used in the power system interconnection. The disadvantage is that it took more time to reduce oscillation and stabilize the system after disturbances or a huge sudden load change. It can cause the generator to be out off synchronization, affecting the transmit Power System Stabilizer of the electric power. Digitally integrated Fuzzy logic control system and artificial neural network has been developed to overcome the disadvantage and in order to obtain a better dynamic characteristic. Digital control hardware is consist of Analogue to Digital Converter, Digital to Analogue Converter, synchronizing hardware and operational hardware had been made for this research. The developed Power System Stabilizer has been tested in Makmal Kuasa Lanjut, Faculty of Electrical Engineering, Universiti Teknologi Malaysia. Electric Power Generator that had been used is a set of micro alternator which consist of 3.5 kW synchronous generator and a 5 kW direct current motor that has been connected to infinite bus. An computerized integrated fuzzy logic and neural control system method is used. From the test for sudden load change and a power transmission that is changed, it was found out that the used integrated fuzzy logic and neural control gave about 5 - 10% improvement of output characteristic average as compared to existing control system.