Improved transient characteristics of output voltage of marine synchronous generator
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Maintaining a constant voltage in a power system is very important for the protection of the electrical and electronic equipment connected to the power system. There are many types of equipment available to keep power quality high, but the most important is an automatic voltage regulator. The control method of an automatic voltage regulator of a synchronous generator is mostly phase control or proportional–integral–derivative (PID) control. However, this paper is compares neural-network predictive control with PID control, and confirms that the proposed neural-network predictive control is effective in adjusting the voltage through experiments conducted by computer simulation. It is shown that the terminal voltage of the PID control was measured with a rise time of 0.863 s, a settling time of 3.08 s, and an overshoot of 8.23%. The proposed method measured a rise time of 0.58 s, a settling time of 1.02 s, and an overshoot of 0.23%. Through the use of the proposed control method, therefore, the output voltage was improved for 48% of rising time, 3.02 times for the settling time, and 10% in overshoot. In this paper, it is proven that neural-network-predictive control is more effective than PID control in maintaining the constant output voltage of synchronous generators.
Abstract
Maintaining a constant voltage in a power system is very important for the protection of the electrical and electronic equipment connected to the power system. There are many types of equipment available to keep power quality high, but the most important is an automatic voltage regulator. The control method of an automatic voltage regulator of a synchronous generator is mostly phase control or proportional–integral–derivative (PID) control. However, this paper is compares neural-network predictive control with PID control, and confirms that the proposed neural-network predictive control is effective in adjusting the voltage through experiments conducted by computer simulation. It is shown that the terminal voltage of the PID control was measured with a rise time of 0.863 s, a settling time of 3.08 s, and an overshoot of 8.23%. The proposed method measured a rise time of 0.58 s, a settling time of 1.02 s, and an overshoot of 0.23%. Through the use of the proposed control method, therefore, the output voltage was improved for 48% of rising time, 3.02 times for the settling time, and 10% in overshoot. In this paper, it is proven that neural-network-predictive control is more effective than PID control in maintaining the constant output voltage of synchronous generators.
참고문헌 (21)
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