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With distribution static synchronous compensator control strategy and

Author: ZhangHong
Tutor: MengXiangPing
School: Changchun University of
Course: Control Theory and Control Engineering
Keywords: Distribution Static synchronous compensation Power quality Reinforcement learning adaptive PID
CLC: TM761
Type: Master's thesis
Year: 2010
Downloads: 121
Quote: 0
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Abstract


The problem of electric energy quality affects seriously the safe operation of power network, especially reactive power and harmonics. As a new var compensator, Reactive power source is an indispensable part of improving power quality, reducing net loss and keeping system stable in the power network. Distribution Static Synchronous Compensator (D-STATCOM) can be an effective solution to power quality problems such as voltage fluctuation and flicker, three-phase voltage imbalance and harmonics pollution, which attract extensive attention for its perfect performance.Based on the theory of dqO reference fame transformation the dynamic mathematical model of D-STATCOM in dqO reference frame was deduced by introducing switch function. The stability of D-STATCOM is proved. In this paper, reinforcement learning adaptive PID control is used for D-STATCOM based on research with the traditional PID. The control strategy is reinforcement learning adaptive with integral action under instantaneous power balance frame for voltage source inverter based D-STATCOM,with the control strategies presented in this paper, the disadvantages of mutual coupling of Active current and reactive current and tradition PID control are overcome, the device capability are realized more sufficiently, reactive power compensation, harmonics and imbalance suppression become more effective. The control performances of the proposed control strategies and tradition PID control strategy are simulated and analyzed with simulink, which results show that the applying of D-STATCOM to improve power quality is better. In the research of control strategy, reinforcement learning adaptive PID control on the ability of improving the power factor and filter of voltage and current is more competent than tradition PID. The reinforcement learning adaptive PID control for inverter has many advantages such as wide stability range, quick dynamic response, and easy realization.device-level was analyzed and discussed, According to the simulation model, system hardware and software design of D-STATCOM are designed.

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CLC: > Industrial Technology > Electrotechnical > Transmission and distribution engineering, power network and power system > Power system automation > Automatically adjusts
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