Research On Mathematic Model And Control Strategy Of Static Synchronous Series Compensator

Static synchronous series compensator (SSSC) with advantages of faster response, higher control precision and perfect dynamic performance is one of the important FACTS (Flexible AC Transmission Systems) devices. One of the main functions of SSSC is fast power flow control, which will be fully played by the choice of a good control method.A two- machine system mathematic model is built in a synchronously rotating d-q frame by using Park's transformation, in which the power systems with SSSC is controlled object. In the deeply research of the mathematic model, a d-q axes decoupling method based on the input transformation is proposed, using which the transmission line active and reactive power flow can be decoupled. Meanwhile, the decoupling model which can be used for dynamic decoupling and the transformation matrix which can be used for static decoupling are present. Afterwards the outer-loop controller of SSSC is designed with the neural network self-tuning PI algorithm in the basic of dynamic decoupling.According to the characteristics of SSSC control system, the control of SSSC is able to divide into two parts which have the controlled objects and can be independently designed respectively, namely inner-loop control and outer-loop control. In inner control strategy, because of the existence of inductance, the transmission line current will not be changes greatly before the capacitance voltage stability, of which is taken into account the traditional PID controller is used to maintain the stability of capacitor voltage, in which the SSSC device itself is selected as control object, and taken the capacitor voltage as control objective. However, considering the defects of tuning difficult, inadaptability and long response time of traditional PID controller, a neural network self-tuning PID controller which is emplied to control DC side capacitor voltage is designed using artificial neural networks and traditional PID controller. The three parameters of traditional PID controller can be tunning on line using neural network which has nonlinear fitting ability, so as to adapt the changes of controlled system. Therefore the traditional PID controller's defects arised due to fixed parameters are able to overcome.In outer control strategy, the traditional PID controller is used to control transmission line effective impedance, in which the transmission line installed with SSSC is selected as control object and taken the effective impedance as control objective. However, the traditional PID controller is not satisfied to morden control since the power system installed with SSSC is a complex nonlinear system. Therefore, the outer controller using Heuristic Dynamic Programming (HDP) is designed for SSSC. The controller based HDP contains a total of three neural networks, in which the model network is to estimate the system's output, the action network to give the control variable, and the critic network to value this control variable.In this paper, the complicacy and design difficulty of SSSC controller are able to debase because a large complex system is divided into two small systems whose controllers are easily designed correspondingly and control objects are unambiguous.A studying example is carried out to estimate good robustness and adaptability of the proposed controller in the MATLAB dynamic simulation platform. The results verified the availability and feasibility of the proposed control strategy in power flow control of power systems.