Research Of Optimal Placement And Control Strategy Of Unified Power Flow Controller

The power system has entered the new stage of large system,ultra high voltage long distance transmission,cross regional networking.The development of the social economy changes the mode of operation and management of modern grid.That has higher and higher requirements of the safe,stable,efficient,flexible power control.With the presentation and development of flexible AC transmission system(FACTS),the realization of various control strategies greatly improve the capability of power flow control.Unified Power Flow Controller(UPFC)is the most complex and attractive compensator in FACTS.That is to say,UPFC can control the line impedance,phase angle,active and reactive power flexibilly,which has gained wide attention since it was proposed.In this thesis,UPFC is studied from UPFC discrete-time nonlinear optimal controller design and finding its optimal location and capacity.Firstly,the present situation of application of UPFC and the influence to the grid were briefly introduced.The basic structure and working principle of UPFC were discussed.Then by analyzing the working principle of the parallel and series VSC presented UPFC voltage regulator and flow control principle.Further more,the thesis describes the UPFC voltage source models and equivalent power injection model.Secondly,based on fuzzy clustering and power flow sensitivity,the method of the optimal location of UPFC is proposed.By selecting a plurality of voltage stability index as the criterion,using fuzzy clustering algorithm to determine that the node is weak.And the next pssage introduces the concept of line active power flow performance index.Then use the line power flow to calculate partial derivative of voltage amplitude and phase angle of UPFC series injected voltage.That is the sensitivity of UPFC.And then determine the optimal location of UPFC based on the the size of the sensitivity.Then analyze the example in the IEEE14 bus system.Based on the installation location which UPFC is determined,using the improved parameter adaptive harmony search(IPAHS)algorithm to solve UPFC optimal capacity.Through the introduction of UPFC calculated capacity principle,to establish the function relationship of UPFC capacity and series injected voltage amplitude.In addition to that,maximize the economic costs and benefits of investment as optimization objective using IPAHS algorithm to determine the installation capacity of UPFC.Finally,establish the single machine infinite bus system model of UPFC to solve the discrete-time state equation of UPFC.In view of the problems existing in the traditional optimization controller,this thesis presents a based on neural network approximation of the finite time ε-iterative ADP algorithm for nonlinear discrete time controller.With UPFC series voltage as the input of the controller,the neural networks are utilized to approximate the cost function and the control law of the ε-iterative ADP algorithm.Then calculate the optimal performance index,and this control law is the optimal one.Simulation results in MATLAB/SIMULINK show that the controller can quickly damp the system and improve the stability of the system compared with the conventional LQR controller and PSS.