Model prediction control method for inhibiting low-frequency oscillation of electric power system based on controllable reactor

Abstract

The invention provides a model prediction control method for inhibiting low-frequency oscillation of an electric power system based on a controllable reactor. Through establishing electromagnetic transient simulation software PSCAD and an Matlab interactive simulation platform, a power system model which comprises the controllable reactor is established, thereby accurately describing a system real-time sate. The future dynamic track of a variable is controlled through a prediction system by means of the model prediction control method based on model characteristics of rolling optimization and feedback correction, and a real device adjustment range is visually added into an algorithm as a restraining condition, thereby improving defects caused by incapability of processing a system restraining condition according to a traditional method. The model prediction control method improves robustness and real-time performance of a controller through rolling optimization and feedback correction mechanisms. The model prediction control method further has advantages of flexibly processing restraining conditions for device control parameters, and improving negative effect of output upper / lower limit of a device and a time constant to controller performance.

Description

technical field [0001] The invention belongs to the field of power system stability and control, and in particular relates to a model predictive control method for suppressing low-frequency oscillation of a power system based on a controllable reactor. Background technique [0002] The main feature of model predictive control is online rolling optimization, and its control object is the trajectory of the control variable, and the optimization and solution of the system objective function is completed by predicting a certain performance index. The model predictive control algorithm combines rolling optimization with feedback correction to find the optimal solution for the time window corresponding to the current moment, and at the same time predicts and compensates future errors, forming a closed-loop optimal control. The model predictive control algorithm obtains accurate prediction of the future dynamic trajectory of the system by keeping the system model unchanged, reducin...

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Problems solved by technology

The disadvantage is that it is impossible to consider the constraints of the operating range of the device when designing the controller. Only a limiting link can be added to the controller, and the upper and lower limits are forced to be added to the controller output, resulting in unsatisfactory performance of the controller.

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