Multi-objective SVG (static var generator) generalized proportional integral error control method of microgrid

Abstract

The invention discloses a multi-objective SVG generalized proportional integral error control method of microgrid. The method comprises the following steps: a target configuration rule module calculates a compensation current instruction signal of the SVG according to a current real-time task object and the real-time sampling data of common point voltage, power factor, harmonics, and voltage deviation on direct current side of the SVG and under the premise of not exceeding security capacity of the SVG; a generalized proportional integral controller and an error correction controller together perform the task for transforming the SVG compensation current instruction signal to a control pulse signal of a SVG power device, and conduct closed-loop control to ensure that the compensation current actually outputted by the SVG tracks the instruction signal. According to the invention, the capacity of the SVG can be utilized fully to reduce resource waste; and the method can improve the tracking control accuracy and ensure the stable operation of the SVG by combining a fast-adjustable two-position control structure with a non-differential generalized proportional integral control structure.

Description

technical field [0001] The invention relates to an SVG control method, in particular to a micro-grid multi-objective SVG generalized proportional-integral error correction control method. Background technique [0002] With the widespread application of SVG in power grids, SVG has good effects on voltage support, reactive power compensation, and harmonic control. How to use control methods to fully utilize SVG capacity has attracted more and more attention. The control variables of SVG multi-objective control mainly include voltage, current, power factor, voltage distortion rate, current distortion rate and so on. In the process of SVG capacity allocation, there is mutual influence among these variables, which makes it impossible to establish an accurate mathematical model, and also makes the traditional PID control method unsuitable. At present, the application of SVG is mainly to compensate reactive power alone or only to control harmonics. The capacity of SVG has not been...

AI Technical Summary

Problems solved by technology

In the process of SVG capacity allocation, there is mutual influence among these variables, which makes it impossible to establish an accurate mathematical model, and also makes the traditional PID control method unsuitable

At present, the application of SVG is mainly to compensate reactive power alone or only to control harmonics. The capacity of SVG has not been fully utilized, and there is a great waste of resources.

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