Idle work optimization method suitable for on-line application

Abstract

The invention provides a powerless optimizing method based on a primal-dual interior-point method and a taboo search method. The method combines the primal-dual interior-point method and the taboo search method together and can quickly and conveniently process the powerless optimizing calculation of a large scale electric network with a discrete variable by utilizing the characteristics of good astringency of the primal-dual interior-point method as well as the characteristic of convenient processing on the discrete variable of the taboo search method. The optimizing method is also suitable for an automatic voltage control system.

Description

technical field [0001] The invention relates to the field of power system calculation, in particular to a reactive power optimization method suitable for on-line application. Background technique [0002] Power quality is an important indicator of power supply quality. Guaranteeing the voltage quality is also on the agenda. At present, the voltage control mainly depends on the reactive power adjustment of the power supply company. Insufficient reactive power will lead to a decrease in system voltage, insufficient utilization of electrical equipment, and even a series of accidents such as voltage collapse; and Excessive reactive power will also deteriorate the system voltage, endangering the safety of the system and equipment, and too much reactive power backup will waste unnecessary investment. In short, it is very necessary for power supply enterprises to reduce network loss and ensure voltage quality through online reactive power optimization. [0003] Reactive power opt...

AI Technical Summary

Problems solved by technology

The original dual interior point method has the advantages of fast calculation speed and does not slow down with the increase of network scale, but the discrete variable processing is not strong; while the tabu search calculation method has the advantages of strong discrete variable processing ability, it is different from other artificial intelligence methods. Compared with the computational efficiency, it is relatively fast, but compared with the traditional mathematical method, the computational efficiency is still low

In terms of solving the online reactive power optimization problem of large-scale power systems, the original dual interior point method can easily meet the speed requirements, but it is difficult to realize the selection of transformer taps and the optimal switching scheme of capacitor banks; tabu search calculation Although the method can easily realize the selection of transformer taps and the optimal switching scheme of capacitor banks, its iteration is a relatively long process, which cannot meet the real-time requirements of online reactive power optimization.

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