Distribution network maintenance scheme optimization method and device based on element failure model

Abstract

The invention provides a distribution network maintenance scheme optimization method and a distribution network maintenance scheme optimization device based on an element failure model. The method comprises the steps of establishing a transformer aging failure model, an overhead line aging failure model, a transformer random failure model and an overhead line random failure model; obtaining a transformer element failure model according to the transformer aging failure model and the transformer random failure model; obtaining an overhead line element failure model according to the overhead line aging failure model and the overhead line random failure model; establishing a distribution network maintenance optimization model according to the transformer element failure model and the overhead line element failure model on the basis of distribution network system constraints and maintenance resource constraints by using the minimum failure risk of a distribution network system as an object; solving a distribution network through a genetic algorithm on the basis of the distribution network maintenance optimization model, so as to obtain an optimal distribution network maintenance scheme.

Description

technical field [0001] The invention relates to the technical field of power systems, in particular to a method and device for optimizing a distribution network maintenance plan based on a component failure model. Background technique [0002] Distribution network equipment maintenance is a very important work content in the daily operation of distribution network, involving equipment management, load forecasting, topology analysis and other aspects, requiring the coordination of multiple departments such as biotechnology, scheduling, line and change inspection , directly related to the interests of power supply enterprises and users. A reasonable maintenance plan plays a positive role in improving the economics of maintenance and preventing equipment failures. It not only helps to improve the reliability of power supply, but also reduces the loss of electricity sales. At present, many power supply enterprises still use manual scheduling to formulate maintenance plans. Howe...

AI Technical Summary

Problems solved by technology

At present, many power supply enterprises still use manual scheduling to formulate maintenance plans. However, due to the complexity of power distribution equipment and many maintenance tasks, manual maintenance plans not only require a lot of work, but also fail to achieve power supply reliability and maintenance economy. sexual demands

However, the existing auxiliary decision-making methods for maintenance plan optimization mostly start from the anticipated deterministic equipment / component failures, but do not scientifically analyze and model potential failures.

For component failures, failure is essentially a probabilistic event, not deterministic, and has the characteristics of randomness. The deterministic failures expected at the time of formulating the maintenance plan often do not occur in reality, resulting in equipment / components based on expectations. There is often a certain deviation between the maintenance plan formulated for the fault and the actual production requirements

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