Equipment operation and maintenance plan dynamic scheduling system and optimization method

Abstract

The invention provides an equipment operation and maintenance plan dynamic scheduling system and method. The system comprises a production plan generation module, a priority decision module, an operation and maintenance resource calculation module, a constraint condition analysis module, a transaction collection module and a production plan update module, wherein the production plan generation module generates operation and maintenance production plans and various elements of the production plans; the priority decision module arranges an execution order of the production plans according to priority division rules; the operation and maintenance resource calculation module calculates all operation and maintenance resource information and a maximum resource value; the constraint condition analysis module reads the operation and maintenance resource information and maximum value information and judges whether operation and maintenance resources exceed a limit in combination with the concurrency of operation and maintenance work, and if the result is yes, the priority decision module arranges the execution order of all the production plans again; the transaction collection module collects a transaction category of the operation and maintenance work; and the production plan update module performs update of the production plans according to the corresponding transaction category, so that the priority decision module arranges the execution order of all the production plans again or the constraint condition analysis module re-judges whether the operation and maintenance resources exceed the limit. Through the dynamic scheduling system and method, the operation and maintenance production plans can be automatically judged and updated.

Description

technical field [0001] The invention relates to the technical field of production plan arrangement and execution, in particular to a dynamic scheduling system and optimization method for equipment operation and maintenance plans. Background technique [0002] Substation equipment is the basis for the operation of the grid system, and its equipment status directly affects the reliability of the grid operation. Grid failures are also caused by equipment failures, and once the grid failure is caused by the substation equipment, it is more likely to develop into a large-scale power outage. The stable state of substation equipment requires regular maintenance and timely handling of hidden dangers or defects of equipment to avoid the occurrence and development of hidden dangers or defects. [0003] The operation and maintenance of substation equipment mainly involves frequent manual inspections, regular preventive maintenance, testing and defect-based elimination work, which is th...

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Problems solved by technology

[0003] The operation and maintenance of substation equipment mainly involves frequent manual inspections, regular preventive maintenance, testing and defect-based elimination work, which is the basic guarantee for the safe operation of substation equipment. The traditional operation and maintenance plan is generally based on various The annual plan is compiled in the regulation cycle, which only includes regular manual inspections and regular preventive maintenance. There are often large-scale plan changes due to power maintenance and defect elimination.

With the current economic development, the scale of substation equipment has grown rapidly, and the advancement of power reform has placed higher and higher labor productivity requirements on the maintenance and operation personnel of power grid companies. It has become more difficult to arrange and adjust operation and maintenance plans. Brings a very high risk of equipment under-maintenance and over-maintenance

[0004] Existing technologies on the automatic generation and optimization of equipment operation and maintenance plans mainly study related target optimization algorithm theory, lack of operable dynamic plan scheduling and adjustment capabilities, and when considering multi-constraint and multi-objective complex problems, a large number of parameters Unable to actually obtain, the algorithm is difficult to achieve large-scale application, limited to the stage of theoretical research and sample testing

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