Power system maintenance and operation collaborative decision-making method oriented to toughness improvement

Abstract

The invention discloses a power system maintenance and operation collaborative decision-making method oriented to toughness improvement, and the method comprises the following steps: 1), carrying out the initialization, confirming the information of network parameters, maintenance demands, weather conditions and the like, and calculating the initial result of a maintenance plan and unit combination; 2) carrying out scene generation: generating a random scene by using a recursive sampling method according to an equipment forced outage rate model and a covariable state; and 3), carrying out dynamic scene updating circulation: a, in the latest scene, using a Lagrange relaxation technology to carry out iterative solution on collaborative optimization of a maintenance plan and a unit combination, namely, innermost layer circulation; b, due to the fact that the OR of the generator is related to the on-off state of the unit, according to the latest collaborative optimization result, using a recursive sampling method for updating the random scene of the generator; and carrying out iterative circulation between the step a and the step b until the maintenance plan, the unit combination and the dynamic scene are not changed any more. The method has the advantages of comprehensive covariable consideration and reasonable steps.

Description

technical field [0001] The invention relates to the technical field of electric power systems, in particular to a collaborative decision-making method for power system maintenance and operation oriented to improving resilience. Background technique [0002] The power system is affected by internal factors and external factors in operation, such as equipment aging, operating status, weather and environment, etc. These influencing factors are collectively referred to as covariates in this paper, and covariates introduce more variables to the power system. Certainty, the deterioration of covariates will lead to forced outage of equipment and increase system operating costs, and even cause blackouts; in recent years, major accidents such as blackouts in the United States and Canada, and blackouts in India have fully demonstrated that when making short-term power system maintenance plans , should be co-optimized with the unit combination, and the influence of covariates on the sy...

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Problems solved by technology

[0003] The existing technology has done research on the maintenance and outage plan of the power system, the unit combination plan, and the collaborative optimization of the two. These literatures have introduced optimization methods such as mixed integer programming, Lagrangian relaxation, and Benders decomposition into the model. And achieved good calculation results, but in most existing models, the uncertainty of the equipment is ignored. In a small number of literatures that consider the availability of equipment, it is usually assumed that the components are in the same pressure and health state, and have Uniform fault distribution. In fact, this assumption is unrealistic. Large power grids are widely distributed, and the aging status, operating status, and weather environment of equipment are different. These factors have little direct impact on maintenance plans and unit combinations. be discussed

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