Collaborative Optimization Approach for Grid Equipment Overhaul/Retirement Strategy Considering System Effectiveness and Risk
In order to improve the scientificity of grid equipment overhaul and decommissioning decision,we proposed a collaborative optimization method of equipment overhaul/decommissioning strategy considering system effectiveness and risk.Firstly,we analyzed the failure rate rollback effect of equipment overhaul,and established a BP neural net-work model to dynamically correct the failure rate curve based on data drive.Secondly,we analyzed the interaction effect between maintenance and decommissioning from the perspective of system effectiveness,and proposed two attrib-utes of comprehensive cost input and system reliability improvement,among which,cost indicators include equipment investment cost,operation and maintenance cost,failure cost,maintenance cost and depreciation loss,and reliability indicators are expressed in terms of system expected power outage,and then established the prospect model of each in-dicator based on the prospect theory.Thirdly,we established a collaborative optimization model of overhaul/retirement strategy with the overhaul time and retirement replacement time as optimization variables,the maximum integrated pros-pect value as the optimization objective,and the system risk level as the constraint.Finally,the proposed model is solved by genetic algorithm,and the effectiveness of the proposed method is verified by taking transformer equipment of a city regional distribution network as an example.
maintenance strategyequipment replacementneural networksystem effectivenessprospect theory
万方数据
维普
