Research On The Decommissioning Strategy Of Distribution Network Equipment Considering Risk And Benefit Cost

With the deepening of energy structure change and the construction of new power system,the future distribution network will assume the responsibility of energy transformation in addition to guaranteeing safe and reliable power supply.To meet this new trend,the investment in distribution network is increasing,the scale of assets is expanding,and the emergence of new technologies and modes is pushing the operation and production and planning management of distribution network to change slowly.However,the asset management system of distribution network and the technical means of condition monitoring have not yet been updated and developed,especially with the increase in the number of old equipment in distribution network,the maintenance and decommissioning management of distribution equipment will face a serious challenge.The decision of equipment maintenance and decommissioning is influenced by many factors,such as the health condition of the equipment itself,benefit cost and system power supply reliability,etc.The traditional decommissioning management mode is mostly oriented to ensure safe and reliable power supply,lacking scientific decision-making methods and ignoring the actual health condition and economic evaluation of the equipment,which will easily cause a huge waste of equipment life value and investment.Therefore,to address the limitations of the existing distribution network equipment decommissioning decision model,this paper establishes a collaborative optimization model of equipment overhaul/retirement strategy considering system effectiveness,risk and benefit cost.The main research contents are as follows:Firstly,the key characteristic quantities of various equipment health indices are determined by analyzing the causes of faults in distribution transformers,overhead lines and switchgear.And the subjective and objective weights of each index are determined by using hierarchical analysis and entropy method respectively.Thus,a health index calculation model based on the combination of subjective and objective weights is established.Secondly,based on the relationship between maintenance,health index and failure rate,a dynamic correction method of failure rate curve based on BP neural network is proposed.A three-layer neural network model with 5 inputs and 2 outputs is established,and the fitting effect and effectiveness of the proposed model are verified by 200 transformers sample data in a certain area.Then,by analyzing the impact of maintenance and decommissioning on the system,the concept of "system effectiveness" is introduced.And two attributes of comprehensive cost investment and system power supply reliability are extracted.Considering the subjective cognition of decision makers,a model for calculating the prospect value of these two attributes based on the prospect theory is established.Thus,a cooperative optimization model of overhaul/retirement strategy considering system effectiveness and risk with the objective of maximizing the comprehensive prospect value and the constraints of maintenance time and system risk level is constructed.Finally,the above model is simulated and verified by genetic algorithm.The results show that the collaborative optimization of equipment overhaul/retirement strategy can take into account the subjective preferences of decision makers for economy and reliability,and changing the importance of attributes can make the optimization results converge to the subjective preferences of decision makers.The results of the study can be used as a reference for the decision of decommissioning and renewal of distribution network equipment.