Research On Production And Distribution Collaborative Optimization Of Energy Metering Device

The power industry is an important basic industry and public utilities related to people’s livelihood.The safety,stability and full supply of electricity are important guarantees for the comprehensive,coordinated and sustainable development of the national economy.The electric energy metering management work is directly related to the accounting of technical and economic indicators such as power generation,power supply and electricity consumption.Under the guidance of the development concept of"group operation,intensive development,lean management and standardization construction" of the State Grid,an efficient metering device production and logistics supply system is established.Equipment production and corresponding logistics support are organically coordinated and optimized to ensure a higher level of service and to cope with the increasing demand.In this context,this paper studies the collaborative optimization of production and distribution of energy metering devices.First,we introduces the related concepts,characteristics and processes of production and distribution.On this basis,we finds problems in operation.In-depth analysis,the root cause is the lack of synergy between production and distribution.Secondly,we analyzes the basic conditions and interdependence between the production and distribution,then determines the optimization objectives based on the problems existing in the operation.Thirdly,it deeply analyzes the influencing factors and cost components of production and distribution collaborative operation,and establishes a production and distribution collaborative optimization model of energy metering device with capacity constraints,gives the model solution ideas and algorithm design.In this paper,In this paper,the optimal strategy is obtained by branch and bound method.A genetic algorithm combining Lagrangian relaxation is designed to find the optimal solution to the problem that the optimal solution cannot be obtained.Finally,this paper takes A provincial-level measurement center as an example,uses relevant data for empirical analysis and proposes relevant management recommendations.