Location Of Electric Wire Around The Meter Based On Smart Meter Data

Electric energy is an important energy for social construction,development and life.The operation of various industries and the smooth operation of economic society cannot be separated from electric energy.During the normal power supply or use of electricity,some illegal elements steal electricity by using many illegal technical means such as interference,modification or destruction of electric energy metering equipment and transmission lines,which has caused huge economic losses to power supply enterprises,affected the smooth operation of one side of the power grid,and also increased the personal and property risks of residents.Compared with other methods of stealing electricity,the phenomenon of users in the station area wiring around the electric energy meter is not easy to be found by the inspectors during offline inspection because of its concealed connection.At the same time,it is not as obvious as other types of stealing electricity in data representation and is more difficult to be found.In this paper,based on the electricity meter characteristics of the phenomenon of electricity theft around the meter and the underlying electricity principle,a threestep identification mechanism based on the Nearest Neighbor Propagation Clustering Algorithm and Shape-based BS Multi-point Detection Algorithm is developed to identify the electricity theft around the meter.Through the three steps of determining the suspected stolen radio station area,identifying the topology map of the station area,and locating the power stealing line around the meter,the location of the power stealing users in the high line loss station area is locked layer by layer,helping the power enterprises to give early warning and locate the location of the power stealing behavior more accurately.In the calculation example,this paper selects the unlabeled data of a real smart electricity meter in a certain area in the southwest to carry out the research and analysis around the electricity data of the total meter in the substation area,and selects the No.4 substation area with the largest judgment index as the most suspicious research object.With the help of the algorithm for identifying the distribution station area extension map proposed in this paper,the lack of topological structure information not provided in the calculation example is remedied.The example data in this paper does not reflect the user’s personal information and illegal labels,and is only used to verify the completeness and feasibility of the algorithm.