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To improve the quality of power distribution network parameters，an abnormal parameter identification and localization method for distribution networks based on smart meter measurements was proposed. The method transformed the nonlinear identification equation solving problem in traditional identification algorithms into the inference problem of the optimal distribution of parameters. On the basis of parameter identification，probability statistics method was used to locate abnormal parameters. Firstly，given the initial distribution of line parameters，Markov Chain Monte Carlo method was used to generate parameter samples. The parameter distribution was updated through tree estimation method and loss function. The expectation of the parameter distribution when the loss function converges was taken as the identified value of the line parameters. Secondly，the relative deviation distances of line parameters were calculated，and probability statistics method was used to judge whether the identified data are bad data or abnormal parameters. The bad data were directly eliminated. Finally，the abnormal factors causing the incorrect feedback of line parameters were analyzed to locate the abnormal parameters of the line. The identification process of parameters was demonstrated through an actual 29-node 10 kV feeder. The abnormal parameter location was carried out through an actual 97-node 10 kV feeder，proving the feasibility and effectiveness of the proposed method.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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