Statistical Approach in Analyzing of Advanced Metering Data in Power Distribution Grid
Abstract
In last period many distribution system operators (DSO) invest significant amount of money in smart metering system. Those investments are in part due to regulatory obligations and in part due to needs of DSO (utilities) for knowledge about electric energy consumption. Term electric energy consumption refers not only on real consumption of electric energy but also on data about peak power, unbalance, voltage profiles, power losses etc. Data which DSO can have depends on type of smart metering system. Further, smart meters as source of data can be implemented in transformer stations (TS) MV/LV and in LV grid at consumer level. Generally, smart meters can be placed in any node of distribution grid. As amount of smart meters is greater, the possibility of data analysis is greater. In this paper a smart metering system of J.P Elektroprivreda HZ HB d.d, Mostar, Bosnia and Herzegovina will be presented. One statistical approach for analyzing of advanced metering data of TS MV/LV will be presented. Statistical approach presented here is powerful tool for analyzing great amount of data from distribution grid in simple way. Main contribution of this paper is in using results obtained from statistical analysis of smart meter data in distribution grid analyzing and in maintenance/investment planning.
Keywords
distribution grid, smart meteringThis work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
I. Ramljak and D. Bago, "Statistical Approach in Analyzing of Advanced Metering Data in Power Distribution Grid," in Journal of Communications Software and Systems, vol. 15, no. 2, pp. 159-165, April 2019, doi: 10.24138/jcomss.v15i2.683
@article{ramljak2019statisticalapproach, author = {Ivan Ramljak and Drago Bago}, title = {Statistical Approach in Analyzing of Advanced Metering Data in Power Distribution Grid}, journal = {Journal of Communications Software and Systems}, month = {4}, year = {2019}, volume = {15}, number = {2}, pages = {159--165}, doi = {10.24138/jcomss.v15i2.683}, url = {https://doi.org/10.24138/jcomss.v15i2.683} }