Impact of smart metering data aggregation on distribution system state estimation

Qipeng Chen, Dritan Kaleshi, Zhong Fan, Simon Armour

Research output: Contribution to journalArticle (Academic Journal)peer-review

28 Citations (Scopus)
241 Downloads (Pure)

Abstract

Pseudo medium/low voltage (MV/LV) transformer loads are usually used as partial inputs to the distribution system state estimation (DSSE) in MV systems. Such pseudo load can be represented by the aggregation of smart metering (SM) data. This follows the government restriction that distribution network operators (DNOs) can only use aggregated SM data. Therefore, we assess the subsequent performance of the DSSE, which shows the impact of this restriction - it affects the voltage angle estimation significantly. The possibilities for improving the DSSE accuracy under this restriction are further studied. First, two strategies that can potentially relax this restriction's impact are studied. First, the correlations among pseudo loads' errors are taken into account in the DSSE process and a power loss estimation method is proposed. Second, the investments (i.e., either adding measurement devices or increasing the original devices' accuracy) for the satisfactory DSSE results are assessed. All these are for addressing DNOs' concerns on this restriction.
Original languageEnglish
Pages (from-to)1426-1437
Number of pages12
JournalIEEE Transactions on Industrial Informatics
Volume12
Issue number4
Early online date26 May 2016
DOIs
Publication statusPublished - Aug 2016

Keywords

  • Smart meter
  • Distribution system state estimation
  • DSSE
  • Medium voltage power system

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