TY - JOUR
T1 - Using grouped smart meter data in phase identification
AU - Brint, A.
AU - Poursharif, G.
AU - Black, M.
AU - Marshall, Mark
PY - 2018/8
Y1 - 2018/8
N2 - Access to smart meter data will enable electricity distribution companies to have a far clearer picture of the operation of their low voltage networks. This in turn will assist in the more active management of these networks. An important current knowledge gap is knowing for certain which phase each customer is connected to. Matching the loads from the smart meter with the loads measured on different phases at the substation has the capability to fill this gap. However, in the United Kingdom at the half hourly level only the loads from groups of meters will be available to the network operators. Therefore, a method is described for using this grouped data to assist with determining each customer's phase when the phase of most meters is correctly known. The method is analysed using the load readings from a data set of 96 smart meters. It successfully ranks the mixed phase groups very highly compared with the single phase groups.
AB - Access to smart meter data will enable electricity distribution companies to have a far clearer picture of the operation of their low voltage networks. This in turn will assist in the more active management of these networks. An important current knowledge gap is knowing for certain which phase each customer is connected to. Matching the loads from the smart meter with the loads measured on different phases at the substation has the capability to fill this gap. However, in the United Kingdom at the half hourly level only the loads from groups of meters will be available to the network operators. Therefore, a method is described for using this grouped data to assist with determining each customer's phase when the phase of most meters is correctly known. The method is analysed using the load readings from a data set of 96 smart meters. It successfully ranks the mixed phase groups very highly compared with the single phase groups.
UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85042408163&partnerID=MN8TOARS
UR - https://www.sciencedirect.com/science/article/pii/S0305054818300480?via%3Dihub
U2 - 10.1016/j.cor.2018.02.010
DO - 10.1016/j.cor.2018.02.010
M3 - Article
SN - 0305-0548
VL - 96
SP - 213
EP - 222
JO - Computers and Operations Research
JF - Computers and Operations Research
ER -