Estimation error analysis due to aggregation interval
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Advancements to the power grid facilitates retail consumers to be participants. Smart Grid initiative allows two way communications by means of distributed intelligent devices and thus allows better controlling and monitoring of the distribution system. Two critical concerns in this regard are: (i) data requirement for demand management lead to additional communication infrastructure, and (ii) increased data processing and storage requirements. In addition customer privacy may be compensated based on the data sharing frequency. On the other hand the higher the data sampling interval is the lower the control accuracy would be. The prime focus of this work is determining the link between the data and power network layers. This work focuses on developing a methodology to quantify the relationship between the required data and the prediction/estimation accuracy. Voltage drop in a feeder and the total power loss are considered as two applications in this work and the impact of data sharing frequency is analyzed. Since the relationship is feeder configuration dependent, the analysis was performed on IEEE 13 Node and 34 Node Test Feeders and the procedure and results are presented in this paper.
Thesis (M.S.)--Wichita State University, College of Engingeering, Dept. of Electrical Engineering and Computer Science