Power demand prediction in smart microgrids using interacting multiple model Kalman filtering

Abstract

Optimized management of energy resources within smart microgrids may require an approximation of near future power demands to institute efficient scheduling of tasks. Since demands are volatile in shorter time spans, localized short-term prediction of demand is non-trivial. Local prediction requires efficiency of calculations to minimize computational… (More)
DOI: 10.1145/2939940.2939947

Topics

15 Figures and Tables

Cite this paper

@inproceedings{Farmer2016PowerDP, title={Power demand prediction in smart microgrids using interacting multiple model Kalman filtering}, author={Michael Farmer and Mark Allison}, booktitle={RSES '16}, year={2016} }