The authors discuss how technologies normally associated with Internet of Things may be applied to demand response in smart grids. The authors present a system consisting of wireless hard-ware and intelligent control software that facilitates the participation of residential and commercial loads in demand response initiatives within smart grids. Obviously, the ability to observe and control these devices digitally is essential to such initiatives. The main objectives of this work are to develop a cost-effective and ultra-low power meshed network, introduce proximity estimation and self-location capability as well as, formulate a learning-based optimization algorithm for load automation.
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Deese et al. (2018) studied this question.
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