1,332 research outputs found
From Packet to Power Switching: Digital Direct Load Scheduling
At present, the power grid has tight control over its dispatchable generation
capacity but a very coarse control on the demand. Energy consumers are shielded
from making price-aware decisions, which degrades the efficiency of the market.
This state of affairs tends to favor fossil fuel generation over renewable
sources. Because of the technological difficulties of storing electric energy,
the quest for mechanisms that would make the demand for electricity
controllable on a day-to-day basis is gaining prominence. The goal of this
paper is to provide one such mechanisms, which we call Digital Direct Load
Scheduling (DDLS). DDLS is a direct load control mechanism in which we unbundle
individual requests for energy and digitize them so that they can be
automatically scheduled in a cellular architecture. Specifically, rather than
storing energy or interrupting the job of appliances, we choose to hold
requests for energy in queues and optimize the service time of individual
appliances belonging to a broad class which we refer to as "deferrable loads".
The function of each neighborhood scheduler is to optimize the time at which
these appliances start to function. This process is intended to shape the
aggregate load profile of the neighborhood so as to optimize an objective
function which incorporates the spot price of energy, and also allows
distributed energy resources to supply part of the generation dynamically.Comment: Accepted by the IEEE journal of Selected Areas in Communications
(JSAC): Smart Grid Communications series, to appea
Real-time Power Aware Routing in Wireless Sensor Networks
Many mission-critical wireless sensor network applications must resolve the inherent conflict between the tight resource constraints on each sensor node, particularly in terms of energy, with the need to achieve desired quality of service such as end-to-end real-time performance. To address this challenge we propose the Real-time Power-Aware Routing (RPAR) protocol. RPAR achieves required communication delays at minimum energy cost by dynamically adapting the transmission power and routing decisions based on packet deadlines. RPAR integrates a geographic forwarding policy cognizant of deadlines, power, and link quality with new algorithms for on-demand power adaptation and efficient neighborhood discovery. Simulations based on a realistic radio model of MICA2 motes show that RPAR significantly reduces the number of deadline misses and energy consumption when compared to existing real-time and energy-efficient routing protocols and beacon based neighborhood management schemes
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