4,229 research outputs found
A Distributed Demand-Side Management Framework for the Smart Grid
This paper proposes a fully distributed Demand-Side Management system for
Smart Grid infrastructures, especially tailored to reduce the peak demand of
residential users. In particular, we use a dynamic pricing strategy, where
energy tariffs are function of the overall power demand of customers. We
consider two practical cases: (1) a fully distributed approach, where each
appliance decides autonomously its own scheduling, and (2) a hybrid approach,
where each user must schedule all his appliances. We analyze numerically these
two approaches, showing that they are characterized practically by the same
performance level in all the considered grid scenarios. We model the proposed
system using a non-cooperative game theoretical approach, and demonstrate that
our game is a generalized ordinal potential one under general conditions.
Furthermore, we propose a simple yet effective best response strategy that is
proved to converge in a few steps to a pure Nash Equilibrium, thus
demonstrating the robustness of the power scheduling plan obtained without any
central coordination of the operator or the customers. Numerical results,
obtained using real load profiles and appliance models, show that the
system-wide peak absorption achieved in a completely distributed fashion can be
reduced up to 55%, thus decreasing the capital expenditure (CAPEX) necessary to
meet the growing energy demand
Polynomial-Time Approximation Scheme for Data Broadcast
The data broadcast problem is to find a schedule for broadcasting a given set
of messages over multiple channels. The goal is to minimize the cost of the
broadcast plus the expected response time to clients who periodically and
probabilistically tune in to wait for particular messages.
The problem models disseminating data to clients in asymmetric communication
environments, where there is a much larger capacity from the information source
to the clients than in the reverse direction. Examples include satellites,
cable TV, internet broadcast, and mobile phones. Such environments favor the
``push-based'' model where the server broadcasts (pushes) its information on
the communication medium and multiple clients simultaneously retrieve the
specific information of individual interest.
This paper presents the first polynomial-time approximation scheme (PTAS) for
data broadcast with O(1) channels and when each message has arbitrary
probability, unit length and bounded cost. The best previous polynomial-time
approximation algorithm for this case has a performance ratio of 9/8
A note on on-line broadcast scheduling with deadlines
In this paper, we study an on-line broadcast scheduling problem with deadlines, in which the requests asking for the same page can be satisfied simultaneously by broadcasting this page, and every request is associated with a release time, deadline and a required page with a unit size. The objective is to maximize the number of requests satisfied by the schedule. In this paper, we focus on an important special case where all the requests have their spans (the difference between release time and deadline) less than 2. We give an optimal online algorithm, i.e., its competitive ratio matches the lower bound of the problem.postprin
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