3,998 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
Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches
Peer-to-peer (P2P) energy trading has emerged as a next-generation energy
management mechanism for the smart grid that enables each prosumer of the
network to participate in energy trading with one another and the grid. This
poses a significant challenge in terms of modeling the decision-making process
of each participant with conflicting interest and motivating prosumers to
participate in energy trading and to cooperate, if necessary, for achieving
different energy management goals. Therefore, such decision-making process
needs to be built on solid mathematical and signal processing tools that can
ensure an efficient operation of the smart grid. This paper provides an
overview of the use of game theoretic approaches for P2P energy trading as a
feasible and effective means of energy management. As such, we discuss various
games and auction theoretic approaches by following a systematic classification
to provide information on the importance of game theory for smart energy
research. Then, the paper focuses on the P2P energy trading describing its key
features and giving an introduction to an existing P2P testbed. Further, the
paper zooms into the detail of some specific game and auction theoretic models
that have recently been used in P2P energy trading and discusses some important
finding of these schemes.Comment: 38 pages, single column, double spac
Autonomous Demand Side Management Based on Energy Consumption Scheduling and Instantaneous Load Billing: An Aggregative Game Approach
In this paper, we investigate a practical demand side management scenario
where the selfish consumers compete to minimize their individual energy cost
through scheduling their future energy consumption profiles. We propose an
instantaneous load billing scheme to effectively convince the consumers to
shift their peak-time consumption and to fairly charge the consumers for their
energy consumption. For the considered DSM scenario, an aggregative game is
first formulated to model the strategic behaviors of the selfish consumers. By
resorting to the variational inequality theory, we analyze the conditions for
the existence and uniqueness of the Nash equilibrium (NE) of the formulated
game. Subsequently, for the scenario where there is a central unit calculating
and sending the real-time aggregated load to all consumers, we develop a one
timescale distributed iterative proximal-point algorithm with provable
convergence to achieve the NE of the formulated game. Finally, considering the
alternative situation where the central unit does not exist, but the consumers
are connected and they would like to share their estimated information with
others, we present a distributed agreement-based algorithm, by which the
consumers can achieve the NE of the formulated game through exchanging
information with their immediate neighbors.Comment: 11 pages, 7 figure
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