6,125 research outputs found
Smart Microgrids: Overview and Outlook
The idea of changing our energy system from a hierarchical design into a set
of nearly independent microgrids becomes feasible with the availability of
small renewable energy generators. The smart microgrid concept comes with
several challenges in research and engineering targeting load balancing,
pricing, consumer integration and home automation. In this paper we first
provide an overview on these challenges and present approaches that target the
problems identified. While there exist promising algorithms for the particular
field, we see a missing integration which specifically targets smart
microgrids. Therefore, we propose an architecture that integrates the presented
approaches and defines interfaces between the identified components such as
generators, storage, smart and \dq{dumb} devices.Comment: presented at the GI Informatik 2012, Braunschweig Germany, Smart Grid
Worksho
Charging Games in Networks of Electrical Vehicles
In this paper, a static non-cooperative game formulation of the problem of
distributed charging in electrical vehicle (EV) networks is proposed. This
formulation allows one to model the interaction between several EV which are
connected to a common residential distribution transformer. Each EV aims at
choosing the time at which it starts charging its battery in order to minimize
an individual cost which is mainly related to the total power delivered by the
transformer, the location of the time interval over which the charging
operation is performed, and the charging duration needed for the considered EV
to have its battery fully recharged. As individual cost functions are assumed
to be memoryless, it is possible to show that the game of interest is always an
ordinal potential game. More precisely, both an atomic and nonatomic versions
of the charging game are considered. In both cases, equilibrium analysis is
conducted. In particular, important issues such as equilibrium uniqueness and
efficiency are tackled. Interestingly, both analytical and numerical results
show that the efficiency loss due to decentralization (e.g., when cost
functions such as distribution network Joule losses or life of residential
distribution transformers when no thermal inertia is assumed) induced by
charging is small and the corresponding "efficiency", a notion close to the
Price of Anarchy, tends to one when the number of EV increases.Comment: 8 pages, 4 figures, keywords: Charging games - electrical vehicle -
distribution networks - potential games - Nash equilibrium - price of anarch
Energy-Efficient Resource Allocation in Wireless Networks: An Overview of Game-Theoretic Approaches
An overview of game-theoretic approaches to energy-efficient resource
allocation in wireless networks is presented. Focusing on multiple-access
networks, it is demonstrated that game theory can be used as an effective tool
to study resource allocation in wireless networks with quality-of-service (QoS)
constraints. A family of non-cooperative (distributed) games is presented in
which each user seeks to choose a strategy that maximizes its own utility while
satisfying its QoS requirements. The utility function considered here measures
the number of reliable bits that are transmitted per joule of energy consumed
and, hence, is particulary suitable for energy-constrained networks. The
actions available to each user in trying to maximize its own utility are at
least the choice of the transmit power and, depending on the situation, the
user may also be able to choose its transmission rate, modulation, packet size,
multiuser receiver, multi-antenna processing algorithm, or carrier allocation
strategy. The best-response strategy and Nash equilibrium for each game is
presented. Using this game-theoretic framework, the effects of power control,
rate control, modulation, temporal and spatial signal processing, carrier
allocation strategy and delay QoS constraints on energy efficiency and network
capacity are quantified.Comment: To appear in the IEEE Signal Processing Magazine: Special Issue on
Resource-Constrained Signal Processing, Communications and Networking, May
200
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