934 research outputs found
A Stochastic Geometry-based Demand Response Management Framework for Cellular Networks Powered by Smart Grid
In this paper, the production decisions across multiple energy suppliers in
smart grid, powering cellular networks are investigated. The suppliers are
characterized by different offered prices and pollutant emissions levels. The
challenge is to decide the amount of energy provided by each supplier to each
of the operators such that their profitability is maximized while respecting
the maximum tolerated level of CO2 emissions. The cellular operators are
characterized by their offered quality of service (QoS) to the subscribers and
the number of users that determines their energy requirements. Stochastic
geometry is used to determine the average power needed to achieve the target
probability of coverage for each operator. The total average power requirements
of all networks are fed to an optimization framework to find the optimal amount
of energy to be provided from each supplier to the operators. The generalized
-fair utility function is used to avoid production bias among the
suppliers based on profitability of generation. Results illustrate the
production behavior of the energy suppliers versus QoS level, cost of energy,
capacity of generation, and level of fairness.Comment: 6 pages, 4 figure
State Estimation for the Individual and the Population in Mean Field Control with Application to Demand Dispatch
This paper concerns state estimation problems in a mean field control
setting. In a finite population model, the goal is to estimate the joint
distribution of the population state and the state of a typical individual. The
observation equations are a noisy measurement of the population.
The general results are applied to demand dispatch for regulation of the
power grid, based on randomized local control algorithms. In prior work by the
authors it has been shown that local control can be carefully designed so that
the aggregate of loads behaves as a controllable resource with accuracy
matching or exceeding traditional sources of frequency regulation. The
operational cost is nearly zero in many cases.
The information exchange between grid and load is minimal, but it is assumed
in the overall control architecture that the aggregate power consumption of
loads is available to the grid operator. It is shown that the Kalman filter can
be constructed to reduce these communication requirements,Comment: To appear, IEEE Trans. Auto. Control. Preliminary version appeared in
the 54rd IEEE Conference on Decision and Control, 201
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Middleware architectures for the smart grid: A survey on the state-of-the-art, taxonomy and main open issues
The integration of small-scale renewable energy sources in the smart grid depends on several challenges that must be overcome. One of them is the presence of devices with very different characteristics present in the grid or how they can interact among them in terms of interoperability and data sharing. While this issue is usually solved by implementing a middleware layer among the available pieces of equipment in order to hide any hardware heterogeneity and offer the application layer a collection of homogenous resources to access lower levels, the variety and differences among them make the definition of what is needed in each particular case challenging. This paper offers a description of the most prominent middleware architectures for the smart grid and assesses the functionalities they have, considering the performance and features expected from them in the context of this application domain
Models and Methods for Network Selection and Balancing in Heterogeneous Scenarios
The outbreak of 5G technologies for wireless communications can be considered a response to the need for widespread coverage, in terms of connectivity and bandwidth, to guarantee broadband services, such as streaming or on-demand programs offered by the main television networks or new generation services based on augmented and virtual reality (AR / VR).
The purpose of the study conducted for this thesis aims to solve two of the main problems that will occur with the outbreak of 5G, that is, the search for the best possible connectivity, in order to offer users the resources necessary to take advantage of the new generation services, and multicast as required by the eMBMS.
The aim of the thesis is the search for innovative algorithms that will allow to obtain the best connectivity to offer users the resources necessary to use the 5G services in a heterogeneous scenario. Study UF that allows you to improve the search for the best candidate network and to achieve a balance that allows you to avoid congestion of the chosen networks. To achieve these two important focuses, I conducted a study on the main mathematical methods that made it possible to select the network based on QoS parameters based on the type of traffic made by users. A further goal was to improve the computational computation performance they present.
Furthermore, I carried out a study in order to obtain an innovative algorithm that would allow the management of multicast. The algorithm that has been implemented responds to the needs present in the eMBMS, in realistic scenarios
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