264,763 research outputs found
A survey on modeling of microgrids - from fundamental physics to phasors and voltage sources
Microgrids have been identified as key components of modern electrical
systems to facilitate the integration of renewable distributed generation
units. Their analysis and controller design requires the development of
advanced (typically model-based) techniques naturally posing an interesting
challenge to the control community. Although there are widely accepted reduced
order models to describe the dynamic behavior of microgrids, they are typically
presented without details about the reduction procedure---hampering the
understanding of the physical phenomena behind them. Preceded by an
introduction to basic notions and definitions in power systems, the present
survey reviews key characteristics and main components of a microgrid. We
introduce the reader to the basic functionality of DC/AC inverters, as well as
to standard operating modes and control schemes of inverter-interfaced power
sources in microgrid applications. Based on this exposition and starting from
fundamental physics, we present detailed dynamical models of the main microgrid
components. Furthermore, we clearly state the underlying assumptions which lead
to the standard reduced model with inverters represented by controllable
voltage sources, as well as static network and load representations, hence,
providing a complete modular model derivation of a three-phase inverter-based
microgrid
Optimized Solar Photovoltaic Generation in a Real Local Distribution Network
Remarkable penetration of renewable energy in electric networks, despite its
valuable opportunities, such as power loss reduction and loadability
improvements, has raised concerns for system operators. Such huge penetration
can lead to a violation of the grid requirements, such as voltage and current
limits and reverse power flow. Optimal placement and sizing of Distributed
Generation (DG) are one of the best ways to strengthen the efficiency of the
power systems. This paper builds a simulation model for the local distribution
network based on obtained load profiles, GIS information, solar insolation,
feeder and voltage settings, and define the optimization problem of solar PVDG
installation to determine the optimal siting and sizing for different
penetration levels with different objective functions. The objective functions
include voltage profile improvement and energy loss minimization and the
considered constraints include the physical distribution network constraints
(AC power flow), the PV capacity constraint, and the voltage and reverse power
flow constraints.Comment: To be published (Accepted) in: Proceedings of the IEEE PES Innovative
Smart Grid Technologies Conference (ISGT), Washington D.C., USA, 201
A Survey of Green Networking Research
Reduction of unnecessary energy consumption is becoming a major concern in
wired networking, because of the potential economical benefits and of its
expected environmental impact. These issues, usually referred to as "green
networking", relate to embedding energy-awareness in the design, in the devices
and in the protocols of networks. In this work, we first formulate a more
precise definition of the "green" attribute. We furthermore identify a few
paradigms that are the key enablers of energy-aware networking research. We
then overview the current state of the art and provide a taxonomy of the
relevant work, with a special focus on wired networking. At a high level, we
identify four branches of green networking research that stem from different
observations on the root causes of energy waste, namely (i) Adaptive Link Rate,
(ii) Interface proxying, (iii) Energy-aware infrastructures and (iv)
Energy-aware applications. In this work, we do not only explore specific
proposals pertaining to each of the above branches, but also offer a
perspective for research.Comment: Index Terms: Green Networking; Wired Networks; Adaptive Link Rate;
Interface Proxying; Energy-aware Infrastructures; Energy-aware Applications.
18 pages, 6 figures, 2 table
A survey of machine learning techniques applied to self organizing cellular networks
In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future
The impact of domestic plug-in hybrid electric vehicles on power distribution system loads
The market for Plug-in Hybrid Electric Vehicle (PHEVs) is expected to grow significantly over the next few years and a number of new products are soon to come onto the market, such as the Toyota Prius plug-in version, . The charging demand of wide-scale use of PHEVs may have a significant impact on domestic electricity loads and could risk of overloading the power system if appropriate charging strategies not applied to prevent this. A Monte Carlo Simulation (MCS) model of domestic PHEV use and availability has been developed based on probabilistic characterisations obtained from UKTUS and quantifies charging demand of PHEVs as a function of time of day. The MCS model has been developed in order to simulate the impact on the electricity distribution system. This article also discusses the potential for responsive battery charging load from PHEVs
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