Smart grid

About: Smart grid is a research topic. Over the lifetime, 37536 publications have been published within this topic receiving 627844 citations. The topic is also known as: intelligent grid.

Electrical energy storage systems in electricity generation: Energy policies, innovative technologies, and regulatory regimes

Abstract: Electricity plays a dominant role to the citizens׳ well-being and the social prosperity of the developed economies. Electricity perspectives have attracted the research interest of the scientific community during the last two decades due to its determining impact upon transportation modes (electric-based mobility: electric vehicles–EVs, hybrid cars, and electric drive-trains), energy-consumed household tasks (Smart House and Smart Grid concepts), working environment, and leisure activities. Electricity generation is mainly determined by the following features: on-grid (mainland) and off-grid (including exploitation of renewables in remote areas) production, peak (during the day) and off-peak (during the night) daytimes of energy production and consumption, efficient and reliable power supply, capability and reliability of energy storage technologies, energy market potential in the future. This study further explores the following issues: which technologies will be most needed, in which technologies there is room for further development, which policy considerations will influence rollout and penetration, and what implementation problems may be expected. Finally, this study addresses a wide spectrum of energy policies regarding the electrochemical, mechanical, and thermal energy storage technologies. In parallel, the study discussed global regulatory regimes of the post-2015 development agenda of Rio20+ United Nations Conference on Sustainable Development that should be adapted to electricity generation under the political initiatives of “Sustainable Development Goals” (SDGs) and “Millennium Development Goals” (MDGs). Finally, the key-issues of research, operation, applicability, and pricing trend of energy storage technologies are addressed while the future orientations of these technologies are outlined.

Machine Learning for the New York City Power Grid

Abstract: Power companies can benefit from the use of knowledge discovery methods and statistical machine learning for preventive maintenance. We introduce a general process for transforming historical electrical grid data into models that aim to predict the risk of failures for components and systems. These models can be used directly by power companies to assist with prioritization of maintenance and repair work. Specialized versions of this process are used to produce (1) feeder failure rankings, (2) cable, joint, terminator, and transformer rankings, (3) feeder Mean Time Between Failure (MTBF) estimates, and (4) manhole events vulnerability rankings. The process in its most general form can handle diverse, noisy, sources that are historical (static), semi-real-time, or real-time, incorporates state-of-the-art machine learning algorithms for prioritization (supervised ranking or MTBF), and includes an evaluation of results via cross-validation and blind test. Above and beyond the ranked lists and MTBF estimates are business management interfaces that allow the prediction capability to be integrated directly into corporate planning and decision support; such interfaces rely on several important properties of our general modeling approach: that machine learning features are meaningful to domain experts, that the processing of data is transparent, and that prediction results are accurate enough to support sound decision making. We discuss the challenges in working with historical electrical grid data that were not designed for predictive purposes. The “rawness” of these data contrasts with the accuracy of the statistical models that can be obtained from the process; these models are sufficiently accurate to assist in maintaining New York City's electrical grid.

Evolution of Communication Technologies for Smart Grid applications

Abstract: The idea of Smart Grid has started to evolve more rapidly with the enhancement in Communication Technologies. Two way communication is a key aspect in realizing Smart Grids and is easily possible with the help of modern day advancements in both wired and wireless communication technologies. This paper discusses some of the major communication technologies which include IEEE specified ZigBee, WiMAX and Wireless LAN (Wi-Fi) technologies, GSM 3G/4G Cellular, DASH 7 and PLC (Power Line Communications), with special focus on their applications in Smart Grids. The Smart Grid environments and domains such as Home Area Automation, Substation Automation, Automated Metering Infrastructure, Vehicle-to-Grid Communications, etc. are considered as priority areas for developing smarter grids. The advancements, challenges and the opportunities present in these priority areas are discussed in this paper.

Three-Party Energy Management With Distributed Energy Resources in Smart Grid

Abstract: In this paper, the benefits of distributed energy resources (DERs) are considered in an energy management scheme for a smart community consisting of a large number of residential units (RUs) and a shared facility controller (SFC). A non-cooperative Stackelberg game between RUs and the SFC is proposed in order to explore how both entities can benefit, in terms of achieved utility and minimizing total cost respectively, from their energy trading with each other and the grid. From the properties of the game, it is shown that the maximum benefit to the SFC in terms of reduction in total cost is obtained at the unique and strategy proof Stackelberg equilibrium (SE). It is further shown that the SE is guaranteed to be reached by the SFC and RUs by executing the proposed algorithm in a distributed fashion, where participating RUs comply with their best strategies in response to the action chosen by the SFC. In addition, a charging-discharging scheme is introduced for the SFC's storage device (SD) that can further lower the SFC's total cost if the proposed game is implemented. Numerical experiments confirm the effectiveness of the proposed scheme.

A Multilevel State Estimation Paradigm for Smart Grids

Abstract: The main objective of this paper is to describe a multilevel framework that facilitates seamless integration of existing state estimators (SEs) that are designed to function at different levels of modeling hierarchy in order to accomplish very large-scale monitoring of interconnected power systems. This has been a major challenge for decades as power systems grew pretty much independently in different areas, which had to operate in an interconnected and synchronized fashion. The paper initially provides a brief historical perspective which also explains the existing state estimation paradigm. This is followed by a review of the recent technological and regulatory drivers that are responsible for the new developments in the energy management functions. The paper then shows that a common theoretical framework can be used to implement a hierarchical scheme by which even very large-scale power systems can be efficiently and accurately monitored. This is illustrated for substation level, transmission system level as well as for a level between different transmission system operators in a given power system. Finally, the paper describes the use and benefits of phasor measurements when incorporated at these different levels of the proposed infrastructure. Numerical examples are included to illustrate performance of the proposed multilevel schemes.