1,299 research outputs found
GIET and MIET
No full textData for Figures 3,4,5 and 6. All data files are standard .mat files . These files can be opened in MATLAB
An improved genetic algorithm and graph theory based method for optimal sectionalizer switch placement in distribution networks with DG
No full textIn this paper a new graph-theory and improved genetic algorithm based practical method is employed to solve the optimal sectionalizer switch placement problem. The proposed method determines the best locations of sectionalizer switching devices in distribution networks considering the effects of presence of distributed generation (DG) in fitness functions and other optimization constraints, providing the maximum number of costumers to be supplied by distributed generation sources in islanded distribution systems after possible faults. The proposed method is simulated and tested on several distribution test systems in both cases of with DG and non DG situations. The results of the simulations validate the proposed method for switch placement of the distribution network in the presence of distributed generation
Graphene-Induced Energy Transfer for Quantitative Membrane Biophysics at Sub-Nanometer Resolution
Get PDFGraphene-induced energy transfer (GIET) is a recently developed
fluorescence-spectroscopic technique that achieves sub-nanometric optical
localization of fluorophores along the optical axis of a microscope. GIET is
based on the near-field energy transfer from an optically excited fluorescent
molecule to a single sheet of graphene. It has been successfully used for
estimating inter-leaflet distances of single lipid bilayers, and for
investigating the membrane organization of living mitochondria. In this study,
we use GIET to measure the cholesterol-induced subtle changes of membrane
thickness at the nanoscale. We quantify membrane thickness variations in
supported lipid bilayers (SLBs) as a function of lipid composition and
increasing cholesterol content. Our findings demonstrate that GIET is an
extremely sensitive tool for investigating nanometric structural changes in
bio-membranes.Comment: 6 pages, 4 figure
Plug In Electric Vehicles in Smart Grids: Energy Management
No full textThis book highlights the cutting-edge research on energy management within smart grids with significant deployment of Plug-in Electric Vehicles (PEV). These vehicles not only can be a significant electrical power consumer during Grid to Vehicle (G2V) charging mode, they can also be smartly utilized as a controlled source of electrical power when they are used in Vehicle to Grid (V2G) operating mode. Electricity Price, Time of Use Tariffs, Quality of Service, Social Welfare as well as electrical parameters of the network are all different criteria considered by the researchers when developing energy management techniques for PEVs. Risk averse stochastic energy hub management, maximizing profits in ancillary service markets, power market bidding strategies for fleets of PEVs, energy management of PEVs in the presence of renewable energy in distribution lines or microgrids and loss minimization in distribution networks based on smart coordination approaches using real time energy prices are some of the attractive and novel topics explored in this book. It will be an excellent reference for graduate students, researchers and industry professionals who are interested in getting a snapshot view of today’s latest research on applying various smart energy management strategies for smart grids with high penetration of PEVs
Plug In Electric Vehicles in Smart Grids: Charging Strategies
No full textThis book covers the recent research advancements in the area of charging strategies that can be employed to accommodate the anticipated high deployment of Plug-in Electric Vehicles (PEVs) in smart grids. Recent literature has focused on various potential issues of uncoordinated charging of PEVs and methods of overcoming such challenges. After an introduction to charging coordination paradigms of PEVs, this book will present various ways the coordinated control can be accomplished. These innovative approaches include hierarchical coordinated control, model predictive control, optimal control strategies to minimize load variance, smart PEV load management based on load forecasting, integrating renewable energy sources such as photovoltaic arrays to supplement grid power, using wireless communication networks to coordinate the charging load of a smart grid and using market price of electricity and customers payment to coordinate the charging load. Hence, this book proposes many new strategies proposed recently by the researchers around the world to address the issues related to coordination of charging load of PEVs in a future smart grid
Plug In Electric Vehicles in Smart Grids: Integration Techniques
No full textThis book focuses on the state of the art in worldwide research on applying optimization approaches to intelligently control charging and discharging of batteries of Plug-in Electric Vehicles (PEVs) in smart grids. Network constraints, cost considerations, the number and penetration level of PEVs, utilization of PEVs by their owners, ancillary services, load forecasting, risk analysis, etc. are all different criteria considered by the researchers in developing mathematical based equations which represent the presence of PEVs in electric networks. Different objective functions can be defined and different optimization methods can be utilized to coordinate the performance of PEVs in smart grids. This book will be an excellent resource for anyone interested in grasping the current state of applying different optimization techniques and approaches that can manage the presence of PEVs in smart grids
Graphene- and metal-induced energy transfer for single-molecule imaging and live-cell nanoscopy with (sub)-nanometer axial resolution
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