Post date: Nov 23, 2013 10:26:49 AM
A copy of the CFP of the journal is provided in the following:
SPECIAL ISSUE ON “NEURAL NETWROKS AND LEARNING SYSTEMS APPLICATIONS IN SMART GRID”
The electric power grid is spatially and temporally complex, non-convex, nonlinear and non-stationary system with uncertainties at many levels. The integration of renewable sources of energy such as wind and solar farms, energy storage and plug-in hybrid electric vehicles further adds complexity and challenges to efficient, reliable and safe operation of electric power grids. Smart grid is aimed at improving power system’s reliability, security, sustainability, efficiency and flexibility through distributed and coordinated intelligence at all levels of the electric power grid – generation, transmission and distribution. The smart grid will experience variable and uncertain generation (such as wind and solar), stochastic load profiles and power flows, cyber-attacks (unintentional and malicious), communication latencies and data loss, etc. All these are challenging issues faced to achieve smooth operation of smart grids. Various types of neural networks including multilayer perceptron (MLP), recurrent neural network (RNN), echo-state network (ESN), Hopfield neural network (HNN), cellular neural network (CNN), self-organizing map (SOM), learning vector quantization (LVQ) and support vector machine (SVM) have been developed for smart grid applications. These applications include intelligent sensing, monitoring and classification of power system dynamics, load forecasting, renewable energy forecasting, and power system security assessment, control and protection.
The objective of this special issue is to bring together the most recent advances in the field of neural networks and learning systems and their applications for smart grids. We invite original and unpublished research contributions to all relevant areas of smart grid. Topics of interest include, but are not limited to:
• New neural network architectures
• New learning system architectures
• Learning algorithms and frameworks for real-time smart grid applications
• Scalable distributed neural network and learning systems
• Big data analytics
• Business intelligence
• Cyber-security
• Demand response and demand side management
• Distributed generation
• Dynamic optimal power flow control
• Energy management systems
• Intelligent sensing and sense-making
• Intelligent decision-making (neuro-fuzzy, etc.)
• Intelligent control (nonlinear, adaptive, optimal, robust, etc.)
• Load forecasting and forecasting of intermittent renewable generation
• Large power system/Bulk power system monitoring and control
• Micro-grids and Nano-grids
• Plug-in electric vehicles and Vehicle-to-Grid (V2G) systems
• Power system communications
• Power system computations
• Power system markets and economics
• Power quality monitoring, identification and classification
• Power system scheduling/dispatch
• Power system security assessment
• Power system control
• Power system protection including intelligent/adaptive relays, intelligent auto-reclosers and intelligent fault locating
• Real-time power system control center applications and visualizations
• Situational awareness and intelligence
• Synchrophasor based applications
• Wide area systems
IMPORTANT DATES
January 15, 2014 – Deadline for manuscript submission
May 31, 2014 – Notification to authors
June 30, 2014 – Deadline for submission of revised manuscripts
July 31, 2014 – Final decision
October/November 2014 – Special issue publication in the IEEE TNNLS
SUBMISSION INSTRUCTIONS
1. Read the information for authors at http://cis.ieee.org/publications.html
2. Submit the manuscript by January 31, 2014 at the IEEE-TNNLS webpage http://mc.manuscriptcentral.com/tnnlsand follow the submission procedure. Please indicate clearly on the first page of the manuscript and the Author’s Cover Letter that the manuscript has been submitted to the Special Issue on Neural Networks and Learning Systems Applications in Smart Grid. Please forward to the guest editors the notification emailed to you by manuscript central on your submission.
GUEST EDITORS
Dipti Srinivasan
National University of Singapore, Singapore
Ganesh Kumar Venayagamoorthy
Clemson University, Clemson, SC, USA