Priority-Based Traffic Scheduling and Utility Optimization for Cognitive Radio Communication Infrastructure-Based Smart Grid
Smart grid can be visualized as an intelligent control system over sensors and communication platforms. Recently, wireless multimedia sensor networks (WMSNs) have shown its advantages for smart grid by providing rich surveillance information for grid failure detection and recovery, energy source monitoring, asset management, security, etc. On the other hand, cognitive radio (CR) networks have been identified as a key wireless technology to reduce the communication interferences and improve the bandwidth efficiency for smart grid communication. There is an essential need to use the CR communication platform to support large-size and time-sensitive multimedia delivery for future smart grid system. In this paper, we consider the heterogeneous characteristics of smart grid traffic including multimedia and propose a priority-based traffic scheduling approach for CR communication infrastructure based smart grid system according to the various traffic types of smart grid such as control commands, multimedia sensing data and meter readings. Specifically, we develop CR channel allocation and traffic scheduling schemes taking into consideration of channel switch and spectrum sensing errors, and solve a system utility optimization problem for smart grid communication system. Our solutions are demonstrated through both analyzes and simulations. This research opens a new vista of future smart grid communications.
Simulating a future smart city: An integrated land use-energy model
Designing a future smart city (FSC) that copes with the reduction of CO2 has become one of the urgent tasks of the next 20years. One promising approach to achieve FSC is to combine appropriate land use (compact city with energy efficient buildings and photovoltaic panels (PVs)), transportation (electric vehicles (EVs) and public transportation system) and energy systems (smart grid systems), because of the interaction between these elements. However, there are few models which simulate these elements in an integrated manner. This paper presents the concept of the integrated model, and shows the land use-energy part of the model created for the Tokyo metropolitan area, which is the largest Mega city in the world. Firstly, a spatially explicit land use model (urban economic model) is constructed for the study area, and the model is calibrated using existing statistical data. Secondly, possible future compact/dispersion city scenarios for the year 2050 are created using the model. Thirdly, intra-day dynamics (hourly) of electricity demand and supply from PVs, which is assumed to be installed to the roofs of all detached houses in the study area, under two urban scenarios is simulated. The obtained results suggest that [1] “compact” urban form may contribute to the reduction of electricity demand from the residential sector, but [2] PV-supply under the scenario may also be reduced because of the decreased share of detached houses. Hence in the compact city scenario, it is important to discuss the effective use of vacant areas in suburbs, which may be used for large PV installations, or be re-vegetated to mitigate urban heat island effects.
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