Table of Contents
ISRN Power Engineering
Volume 2014, Article ID 894628, 22 pages
Research Article

Wireless Sensor Network Design for Transmission Line Monitoring, Metering, and Controlling: Introducing Broadband over Power Lines-Enhanced Network Model (BPLeNM)

School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), 9 Iroon Polytechniou Street, Zografou, 15780 Athens, Greece

Received 11 February 2014; Accepted 2 April 2014; Published 4 June 2014

Academic Editors: A. R. Beig and J. J. González de la Rosa

Copyright © 2014 Athanasios G. Lazaropoulos. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper introduces the broadband over power lines-enhanced network model (BPLeNM) that is suitable for efficiently delivering the generated data of wireless sensor networks (WSNs) of overhead high-voltage (HV) power grids to the substations. BPLeNM exploits the high data rates of the already installed BPL networks across overhead HV grids. BPLeNM is compared against other two well-verified network models from the relevant literature: the linear network model (LNM) and the optimal arrangement network model (OANM). The contribution of this paper is threefold. First, the general mathematical framework that is necessary for describing WSNs of overhead HV grids is first presented. In detail, the general mathematical formulation of BPLeNM is proposed while the existing formulations of LNM and OANM are extended so as to deal with the general case of overhead HV grids. Based on these general mathematical formulations, the general expression of maximum delay time of the WSN data is determined for the three network models. Second, the three network models are studied and assessed for a plethora of case scenarios. Through these case scenarios, the impact of different lengths of overhead HV grids, different network arrangements, new communications technologies, variation of WSN density across overhead HV grids, and changes of generated WSN data rate on the maximum delay time is thoroughly examined. Third, to assess the performance and the feasibility of the previous network models, the feasibility probability (FP) is proposed. FP is a macroscopic metric that estimates how much practical and economically feasible is the selection of one of the previous three network models. The main conclusion of this paper is that BPLeNM defines a powerful, convenient, and schedulable network model for today’s and future’s overhead HV grids in the smart grid (SG) landscape.