Performance Evaluation of Communication Technologies and Network Structure for Smart Grid Applications

The design of an effective and reliable communication network supporting smart grid applications requires the selection of appropriate communication technologies and protocols. The objective of this study is to study and quantify the capabilities of an advanced metring infrastructure (AMI) to support the simultaneous operation of major smart grid functions. These include smart metring, price-induced controls, distribution automation, demand response, and electric vehicle charging/discharging applications in terms of throughput and latency. OPNET is used to simulate the performance of selected communication technologies and protocols. Research findings indicate that smart grid applications can operate simultaneously by piggybacking on an existing AMI infrastructure and still achieve their latency requirements

WiMAX for Smart Grid Applications and the Influence of Impulsive Noise

In order to adapt the power grid to today’s level of electricity consumption, growing investments are made in a smart power grid. The employment of this novel architecture brings advantages such as efficiency of energy production and consumption, availability and reliability of the service, scalability, self-healing grid, environment friendly, consumer participation in electricity production with harvested energy through solar panels and wind turbines. The rising power demand curve can be restrained by a smart implementation of the new electrical power grid. The smart grid brings out an additional layer that will interconnect and manage all the generation, transmission and distribution sectors of the power grid. Many other features will be brought by the smart grid that will improve its reliability and efficiency and will lead towards renewable and sustainable energy development. In this thesis, we analyze the performances of a smart grid in which the communication layer is implemented using Worldwide Interoperability for Microwave Access (WiMAX) communication technology. Parameters such as throughput, network capacity, packet loss, latency are studied by analyzing the traffic model generated by using several applications in the Distribution Area Network (DAN) of the Smart Grid. The applications whose traffic was simulated using OPNET are the following four: metering and pricing, electrical car, video surveillance and voice support for workforce. The capacity of a base station in the distribution area network is obtained for each smart grid application individually as well as for the combined traffic of all applications. Furthermore, this thesis also discusses the effects of the impulsive noise over the communication layer. An Orthogonal Frequency Division Multiplexing (OFDM) structure using WiMAX physical layer characteristics was simulated with and without the influence of impulsive noise using MATLAB. The results highlighted the effects of the impulsive noise over performances such as bit error rate, packet error rate, throughput and the overall capacity of the network. For a better understanding, the outcomes are presented with and without the presence of impulsive noise

Density-Aware Smart Grid Node Allocation in Heterogeneous Radio Access Technology Environments

Smart grid (SG) is an intelligent enhancement of the conventional energy grid allowing a smarter management. In order to be implemented, SG needs to rely on a communication network connecting different node types, implementing the SG services, with different communication and energy requirements. Heterogeneous network (Het-Net) solutions are very attractive, gaining from the allocation of different radio access technologies (RATs) to the different SG node types; however, due to the heterogeneity of the system, an efficient radio resource optimization and energy management are a complex task. Through the exploitation of the most significant key performance indicators (KPIs) of the SG node types and the key features of the RATs, a joint communication and energy cost function are here defined. Through this approach it is possible to optimally assign the nodes to the RATs while respecting their requirements. In particular, we show the effect of different nodes’ density scenarios on the proposed allocation algorithm