Dissertação

Clustering-driven equipment deployment planner and analyzer for wireless non-mobile networks applied to smart grid scenarios

The modern power grids, known as smart grids, rely on various advancements, one of them being the introduction of bi-directional communication. In some cases, data exchanged in the network is of critical importance. The data transmissions need to meet speci c delay limits set by the regulatory agenc...

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Autor principal: VRBSKÝ, Ladislav
Grau: Dissertação
Idioma: por
Publicado em: Universidade Federal do Pará 2018
Assuntos:
Acesso em linha: http://repositorio.ufpa.br/jspui/handle/2011/10013
Resumo:
The modern power grids, known as smart grids, rely on various advancements, one of them being the introduction of bi-directional communication. In some cases, data exchanged in the network is of critical importance. The data transmissions need to meet speci c delay limits set by the regulatory agencies in order for the smart grid to function properly. Meeting these standards allows the use of new applications of monitoring, control and system protection, resulting in a more e cient, stable and environment-friendly system. This thesis presents a methodology for analysis and planning of wireless communication networks for smart grid, which uses a clustering algorithm to determine the optimal positions of the routers and gateways of the network to be installed. After, it calculates the delay for each Intelligent Eletronic Device that is a network subscriber. This way, an analysis can be made to obtain the Quality of Service requested for a speci c network setup in a speci c scenario. The results obtained in the performed case study show that it is possible to achieve a network topology that satis es the maximum delay requirements of 100% of its subscribers, using WiMAX or a combination of Wi-Fi and WiMAX. Also, the thesis explores a restricted communication mode that can temporarily suspend the transferences of non-critical data. In most scenario con gurations, the restricted mode delivers all the data within the maximum delay. The software implementation of the proposed model is made publicly available under open-source license, so that anyone, including researchers, or private and public companies, can take advantage of it. The model presented in this thesis is customizable, allowing the use of other technologies and be used with other networks, including scenarios that are not related to smart grid.