Preprint Article Version 1 This version is not peer-reviewed

Optimal Deployment of FiWi Networks using Heuristic Method for Integration Microgrids with Smart Metering

Version 1 : Received: 2 July 2018 / Approved: 4 July 2018 / Online: 4 July 2018 (15:49:59 CEST)

A peer-reviewed article of this Preprint also exists.

Inga, E.; Campaña, M.; Hincapié, R.; Moscoso-Zea, O. Optimal Deployment of FiWi Networks Using Heuristic Method for Integration Microgrids with Smart Metering. Sensors 2018, 18, 2724. Inga, E.; Campaña, M.; Hincapié, R.; Moscoso-Zea, O. Optimal Deployment of FiWi Networks Using Heuristic Method for Integration Microgrids with Smart Metering. Sensors 2018, 18, 2724.

Journal reference: Sensors 2018, 18, 2724
DOI: 10.3390/s18082724

Abstract

The unpredictable increase in electrical demand affects the quality of theenergy throughout the network. A solution to the problem is the increase of distributedgeneration units which burn fossil fuels.While this is an immediate solution to theproblem the ecosystem gets affected by the emission of CO2.A promising solutionis the integration of Distributed Renewable Energy Sources (DRES) to the conventionalelectrical system, thus, introducing the concept of smart microgrids (SMG) that requirea safe, reliable and technically planned two-way communication system. This documentpresents a heuristic based on planning capable of providing a bidirectional communicationnear optimal route map, following the structure of an hybrid Fiber-Wireless (FiWi) with thepurpose of obtaining information of electrical parameters that help us to manage the useof energy by integrating conventional electrical system to SMG. A FiWi network is basedon the integration of wireless access and optical networks. This integration increases thecoverage and reliability at a lower cost. The optimization model is based on clusteringtechniques, through the construction of balanced conglomerates. The method is used forthe development of the clusters along with the Nearest-Neighbor Spanning Tree Algorithm(N-NST). Additionally, Optimal Delay Balancing (ODB) model will be used to minimizethe end to end delay of each grouping. In addition, the heuristic observes real designparameters such as: capacity and coverage. Using the Dijkstra algorithm, the routes arebuilt following the minimum shorter path. Therefore, this paper presents a heuristic able to plan the deployment of smart meters (SMs) through a tree-like hierarchical topology for theintegration of SMG at the lowest cost.

Subject Areas

Optimization; Smart Metering; IoT; Microgrid; Heuristic; Sensor Networks

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