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

Esteban Inga; Miguel Campaña; Roberto Hincapié; Oswaldo Moscoso-Zea

doi:10.3390/s18082724

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

Journal

Sensors

ISSN

1424-8220

Date Issued

2018-08-19

Author(s)

Esteban Inga

Miguel Campaña

Roberto Hincapié

Oswaldo Moscoso-Zea

Facultad de Ciencias de la Ingeniería e Industrias

DOI

10.3390/s18082724

URL

https://cris.ute.edu.ec/handle/123456789/920

Abstract

The unpredictable increase in electrical demand affects the quality of the energy throughout the network. A solution to the problem is the increase of distributed generation units, which burn fossil fuels. While this is an immediate solution to the problem, the ecosystem is affected by the emission of CO2. A promising solution is the integration of Distributed Renewable Energy Sources (DRES) with the conventional electrical system, thus introducing the concept of Smart Microgrids (SMG). These SMGs require a safe, reliable and technically planned two-way communication system. This paper presents a heuristic based on planning capable of providing a bidirectional communication that is near optimal. The model follows the structure of a hybrid Fiber-Wireless (FiWi) network with the purpose of obtaining information of electrical parameters that help us to manage the use of energy by integrating conventional electrical system with SMG. The optimization model is based on clustering techniques, through the construction of balanced conglomerates. The method is used for the development of the clusters along with the Nearest-Neighbor Spanning Tree algorithm (N-NST). Additionally, the Optimal Delay Balancing (ODB) model will be used to minimize the end to end delay of each grouping. In addition, the heuristic observes real design parameters such as: capacity and coverage. Using the Dijkstra algorithm, the routes are built following the shortest path. Therefore, this paper presents a heuristic able to plan the deployment of Smart Meters (SMs) through a tree-like hierarchical topology for the integration of SMG at the lowest cost.