Optimal Deployment of FiWi Networks Using Heuristic Method for Integration Microgrids with Smart Metering
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...
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MDPI AG
2018-08-01
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Online Access: | http://www.mdpi.com/1424-8220/18/8/2724 |
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author | Esteban Inga Miguel Campaña Roberto Hincapié Oswaldo Moscoso-Zea |
author_facet | Esteban Inga Miguel Campaña Roberto Hincapié Oswaldo Moscoso-Zea |
author_sort | Esteban Inga |
collection | DOAJ |
description | 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. |
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issn | 1424-8220 |
language | English |
last_indexed | 2024-04-11T14:05:32Z |
publishDate | 2018-08-01 |
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spelling | doaj.art-168bfdfcc51e4b828f9dd23c3038abbc2022-12-22T04:19:53ZengMDPI AGSensors1424-82202018-08-01188272410.3390/s18082724s18082724Optimal Deployment of FiWi Networks Using Heuristic Method for Integration Microgrids with Smart MeteringEsteban Inga0Miguel Campaña1Roberto Hincapié2Oswaldo Moscoso-Zea3Electrical Engineering, Universidad Politécnica Salesiana, Quito EC170146, EcuadorElectrical Engineering, Universidad Politécnica Salesiana, Quito EC170146, EcuadorDepartment of Telecommunications, Universidad Pontificia Bolivariana, Medellín 050031, ColombiaFaculty of Engineering, Universidad Tecnológica Equinoccial, Quito EC170147, EcuadorThe 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.http://www.mdpi.com/1424-8220/18/8/2724optimizationsmart meteringIoTmicrogridheuristicsensor networks |
spellingShingle | Esteban Inga Miguel Campaña Roberto Hincapié Oswaldo Moscoso-Zea Optimal Deployment of FiWi Networks Using Heuristic Method for Integration Microgrids with Smart Metering Sensors optimization smart metering IoT microgrid heuristic sensor networks |
title | Optimal Deployment of FiWi Networks Using Heuristic Method for Integration Microgrids with Smart Metering |
title_full | Optimal Deployment of FiWi Networks Using Heuristic Method for Integration Microgrids with Smart Metering |
title_fullStr | Optimal Deployment of FiWi Networks Using Heuristic Method for Integration Microgrids with Smart Metering |
title_full_unstemmed | Optimal Deployment of FiWi Networks Using Heuristic Method for Integration Microgrids with Smart Metering |
title_short | Optimal Deployment of FiWi Networks Using Heuristic Method for Integration Microgrids with Smart Metering |
title_sort | optimal deployment of fiwi networks using heuristic method for integration microgrids with smart metering |
topic | optimization smart metering IoT microgrid heuristic sensor networks |
url | http://www.mdpi.com/1424-8220/18/8/2724 |
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