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

机译:使用启发式方法将微电网与智能电表集成的FiWi网络的最佳部署

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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 CO 2 . 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.
机译:电力需求的不可预测的增长会影响整个网络的能源质量。该问题的解决方案是增加燃烧化石燃料的分布式发电机组。虽然这是解决问题的直接方法,但生态系统受到CO 2排放的影响。一种有前途的解决方案是将分布式可再生能源(DRES)与常规电气系统集成在一起,从而引入了智能微电网(SMG)的概念。这些SMG需要安全,可靠且经过技术规划的双向通信系统。本文提出了一种基于计划的启发式方法,该方法能够提供接近最佳的双向通信。该模型遵循混合光纤(FiWi)网络的结构,其目的是获得电参数信息,以帮助我们通过将常规电气系统与SMG集成在一起来管理能源的使用。优化模型基于聚类技术,通过构建平衡的企业集团来构建。该方法与最近邻居生成树算法(N-NST)一起用于群集的开发。此外,将使用最佳延迟平衡(ODB)模型来最小化每个分组的端到端延迟。另外,启发式观察实际的设计参数,例如:容量和覆盖范围。使用Dijkstra算法,将按照最短路径构建路线。因此,本文提出了一种启发式方法,该方法能够通过树状分层拓扑计划智能电表(SM)的部署,从而以最低的成本集成SMG。

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