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

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This study introduces a novel heuristic for planning Smart Microgrids (SMG) communication networks. It optimizes the deployment of Smart Meters (SMs) for efficient integration of Distributed Renewable Energy Sources (DRES) at minimal cost.

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Area of Science:

  • Electrical Engineering
  • Computer Science
  • Network Optimization

Background:

  • Rising electrical demand impacts grid stability.
  • Fossil fuel-based distributed generation increases CO₂ emissions.
  • Smart Microgrids (SMG) offer a sustainable solution by integrating Distributed Renewable Energy Sources (DRES).

Purpose of the Study:

  • To present a planning heuristic for a reliable, bidirectional communication system for SMGs.
  • To optimize the deployment of Smart Meters (SMs) within a hybrid Fiber-Wireless (FiWi) network.
  • To achieve cost-effective integration of SMGs with conventional electrical systems.

Main Methods:

  • A heuristic planning approach based on clustering techniques and the Nearest-Neighbor Spanning Tree (N-NST) algorithm.
  • Optimization using the Optimal Delay Balancing (ODB) model to minimize end-to-end delay.
  • Route construction via Dijkstra's algorithm, considering capacity and coverage for a tree-like hierarchical topology.

Main Results:

  • Development of a near-optimal bidirectional communication plan for SMGs.
  • Efficient clustering of network elements using N-NST and ODB.
  • Cost-effective deployment strategy for Smart Meters (SMs) enabling SMG integration.

Conclusions:

  • The proposed heuristic effectively plans Smart Meter (SM) deployment for Smart Microgrid (SMG) integration.
  • The hybrid FiWi network model facilitates essential electrical parameter monitoring.
  • This approach enables efficient energy management and integration of DRES at reduced costs.