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

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.