Planning Hybrid Networks for Multi-Microgrids with LoRaWAN

This study addresses the optimization challenge of Smart Grid (SG) and Microgrid (MG) networks, aiming to reduce the number of Data Aggregation Points (DAPs) and Concentrators (CONs) required to ensure an efficient and sustainable grid. Within this context, an optimization model is proposed that aims to balance network quality with cost reduction, while ensuring superior performance compared to conventional SG networks. The proposed approach involves implementing a decentralized architecture, with an emphasis on integrating residential DAPs, enabling a granular analysis of energy consumption and generation data, and facilitating the implementation of advanced energy control and optimization strategies at the local level. The main contributions include the development of a hybrid network model, a network planning model for positioning CONs and DAPs, an optimization model for minimizing DAPs and CONs and the proposal of a large-scale network planning model. As main results, we highlight a significant reduction in DAPs, with a decrease of up to 5 units, and a reduction in CONs, with a decrease of up to 2 units. These numbers demonstrate the effectiveness of the proposed model in achieving a more efficient and adaptable electrical infrastructure, representing a significant step towards a smart and sustainable energy network.