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In this paper a new mathematical optimization model is proposed to optimize the number of data aggregators in smart grids and assign each smart meter to at least one data aggregator. The model is based on a Set-Covering Problem, which aims to find the minimum number of sets that cover all elements. In the case of smart grids, these elements will be the smart meters. We used a branch–bound algorithm for the new optimization model to solve several instances considering different smart grid scenarios. In the scenarios, real-world parameters were used for a lot of smart meters (which ranged from 15 to 900, with output powers of 23 and 30 dBm used in the theoretical analysis), data aggregator costs, dispersions, maximum budget, and signal propagation losses. The tests reached the best values for the objective function with small, medium and large-scale instances in low computational times. Theoretical analysis was used to evaluate the signal received from data aggregators, indicating that they can receive information with a high-quality signal.The proposed model provides insights for stakeholders involved and can aid in smart grid implementation. In addition, it can offer a blueprint for engineers to optimize data flow within hierarchical grid structures with smart meters and data aggregators.
Aranda et al. (Fri,) studied this question.