Optimizing data aggregation point location with grid-based model for smart grids

Abstract

With the construction of smart grids, smart meters are gradually being installed in every house. In order to transfer the user data collected by smart meters to the control center, it is necessary to transfer the data to the data aggregation point (DAP) before being transmitted to the control center. The numbers and locations of DAPs affect the communication quality and cost of the smart meter neighborhood network, and because smart meters rely on wireless technology to transmit data, their transmission range is limited. Thus, suburban and rural areas require a large number of DAP installation needs, and it is very important to reduce their numbers. For this problem, this study proposes a grid-based relay DAP placement scheme and presents the corresponding algorithms to reduce the number of DAPs and to avoid the large impact of relay DAP locations on communication quality for the two cases of whether or not the number of relay DAPs is limited. This paper used random smart meter coordinates for testing, and the test results verify that the proposed solution can in fact significantly reduce the number of DAPs and avoid the large impact of relay DAP locations on communication quality.

A QoS-Aware Data Aggregation Strategy for Resource Constrained IoT-Enabled AMI Network in Smart Grid

“…To reduce the number of DAPs installation required in rural and suburban areas (neighborhood network), authors proposed [25] a grid-based scheme using corresponding algorithms to minimize the needs of DAPs and eliminate its impact on relay locations such that communication quality is improved in the wireless network. Similarly, the authors in [26] investigated the DAPs point placement problem in terms of guaranteeing real-time communication and shortening latency in the smart metering networks.…”

“…In the aforementioned discussion, various network models such as clustering ( [18], [19], [21], [23], [26], [30], [31], [37]), star ( [22], [25], [36], [38]), tree-based ([27], [28], [34]), and hierarchical ( [24], [29], [32], [39]) models were proposed for AMI network design problem using different data aggregation and data collection techniques as needed for different AMI applications data. In particular, cluster-based network topology uses CH (here, SM and/or DCs) for data collection, processing, data aggregation and relaying purposes in the AMI network.…”