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

Author:

Sung Tien-Wen1,Xu Yuntao1,Hu Xiaohui1,Lee Chao-Yang2,Fang Qingjun1

Affiliation:

1. Fujian Provincial Key Laboratory of Big Data Mining and Applications, College of Computer Science and Mathematics, Fujian University of Technology, Fuzhou, China

2. Department of Aeronautical Engineering, National Formosa University, Yunlin, Taiwan

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.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

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1. Privacy Preserving Data Aggregation Algorithm for IoT-Enabled Advanced Metering Infrastructure Network in Smart Grid;Advances in Information Security, Privacy, and Ethics;2024-06-28

2. New Dual Algorithm to Placement the Data Aggregation Point for Smart Grid Meters;Smart Grids and Sustainable Energy;2024-03-22

3. A multi-hierarchical method to extract spatial network structures from large-scale origin-destination flow data;International Journal of Geographical Information Science;2024-01-09

4. Data Center Location Planning for Social Network Data;2023 Tenth International Conference on Social Networks Analysis, Management and Security (SNAMS);2023-11-21

5. A QoS-Aware Data Aggregation Strategy for Resource Constrained IoT-Enabled AMI Network in Smart Grid;IEEE Access;2023

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