TY  - EJOU
AU  - Sung, Tien-Wen 
AU  - Li, Wei 
AU  - Lee, Chao-Yang 
AU  - Chen, Yuzhen 
AU  - Fang, Qingjun 

TI  - Data Aggregation Point Placement and Subnetwork Optimization for Smart Grids
T2  - Computers, Materials \& Continua

PY  - 2025
VL  - 83
IS  - 1
SN  - 1546-2226

AB  - To transmit customer power data collected by smart meters (SMs) to utility companies, data must first be transmitted to the corresponding data aggregation point (DAP) of the SM. The number of DAPs installed and the installation location greatly impact the whole network. For the traditional DAP placement algorithm, the number of DAPs must be set in advance, but determining the best number of DAPs is difficult, which undoubtedly reduces the overall performance of the network. Moreover, the excessive gap between the loads of different DAPs is also an important factor affecting the quality of the network. To address the above problems, this paper proposes a DAP placement algorithm, APSSA, based on the improved affinity propagation (AP) algorithm and sparrow search (SSA) algorithm, which can select the appropriate number of DAPs to be installed and the corresponding installation locations according to the number of SMs and their distribution locations in different environments. The algorithm adds an allocation mechanism to optimize the subnetwork in the SSA. APSSA is evaluated under three different areas and compared with other DAP placement algorithms. The experimental results validated that the method in this paper can reduce the network cost, shorten the average transmission distance, and reduce the load gap.
KW  - Smart grid; data aggregation point placement; network cost; average transmission distance; load gap

DO  - 10.32604/cmc.2025.061694