Cost-efficient approximation algorithm for aggregation points planning in smart grid communications

  • Yue Li
  • Tianyu Wang
  • Shaowei WangEmail author


Smart grid is in need of an efficient communication network to guarantee reliable two-way data transmission between the control center and smart meters (SMs). In this work, a software-defined networking (SDN) based smart grid communication (SGC) scheme is introduced to fulfill the information transmission requirement, where the control plane is separated from the data plane to support diverse services flexibly in the smart grid. In such an SDN-based SGC system, to guarantee effective data processing and forwarding between the SMs and the control center, aggregation points (APs) are introduced. These APs should be deployed in an optimal way so as to cut down the total capital expenditure of the SGC system. The total cost generally includes the transmission cost between APs and the control center as well as APs and SMs. The construction and maintenance cost of the APs is also included. An approximation algorithm is introduced in this paper. The algorithm can deal with the formulated intractable APs planning task and produce performance-guaranteed solutions with reasonable complexity. Experiments indicate that the proposed algorithm works well for geographical areas with different densities of SMs. Our proposal yields cost-efficient APs deployment scheme and sheds insight into the reduction of the capital expenditure of the SGC system.


Aggregation point Approximation algorithm Smart grid communications Software defined network 



The authors would acknowledge the financial and data support from State Grid Corporation of China (SGCC). This work was partially supported by the National Natural Science Foundation of China (61671233, 61801208, 61931023), the Jiangsu Science Foundation (BK20170650), the Postdoctoral Science Foundation of China (BX201700118, 2017M621712), the Jiangsu Postdoctoral Science Foundation (1701118B), and the open research fund of National Mobile Communications Research Laboratory (2019D02).


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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Nanjing UniversityNanjingChina

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