Genetic algorithm-based redundancy optimization method for smart grid communication network

This paper proposes a redundancy optimization method for smart grid Advanced Metering Infrastructure (AMI) to realize economy and reliability targets. AMI is a crucial part of the smart grid to measure, collect, and analyze data about energy usage and power quality from customer premises. From the communication perspective, the AMI consists of smart meters, Home Area Network (HAN) gateways and data concentrators; in particular, the redundancy optimization problem focus on deciding which data concentrator needs redundancy. In order to solve the problem, we first develop a quantitative analysis model for the network economic loss caused by the data concentrator failures. Then, we establish a complete redundancy optimization model, which comprehensively consider the factors of reliability and economy. Finally, an advanced redundancy deployment method based on genetic algorithm (GA) is developed to solve the proposed problem. The simulation results testify that the proposed redundancy optimization method is capable to build a reliable and economic smart grid communication network.