# Communication Performance Assessment for Advanced Metering Infrastructure
## 1 Introduction  
The integration of renewable energy generation into power grids has been looked upon as one of the most effective and efficient methodologies to reduce carbon emissions from energy demand increases. However, the power output of renewable energy generation is quite stochastic with high uncertainty and raises difficulties in the planning and operation of power grids. Smart grids, integrated with new communication interfaces, smart sensing measurement technologies, advanced control strategies, intelligent decision supporting systems etc., are therefore considered to be the best way to facilitate the integration of renewable energy generation. A contemporary smart grid must at least include the functionalities of control and management for renewable energy generation, self-healing from power events, demand response for consumers, optimal power assent usage and management, new market service development and so on [1; 2; 3; 4; 5]. Due to the uncertainties and complexities of smart grids, the deployment of Advanced Metering Infrastructure (AMI) has been treated as the foundation for the realization of smart grids [6; 7; 8; 9; 10; 11]. In general, AMI consists of smart meters, meter data management system, communication infrastructure etc. and can provide useful information based on the data acquired from smart meters to realize numerous intelligent controls and services for smart grids. For example, [PERSON] [11] proposed two methods to discover abnormal electricity consumption by utilizing contextual and factual information from AMI, including energy consumption patterns, nature of supply and categoryof day to logically group meters. The AMI market has experienced a large growth in demand due to the increasing implementation of smart grid technology. The total number of smart meter installations in 2017 was close to 88.2 million and is predicted to reach a cumulative figure of over 588 million by 2022 [6]. [PERSON] [7] forecasted that during the period 2017-2023, the worldwide AMI market is estimated to grow by 9 billion USD by 2023 at a compound annual growth rate of 14%. Some countries including the US, Japan, South Korea and so on have legislated to achieve the target of 100% smart meter deployment. In 2012-2013, an AMI pilot project with about twelve-thousand smart meters has been deployed in Taiwan. Two hundred thousand smart meters are deployed now and this will grow in the next few years to five-million meters. Effective and efficient communication performance between widely-spread smart meters and Data Concentrator Units (DCUs), the core of data management in an AMI providing the technology to measure and collect energy usage data from smart meters to the meter data management system, is one of the most important issues for the successful deployment and operation of AMI. If the communication performance and stability is poor, all AMI functionalities cannot be successfully realized [8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24]. Wire and wireless communications are both the commonly-used communication interfaces. Wire communication with huge construction costs has the advantage of high reliability. The conventional wireless communication techniques have the disadvantages of lower reliability, lower data rate, uncertain time-delay etc. The recent local-area-network communications such as ZigBee and Power Line Communication (PLC), also used in Taiwan's AMI, have been verified to be suitable for the communication network of AMI between the smart meters and DCUs. Some new ZigBee and PLC techniques are still being developed, for example, Reference [15] proposed a new PLC-based smart metering architecture. The coupling interfaces were experimentally verified in a wide frequency range up to 200 kHz using different modulations. Many papers have been published to discuss the communication deployment for AMI [12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24]. Most of the published papers focused on the issues of data acquisition point placement, routing protocol, delay analysis etc.