Abstract

This effort to make the power grid more intelligent is tightly coupled with the deployment of advanced metering infrastructure (AMI) as an integral part of the future vision of smart grid. The goal of AMI is to provide necessary information for the consumers and utilities to accurately monitor and manage energy consumption and pricing in real time. Immediate benefits are enhanced transparency and efficiency of energy usage and the improvement of customer services. Although the road map toward successful AMI deployment is clearly defined, many challenges and issues are to be solved regarding the design of AMI. In this paper, a multi-agent AMI based on the fog-computing approach is presented. Architecture follows structural decomposition of AMI functionalities encapsulated in a form of local and area-specific service components that reside at the different tiers of hierarchically organized AMI deployment. Fog computing concepts provide the framework to effectively solve the problems of creating refined and scalable solutions capable of meeting the requirements of the AMI as a part of future smart grid. On the other hand, agent-based design enables concurrent execution of AMI operations across the distributed system architecture, in the same time improving performance of its execution and preserving the scalability of the AMI solution. The real-time performance of the proposed AMI solution, related to the periodic and on-demand acquisition of metering data from the connected electricity meters, was successfully verified during one year of pilot project operation. The detailed analysis of the performance of AMI operation regarding data collection, communication and data availability across the deployed pilot AMI, covering several transformer station areas with diverse grid topologies, is also presented.

Highlights

  • The presented advanced metering infrastructure (AMI) architecture, based on fog-computing, defines the flexible and scalable framework for the implementation of all the AMI functionalities envisioned in the Smart Grid concept

  • The real-time operation is provided by adopting hierarchically organized tiered model for AMI implementation, where Local Meter Concentrator (LMC) tier can be considered as a conceptual upgrade of electricity meter (EM) communication module, and the Transformer Station Concentrator (TSC) tier as an upgrade of a traditional gateway-based data concentrator

  • Introduction of the service agents enables a unified model for the automated execution of the tier-specific services, without any unnecessary involvement of upper-tier AMI services

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Summary

Introduction

The road-map of the smart grid [1] and representative surveys [2,3,4,5] point out the essential role of AMI in the joint effort of smart grid subsystems to enable sophisticated real-time services for monitoring, management, and optimization of the power distribution from generation sources to the end-users. Comprehensive reviews of the smart grid application in different technology areas [6,7,8], as well as the analyses of the smart grid infrastructure, architecture, and communication requirements [9,10,11,12,13,14,15], identify the most recent open issues of AMI implementation, regarding large-scale deployment, communication, big-data analysis, real-time operation, information security and scalability. There are only a few papers analyzing the possibility of upgrading the existing metering infrastructure for their integration in smart grid, the majority of existing electricity meters are legacy models with constrained communication capabilities

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