Towards cloud energy metering system with 32 bit FPGA device architecture

Abstract

Cloud based Advanced Metering Infrastructure (CAMI) is the next digital future for energy  management (EM). Various efforts on EM capabilities are mainly skewed towards embedded device  architectures that support non-concurrent execution. This paper presents cloud energy metering system  (CEMS) using high speed 32 bit field programmable gate array (FPGA) device. The architectural  framework for energy tracking and profile measurement in CEMS is presented. This aims at accurate  metering with demand side management (DSM). An application context that supports an EM  architecture is highlighted. The contextual CEMS features energy monitoring in distributed energy  utilities such as solar generators, wind and energy storage sources. Process integration with Cloud  based Internet for real-time energy reading is achieved through the FPGA synthesis to provide end-to-end energy analytics. CEM prototype (Xilinx FPGA) running on a wireless open-access research  platform supports management of large historical data-sets from the current data up to the last granular  interval, hourly, daily, monthly and yearly dataset captures. The system provides the low latency  datasets in both tabular and graphical forms for end-user visualization of energy consumption patterns.  In the experimental setup, three case scenarios demonstrate how the metering system executes fast  edge computing profiling, thereby providing data-visualization services to end-users. The results show  the Avg. Latency time for CAMI household 1, 2 and 3 respectively. In case 1, the average latencies for  actual and measured (proposed CAMI) are 75% and 25% respectively. In case 2 and case 3, this gave  66.67% and 33.33% respectively. Clearly, the proposed CAMI offers lower latency for all scenarios of  energy consumption metering usage.

Keywords: Advanced Metering, Energy management, Cyber-physical systems, Cloud Computing,  IoT, Fog. 1.0 INTRODUCTION