Towards cloud energy metering system with 32 bit FPGA device architecture
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