An Advanced Software Designed Intelligent Electronic Device Platform

Abstract

Technology progress combined with aging infrastructure and a use case model that evolved and changed completely over the years is a common external force affecting energy companies worldwide. As a result, the idea of a “smart grid” has taken center stage • an evolution of advanced technologies that make the availability of a smarter, more efficient electrical power grid possible. Whether this is providing an abundant supply of electricity, deploying distributed intelligence at the measurement nodes or improving overall reliability, monitoring, and safety, energy companies are realizing the importance of technology to address the complex challenges facing grid systems today. As a result, a new generation of instruments, also known as Software Designed Intelligent Electronic Devices (SD-IEDs) are rapidly being deployed throughout the power system. Utilizing computer-based remote control and automation, these devices can be efficiently controlled and adjusted at the node level as changes and disturbances on the grid occur. In another example, utilities could use a generic SD-IED platform, and define the instrument functionality and algorithms executed completely in software using graphical design tools. At the heart of these advanced SD-IEDs lies the powerful technology of the FPGA, yielding additional flexibility and reliability that allows convergence of multiple functional devices into a single unit, which in turn lowers the cost of smart grid systems as a whole. Because FPGAs can be reprogrammed in the field, as requirements and standards for the smart grid mature, functional enhancements can be deployed to SD-IEDs without the need to modify the hardware layout or replace the entire device. SD-IEDs represents a fundamental shift from traditional hardware-centric instrumentation systems to software-centric systems that explore computing power, productivity, and connectivity capabilities of popular desktop computers. This paper describes how to apply the virtual instrumentation approach to create advanced SD-IEDs and illustrates it with two deployment examples: (1) smart switches for a leading energy delivery utility in the USA, and (2) advanced PMU research for distribution grids.