An Application-Specific Instruction Set Processor for Power Quality Monitoring

Power quality has an essential relevance for industrial economies. Server farms and highly accurate automation processes are directly dependent on the power quality of the power grid. To guarantee a standard of quality, power is measured by power quality monitoring (PQM) units. However, standard PQM systems using servers for data processing are too expensive for the installation on small power plants, which is especially a problem for the increasing number of small scaled renewable energy power plants. Thus, there are several embedded approaches using microcontrollers or FPGAs, but they are insufficient in terms of performance or flexibility. This work presents an application-specific instruction set processor (ASIP) architecture for PQM implemented on a low-end FPGA. ASIPs include customized operators, which are optimized for algorithms of specific applications. This weak programmable architecture leads to a flexible system delivering sufficient performance for handling multiple different PQM tasks in parallel. Moreover, a comparison with the embedded processors ARM Cortex-A9 and Epiphany III (E16) shows, that PQM algorithms can be executed up to five times faster even for only one measurement channel.