PSC USA partnered with the Pacific Northwest National Labs (PNNL) to study the effects of smart grid technology on distribution feeders using the GridLAB-D™ simulation software. This smart grid demonstration project is aimed at reducing dependence on imported energy and improving energy supply. The project location was chosen due to the large penetration of existing and planned wind and solar distributed generation in a region with limited grid interconnections. Three technologies that will have effects on the future distribution system will be considered for this study; electric vehicles (EV), solar photo voltaic (PV), and micro distribution management system (µDMS).
The GridLAB-D™ software employed for this work is a power distribution system simulation and analysis tool. This was initially developed by the U.S. Department of Energy at PNNL. The software incorporates advanced modeling techniques with high-performance algorithms to deliver the latest in end-use load modeling technology.
For the PNNL smart grid demonstration project, PSC USA distribution engineers were given three base case feeders that were modeled in the GridLAB-D™ simulation environment. These feeder models were then populated with four varying amounts of PV penetration; 5%, 20%, and 50% of historical peak load, and a 1MW PV array near the end of each feeder. One minute and one second time interval simulations were run on the populated feeders and compared to the base cases to study the effect of the additional PV on system voltage, power factor, and system losses and the effects of cloud transients.
In conjunction with this study, a web-based training session was presented by PNNL staff. In this training PSC employees from various parts of the world were given an overview of GridLAB-D™ software, its functionality, and how to create models for use with GridLAB-D™.
Going forward PSC USA and PNNL will partner to deliver a GridLAB-D™ simulation model on weather-driven time-series power flows for distribution feeders operated by a major American utility. These feeders will include detailed models of end-use loads, demand response schemes, and other selected smart grid assets such as electric vehicles and distributed storage and generation. The purpose of this simulation model is to form the basis to develop predictive control strategies and decision support tools for advanced distribution management systems (DMS).
Gridlab-D website: http://www.gridlabd.org/