HiPAS GridLAB-D: A High-Performance Agent-based Simulation using GridLAB-D
The High Performance Agent-based Simulation upgrade speeds up performance and efficiency of GridLAB-D.
In 2022, the HiPAS project team completed the beta version of GridLAB-D to support OpenFIDO and GLOW. The project team evaluated the performance of HiPAS GridLAB-D on the National Grid 15-year load forecast study for the state of New York and demonstrated more than 100-fold speed increase and more 1000-fold cost decrease. The four use-cases (integrated capacity analysis, distribution system resilience analysis, tariff design, and end-use load electrification) were completed and deployed. The final production release of HiPAS GridLAB-D was prepared and will be released in 2023. The Linux Foundation Energy has adopted HiPAS GridLAB-D as an open-source project they will support after the project ends, and will be distributed commercially under the name "Arras Energy".
The High Performance Agent-Based Simulation (HiPAS) GridLAB-D project will increase the performance of the open-source version of GridLAB-D and improve the broad accessibility of high-performance power grid simulation capabilities to the community of smart grid and distribution simulation users in California. HiPAS includes methods that parallelize many of the iterative methods used in simulations. HiPAS is intended for both desktop multi-core processors and cloud platforms. It will enable GridLAB-D users to more efficiently analyze multiple scenarios with improved resolution by reducing the computational costs associated with analysis.
HiPAS GridLAB-D will address the primary barriers to analyzing more grid locations for distributed energy resource deployment, by reducing the computational costs associated with these kinds of analyses. This will reduce the cost for interconnection studies.
The HiPAS enhancements to GridLAB-D achieved through this project will increase utility analyst productivity in performing distributed energy resource integration studies by improving the accuracy and timeliness of results supporting interconnection and grid planning.
Key Project Members
Pacific Northwest National Laboratory