|dc.description.abstract||The power grid is a complex network interconnecting energy sources with loads. The power flow
and state estimation problems model the power flows and voltages throughout the grid. They are
currently solved using computer simulations computed with serial processing methods, on
traditional CPUs. To reduce the simulation timelines, and provide a faster, “real-time” solution, the
practicality of using the Graphics Processing Unit (GPU) will be investigated.
High Performance Computing (HPC) technology is becoming more mature as it is being interweaved
in many high-computational tasks related to the STEM industry. Currently, the knowledge barrier to
entry is relatively low and therefore the concepts of HPC can be applied to power simulation
software used in MATPOWER and MATLAB™ with minimal knowledge of GPU primitives coding in
OpenGL and DirectX.
MATLAB’s parallel computing toolbox has many built-in functions that will compute their operations
directly on the GPU. This thesis will take this simplified approach to HPC and leverage this toolbox
to determine if the power flow problem can be sped up by paralleizing MATPOWER’s algorithm,
which is already optimized to run on the CPU. If speed up is achieved this technology can be used
with MATPOWER’s already robust libraries and functions to help researchers in the areas Optimal
Power Flow (OPF), State Estimation, and Economic Dispatch to name a few.
The conclusion to this thesis will demonstrate that yes, a simplified approach to power flow can be
executed using MATLAB’s parallel computing toolbox, but there are bottlenecks created by the
limitations of MATLAB, which if addressed through future research, could unlock the full potential
behind the GPU.||en_US