Engineering Commons^™

Solar Pv Power Generation Forecasting Using Hybrid Intelligent Algorithms And Uncertainty Quantification Based On Bootstrap Confidence Intervals, Donna Alhakeem

Open Access Theses & Dissertations

This Thesis focuses on short-term photovoltaic forecasting (STPVF) for the power generation of a solar PV system using probabilistic forecasts and deterministic forecasts. Uncertainty estimation, in the form of a probabilistic forecast, is emphasized in this Thesis to quantify the uncertainties of the deterministic forecasts. Two hybrid intelligent models are proposed in two separate chapters to perform the STPVF. In Chapter 4, the framework of the deterministic proposed hybrid intelligent model is presented, which is a combination of wavelet transform (WT) that is a data filtering technique and a soft computing model (SCM) that is generalized regression neural network (GRNN). …

Efficient, Scalable, Parallel, Matrix-Matrix Multiplication, Enrique Portillo

Open Access Theses & Dissertations

For the past decade, power/energy consumption has become a limiting factor for large-scale and embedded High Performance Computing (HPC) systems. This is especially true for systems that include accelerators, e.g., high-end computing devices, such as Graphics Processing Units (GPUs), with terascale computing capabilities and high power draws that greatly surpass that of multi-core CPUs. Accordingly, improving the node-level power/energy efficiency of an application can have a direct and positive impact on both classes of HPC systems.

The research reported in this thesis explores the use of software techniques to enhance the execution-time and power-consumption performance of applications executed on a …