Recent advancements in the field of Natural Language Processing (NLP) and Large Language Models (LLMs) have opened new avenues for processing qualitative data. This development is particularly interesting for power systems as they have an enormous amount of untapped qualitative data. Decision-making in the power system sector has relied on quantitative data. However, qualitative data…
This study explores the impact of weather features on short to medium electricity load prediction across diverse geographical locations. Using hourly load data, we evaluated the effectiveness of several feature selection methods, including Mutual Information (MI), Principal Component Analysis (PCA), Lasso, and Heatmap correlation. We benchmarked these feature selection methods with a hybrid deep learning model to investigate the impact of choosing…
The integration of wind energy into the power grid has been on the rise, becoming an increasingly important source of electricity. However, the intermittency of wind energy output, particularly the wind power ramps (the rate at which wind energy output increases or decreases) can pose challenges for the grid and its operators. The first step…