Hybrid Forecasting Model for Smart Grid Using Exogenous Variables
F Shaikh, HA Khattak - 2024 International Conference on …, 2024 - ieeexplore.ieee.org
Smart grids augment the existing power grids with information and communication
technology to enable enhanced monitoring and control. Power grid resilience and failure …
technology to enable enhanced monitoring and control. Power grid resilience and failure …
GHI Prediction Based on Weather Data Using Machine Learning
SV Hiremath, R Naik, S Naik, S Shettar… - 2024 IEEE …, 2024 - ieeexplore.ieee.org
The proposed model aims to predict Global Horizontal Irradiance (GHI) by using various
environmental factors and several Machine Learning algorithms like Linear Regression …
environmental factors and several Machine Learning algorithms like Linear Regression …
Eclipse Assessment Using Distributed Gradient Boosted Decision Tree-Specific Machine Learning Model
In the observable universe, we have mainly two types of eclipses on Earth: solar eclipse and
lunar eclipse. Solar eclipse is defined as the alignment of Moon between Sun and Earth …
lunar eclipse. Solar eclipse is defined as the alignment of Moon between Sun and Earth …
Comparative Analysis of Univariate and Multivariate Models for Solar Irradiance Forecasting
The focus of this study is to analyse and compare the predictive capabilities of univariate
and multivariate methods of forecasting the global horizontal irradiance (GHI) for an hour …
and multivariate methods of forecasting the global horizontal irradiance (GHI) for an hour …
Predictive Modeling of Solar Energy Production: A Comparative Analysis of Machine Learning and Time Series Approaches
MM Sucharitha, S Sowjanya… - … for Women in …, 2024 - ieeexplore.ieee.org
In this study, we dive into the world of renewable energy, specifically focusing on predicting
solar energy output, which is a crucial part of managing renewable energy resources. We …
solar energy output, which is a crucial part of managing renewable energy resources. We …