Forecasting of Power plants consumption using Machine Learning Techniques

Jain, Mohit Kaushal (2023) Forecasting of Power plants consumption using Machine Learning Techniques. Masters thesis, Dublin, National College of Ireland.

Preview	PDF (Master of Science) Download (2MB) | Preview
Preview	PDF (Configuration manual) Download (3MB) | Preview

Abstract

A vital task in ensuring the effective use of energy resources and maintaining a steady power supply is to predict power plant consumption. The generation, distribution, and overall grid stability of energy can all be impacted by changes in power consumption. This study explores the use of machine learning algorithms to forecast power plant consumption with the goal of offering insightful information. This study creates a prediction model for energy consumption by using SARIMAX Time Series Modelling. The dataset used for this study was the Tetuan City power consumption dataset from Kaggle. To evaluate the performance of the model RMSE(Root Mean Square Error) and MSE(Mean Square Error) were used.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Milosavljevic, Vladimir UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Electricity Supply Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Tamara Malone
Date Deposited:	22 Nov 2024 13:26
Last Modified:	22 Nov 2024 13:26
URI:	https://norma.ncirl.ie/id/eprint/7192

Actions (login required)

View Item