Development of Grey Machine Learning Models for Forecasting of Energy Consumption, Carbon Emission and Energy Generation for the Sustainable Development of Society
Loading...
Date
2023-03
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Energy is an important denominator for evaluating the development of any country. Energy
consumption, energy production and steps towards obtaining green energy are important factors
for sustainable development. With the advent of forecasting technologies, these factors can be
accessed earlier, and the planning path for sustainable development can be chalked out. Forecasting
technologies pertaining to grey systems are in the spotlight due to the fact that they do not require
many data points. In this work, an optimized model with grey machine learning architecture
of a polynomial realization was employed to predict power generation, power consumption and
CO2 emissions. A nonlinear kernel was taken and optimized with a recently published algorithm,
the augmented crow search algorithm (ACSA), for prediction. It was found that as compared to
conventional grey models, the proposed framework yields better results in terms of accuracy.