long-term solar irradiance forecasting using multilinear predictors

Title

long-term solar irradiance forecasting using multilinear predictors

Abstract

As the demand for crude oil is increasing every day, prices and pollution are both increasing in return, which has harmful effects on the environment. Thus, more attempts are being made to develop clean energy to rescue the planet and provide humanity with a cleaner energy source. As the renewable energy sector grows, new issues and challenges have emerged. Instability in electricity production from wind turbines, solar power plants, and dams creates challenges for energy transmission and storage systems. In order to achieve a more reliable and effective energy system, machine learning techniques have been used to forecast energy changes. Predicting the sun's Global Horizontal Irradiance (GHI) is one of the machine learning applications used in that sector. In this paper, many machine learning methods have been utilized, such as linear regression and long-short term memory (LSTM) methods to have long term GHI forecasting. Moreover, the significance of this paper is located in the way of prediction of the GHI irradiance prediction by using different levels of the linear regressors to find the best regressor level that provides the minimum error for the testing set based on cross-validation. Results showed that the regressor method provides a lower error compared with a single vanilla LSTM system for a shorter time computationally.

Scientific Type

اكاديمي

Link

http://www.ijeetc.com/show-233-1704-1.html

Journal volume

vol.12,No.2

Collaboration type

مشترك

Publish Date

March 1, 2023

Participated Universities (Publication)

Alnoor University

Al-Hadba University College

Mosul University

Scopus status

In Scopus

Scopus index year

2 023

Scopus quarter

2

Scopus citation score

3.200000048

Clarivate status

Not In Clarivate

Pub. Med. status

Not In PubMed

Author (Publication)

عبد المجيد احمد رفعت محمود

Journal (Publication)

International Journal of Electrical and Electronic Engineering & Telecommunications

Publisher (Publication)

Warsaw University of Technology

ISSN

2319-2518

Country (Publication)

India

Country type

عالمية

College (Publication)

College of Health and Medical Technologies

Departement (Publication)

Department of Optics Techniques