Hybrid Random Forest and Particle Swarm Optimization Algorithm for Solar Radiation Prediction

Sunayana Gupta, Anudeep Reddy Katta, Yashi Baldaniya, Rajesh Kumar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Citations (Scopus)

Abstract

Due to increased pollution, greenhouse effect and global warming resulting from power production using fossil fuels, there is increased penetration of renewable energy sources into the power system. The concept of microgrids has made solar radiation an indispensable source of power in the distribution system. But the power production using solar energy is highly variable and weather dependent which creates a power imbalance into the system when it is penetrated without forecasting. Therefore, solar power prediction plays a critical role in the proper usage of solar energy while keeping the system stable. For automating the power system, the forecast needs to be very accurate and thus, it is needed to improve the existing forecasting techniques. In this study, we have proposed a solar radiation scheme based on various meteorological factors, including temperature, humidity, wind speed, and others. We have introduced a hybrid model for prediction which optimizes the parameters of Random Forest using Particle Swarm Optimization technique.

Original languageEnglish
Title of host publication2020 IEEE 5th International Conference on Computing Communication and Automation, ICCCA 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages302-307
Number of pages6
ISBN (Electronic)9781728163246
DOIs
Publication statusPublished - 30 Oct 2020
Externally publishedYes
Event5th IEEE International Conference on Computing Communication and Automation, ICCCA 2020 - Greater Noida, India
Duration: 30 Oct 202031 Oct 2020

Publication series

Name2020 IEEE 5th International Conference on Computing Communication and Automation, ICCCA 2020

Conference

Conference5th IEEE International Conference on Computing Communication and Automation, ICCCA 2020
Country/TerritoryIndia
CityGreater Noida
Period30/10/2031/10/20

Keywords

  • Decision Tree
  • Distribution Automation
  • Particle Swarm Optimization
  • Radiation
  • Random Forest

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Control and Optimization

Fingerprint

Dive into the research topics of 'Hybrid Random Forest and Particle Swarm Optimization Algorithm for Solar Radiation Prediction'. Together they form a unique fingerprint.

Cite this