A Novel Wind Power Forecasting Based Feature Selection and Hybrid Forecast Engine Bundled with Honey Bee Mating Optimization

Mehdi Bagheri, Venera Nurmanova, Oveis Abedinia, Mohammad Salay Naderi, Mehdi Salay Naderi, Noradin Ghadimi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

In this study, new forecasting approach is developed for wind power signal based on Empirical Mode Decomposition (EMD), feature selection and forecast engine. Due to high volatility of wind power signal, we used a complex prediction approach with hybrid forecast engine. The proposed forecast engine is coupled with an intelligent algorithm to improve the training mechanism and optimize free parameters. To show the abilities of proposed forecasting approach real test case is considered by comparison with other strategies. In order to proof the superiority of suggested method, it is compared with various prediction approaches. Generated results confirm the validity of this strategy.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538651858
DOIs
Publication statusPublished - Oct 16 2018
Event2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018 - Palermo, Italy
Duration: Jun 12 2018Jun 15 2018

Other

Other2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018
CountryItaly
CityPalermo
Period6/12/186/15/18

Keywords

  • EMD
  • Feature Selection
  • Hybrid Forecast Engine
  • Wind Power Forecast

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering
  • Environmental Engineering
  • Hardware and Architecture

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  • Cite this

    Bagheri, M., Nurmanova, V., Abedinia, O., Naderi, M. S., Naderi, M. S., & Ghadimi, N. (2018). A Novel Wind Power Forecasting Based Feature Selection and Hybrid Forecast Engine Bundled with Honey Bee Mating Optimization. In Proceedings - 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018 [8493805] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EEEIC.2018.8493805