Renewable energy inclusion on economic power optimization using thunderstorm algorithm

A. N. Afandi, Goro Fujita, Nguyen Phuc Khai, Yunis Sulistyorini, Nedim Tutkun

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

12 Citations (Scopus)

Abstract

This paper presents an economic operation considered renewable energy which is optimized using thunderstorm algorithm. The problem is constrained by an emission standard and various technical limits implemented on the 62-bus system model. Simulations showed that the renewable energy inclusion penetrates to the unit commitment of generating units with strongly approach for the computational solution. This inclusion also affects to the individual power production in accordance to the fuel cost and pollutant discharge.

Original languageEnglish
Title of host publicationProceedings - 2017 4th International Conference on Electrical Engineering, Computer Science and Informatics, EECSI 2017
PublisherInstitute of Advanced Engineering and Science
Volume2017-December
ISBN (Electronic)9781538605486
DOIs
Publication statusPublished - 2017 Dec 22
Event4th International Conference on Electrical Engineering, Computer Science and Informatics, EECSI 2017 - Yogyakarta, Indonesia
Duration: 2017 Sep 192017 Sep 21

Other

Other4th International Conference on Electrical Engineering, Computer Science and Informatics, EECSI 2017
CountryIndonesia
CityYogyakarta
Period17/9/1917/9/21

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Keywords

  • Economic operation
  • Pollutant emission
  • Renewable energy
  • Thunderstorm algorithm

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Information Systems
  • Electrical and Electronic Engineering

Cite this

Afandi, A. N., Fujita, G., Khai, N. P., Sulistyorini, Y., & Tutkun, N. (2017). Renewable energy inclusion on economic power optimization using thunderstorm algorithm. In Proceedings - 2017 4th International Conference on Electrical Engineering, Computer Science and Informatics, EECSI 2017 (Vol. 2017-December). Institute of Advanced Engineering and Science. https://doi.org/10.1109/EECSI.2017.8239141