Swarm decomposition technique based hybrid model for very short-term solar PV power generation forecast

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DOKUR E.

Elektronika ir Elektrotechnika, cilt.26, sa.3, ss.79-83, 2020 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 26 Sayı: 3
  • Basım Tarihi: 2020
  • Doi Numarası: 10.5755/j01.eie.26.3.25898
  • Dergi Adı: Elektronika ir Elektrotechnika
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Applied Science & Technology Source, Central & Eastern European Academic Source (CEEAS), Communication Abstracts, Computer & Applied Sciences, INSPEC, Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.79-83
  • Anahtar Kelimeler: Energy management, Forecasting, Solar energy, Swarm decomposition
  • Bilecik Şeyh Edebali Üniversitesi Adresli: Evet

Özet

© 2020 Kauno Technologijos Universitetas. All rights reserved.Accurate predictions of solar photovoltaic (PV) power generation at different time horizons are essential for reliable operation of energy management systems. The output power of a PV power plant is dependent on non-linear and intermittent environmental factors, such as solar irradiance, wind speed, relative humidity, etc. Intermittency and randomness of solar PV power effect precision of estimation. To address the challenge, this paper presents a Swarm Decomposition Technique (SWD) based hybrid model as a novel approach for very short-term (15 min) solar PV power generation forecast. The original contribution of the study is to investigate use of SWD for solar data forecast. The solar PV power generation data with hourly resolution obtained from the field (grid connected, 857.08 kWp Akgul Solar PV Power Plant in Turkey) are used to develop and validate the forecast model. Specifically, the analysis showed that the hybrid model with SWD technique provides highly accurate predictions in cloudy periods.