Comparative Analysis of Reduced-Rule Compressed Fuzzy Logic Control and Incremental Conductance MPPT Methods

Kandemir E., BÖREKCİ S., ÇETİN N. S.

JOURNAL OF ELECTRONIC MATERIALS, cilt.47, sa.8, ss.4463-4474, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 47 Sayı: 8
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1007/s11664-018-6273-y
  • Dergi Adı: JOURNAL OF ELECTRONIC MATERIALS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.4463-4474
  • Anahtar Kelimeler: PV model, maximum-power-point tracking, incremental conductance, fuzzy logic control, POWER-POINT-TRACKING, PHOTOVOLTAIC SYSTEMS, EFFICIENCY, ALGORITHM, ARRAY, IMPLEMENTATION, CONVERSION, PERTURB, OBSERVE, SEARCH
  • Akdeniz Üniversitesi Adresli: Evet

Özet

Photovoltaic (PV) power generation has been widely used in recent years, with techniques for increasing the power efficiency representing one of the most important issues. The available maximum power of a PV panel is dependent on environmental conditions such as solar irradiance and temperature. To extract the maximum available power from a PV panel, various maximum-power-point tracking (MPPT) methods are used. In this work, two different MPPT methods were implemented for a 150-W PV panel. The first method, known as incremental conductance (Inc. Cond.) MPPT, determines the maximum power by measuring the derivative of the PV voltage and current. The other method is based on reduced-rule compressed fuzzy logic control (RR-FLC), using which it is relatively easier to determine the maximum power because a single input variable is used to reduce computing loads. In this study, a 150-W PV panel system model was realized using these MPPT methods in MATLAB and the results compared. According to the simulation results, the proposed RR-FLC-based MPPT could increase the response rate and tracking accuracy by 4.66% under standard test conditions.