Steady State Modeling and ANFIS Based Analysis of Doubly-Fed Induction Generator

Abstract

The paper presents a new technique for the steady state performance analysis of the DFIG using Adaptive Neuro-Fuzzy Inference System (ANFIS). First, a mathematical model of DFIG in an appropriate d-q reference frame is established. The effect of the excitation voltage vector on the performance characteristics is illustrated to investigate simulations. A novel approach for the performance analysis of DFIG using ANFIS is employed for fast, accurate, and efficient methodology. The proposed ANFIS model has been trained off-line to predict the effect of excitation voltage magnitude, excitation voltage angle and speed on total output power of DFIG without overheating. The performance of the proposed scheme is investigated at different operating conditions. The simulation study indicates accuracy and effectiveness of the ANFIS based modeling of DFIG.

Concurrent unity power factor and constant mutual flux control for PMSG-WT MPPT

“…It is also predicted that by 2020–2030, nearly 20% of the energy required by the world will be supplied by wind power (Flavin, 2008). Many of the generators that have been investigated and have practical applications in wind power generation are double-fed induction generators (Ayrir and Haddi, 2019; Elsonbaty and Holmes, 1982, 1983a, 1983b; Elsonbaty et al, 1993, 2015, 2015a, 2015b, 2016, 2017, 2018a, 2018b; Holmes and Elsonbaty, 1984; Zhou et al, 2015). The results of this research show good performance, reliability, and depending on the control strategy, a good dynamic response for this type of machines.…”