Optimization of ANFIS controller for solar/battery sources fed UPQC using an hybrid algorithm

• Published in: Electrical engineering 2024, Vol.106 (4), p.3743-3770
• Main Authors: Srilakshmi, Koganti, Rao, Gummadi Srinivasa, Swarnasri, Katragadda, Inkollu, Sai Ram, Kondreddi, Krishnaveni, Balachandran, Praveen Kumar, Colak, Ilhami
• Format: Article
• Language: English
• Subjects: Adaptive algorithms; Adaptive systems; Algorithms; Ant colony optimization; Artificial neural networks; Back propagation networks; Design factors; Direct current; Economics and Management; Electric potential; Electrical Engineering; Electrical Machines and Networks; Energy Policy; Engineering; Fuzzy logic; Genetic algorithms; Harmonic distortion; Heuristic methods; Irradiation; Network control; Original Paper; Photovoltaic cells; Power Electronics; Power factor; Reference signals; Search algorithms; Solar radiation; Voltage
• ISSN: 0948-7921; 1432-0487
• DOI: 10.1007/s00202-023-02185-8

This study introduces an integrated power quality (PQ) conditioner, referred to as UPQC, that is linked with photovoltaic (PV) and battery energy systems (BSS) in order to address and solve PQ issues. It is proposed to employ the Levenberg–Marquardt (LM) backpropagation (LMBP) trained artificial neural network control (ANNC) technique for generating reference signal for converters in UPQC. This approach eliminates the need for traditional abc to dq0 to αβ conversions. Additionally, the hybrid algorithm (FFHSA) in combination of harmony search algorithm (HSA), and firefly algorithm (FFA) is also implemented for the optimal selection of adaptive neuro-fuzzy interface system (ANFIS) parameters to maintain direct current link capacitor voltage (DLCV) constant. The prime goal of the developed hybrid ANNC-FFHSA is to stabilize the DLCV with low settling time during load and solar irradiation (G), Temperature (T) changes, minimization of distortions in the source current signal to diminish total harmonic distortion (THD) in turn boosting the power factor (PF), suppression of fluctuations like disturbances, swell, sag and unbalances in the supply voltage. The suggested method is validated by four test cases with several combinations of variable irradiation (G), temperature and loads. On the other hand, to reveal the superiority of the developed method, the comparison is carried out with the genetic algorithm (GA) and Ant colony algorithm (ACA) along with instantaneous power (p–q) and Synchronous reference frame (SRF) conventional methods. The proposed approach significantly diminishes the total harmonic distortion to values of 3.61%, 3.48%, 3.48%, and 4.51%, which are notably lower compared to the values reported in the existing literature and also improves the power factor to almost unity. The design and implementation of this method were carried out using MATLAB/Simulink software.