A Novel Artificial Intelligence Maximum Power Point Tracking Technique for Integrated PV-WT-FC Frameworks

Abstract

The development of each country depends on electricity. In this regard, conventional energy sources, e.g., diesel, petrol, etc., are decaying. Consequently, the investigations of renewable energy sources (RES) are increasing as alternate energy sources for the fulfillment of energy requirements. The output characteristics of RES are becoming non-linear. Therefore, the Maximum Power Point Tracking (MPPT) techniques are critical for extracting the Maximum Power Point (MPP) from RES, e.g., photovoltaic (PV) and wind turbines (WT). RES such as the Fuel Cell (FC) has been hailed as one of the major capable RES for automobile applications since they continually create electricity for the dc-link (even if one or both RES are not supplied by solar and wind, the FC will continue to supply to the load). Adaptive Neuro-Fuzzy Inference System (AN-FIS) MPPT for PV, WT, FC, and Hybrid RES is employed in this research article to solve this problem. The high step-ups (boost converters) are connected with PV and FC modules, and the buck converter is connected with the WT framework, to extract the maximum amount of power using MPPT algorithms. The performance of proposed frameworks based on MPPT algorithms is assessed in variable operating conditions such as Solar-Radiation (SR), Wind-Speed (WS), and Hydrogen-Fuel-Rate (HFR). A novel AN-FIS MPPT framework has enhanced the power of Hybrid RES at DC-link, and also reduced the simulation time to reach the MPP when compared to the perturb and observe (P-&-O), Fuzzy-Logic Controller (F-LC), and artificial neural network (AN-N) MPPTs.

Artificial Intelligence Techniques for the Photovoltaic System: A Systematic Review and Analysis for Evaluation and Benchmarking

“…Figure 1 shows the basic process of the PV generation process. The radiant energy is absorbed by the PV panel or grid of PV panels [34]. This radiant energy is then converted into DC power and then it is passed to the power electronic converters [32,35].…”

“…A review of the AI-based Maximum Power Point Tracking (MPPT) in the solar power system was carried out by Yap et al [60]. Since conventional MPPT techniques are unable to track the global maximum power point under Partial Shading Conditions (PSC), it is necessary to introduce artificial intelligence techniques to enhance this method [34,61]. A model-based approach has been used to review the specific MPPT open-circuit voltage.…”

Renewable Energy and Energy Storage Systems

“…Sometimes there are several different renewable energy sources integrated with one or more other energy storage systems, as shown in Figure 6. The main purpose of these integrations is to guarantee a continuous energy supply all day at the lowest cost [97][98][99]. Many researchers have studied the combination of different renewable energy systems to provide carbon-free, higher energy production, and cheap energy sources [100].…”

Maximum Power Point Tracking Simulation for Photovoltaic Systems Using Perturb and Observe Algorithm

“…There are different techniques used to track the maximum power point. These are perturb and observe, incremental conductance method, fractional short-circuit current, fractional open-circuit voltage, and neural network [7][8][9][10][11].…”