Overview of Solar Photovoltaic MPPT Methods: A State of the Art on Conventional and Artificial Intelligence Control Techniques

Author:

Mazumdar Debabrata1,Sain Chiranjit2,Biswas Pabitra Kumar1,Sanjeevikumar P.3,Khan Baseem45ORCID

Affiliation:

1. Department of Electrical & Electronics Engineering, National Institute of Technology, Aizwal, Mizoram 796012, India

2. Department of Electrical Engineering, Ghani Khan Chowdhury Institute of Engineering & Technology, Narayanpur, Malda 732141, West Bengal, India

3. Department of Electrical Engineering, IT and Cybernetics, University of South-Eastern Norway, Porsgrunn 3918, Norway

4. Department of Electrical and Computer Engineering, Hawassa University, Hawassa, Ethiopia

5. Department of Electrical and Electronic Engineering Technology, University of Johannesburg, Johannesburg, South Africa

Abstract

Due to their inherent ability and environmentally friendly nature, renewable energy sources are the only real option for producing pollution-free energy in the modern era. Solar energy is one of the best possibilities in this family for supplying civilization with the power and energy it needs. Researchers can efficiently boost a PV panel’s efficiency by using the maximum power point tracking (MPPT) approach to extract the most power from the panel and send it to the load. The authors of this study examined and surveyed the sequential advancement of solar PV cell research from one decade to the next, and they elaborated on the upcoming trends and behaviours. Many maximum power point tracking algorithms (MPPTs) that are employed in photovoltaic systems (PVSs) that function under both uniform and partial shade situations are structurally summarized in this work. Well-written descriptions of the features of photovoltaic modules are followed by a variety of effective control strategies, including both AI-based and traditional controllers. In addition, appropriate knowledge of the various controllers is essential when the PV system is exposed to partial shade, keeping in mind the different control systems’ classifications in this situation. A thorough analysis of several soft computing-based techniques is also included, as well as many classical controller-based PV systems. First, well-developed traditional MPPT methods are used, followed by artificial intelligence-based MPPT approaches. Later, a thorough comparison of the various MPPT-controlling approaches is established. For PV systems operating under partial shade conditions (PSCs), the advantages and disadvantages of the various MPPT techniques are outlined, contrasted, and assessed. Future research directions for MPPT are also being investigated. A collection of several datasets pertaining to various control processes that were gleaned from various research articles has also been presented. Researchers working on PV-based MPPT and those working in the sectors of renewable energy production and environmentally sustainable development would be very interested in the findings of this review study.

Publisher

Hindawi Limited

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