https://ph01.tci-thaijo.org/index.php/RAST <p>Welcome to the official website of the <strong>Journal of Renewable Energy and Smart Grid Technology (RAST).</strong></p> <p>The journal aims to publish articles about renewable energy and smart grid technology written by professors, scholars, and business practitioners. It encourages the exchange of information and discussions to promote widespread deployment and investment in these technologies. The journal seeks high-quality research articles for regular submission and also publishes reviews on important development areas, which may be submitted or invited by the editors.</p> <p>All papers in RAST undergo double-blind peer review by at least three reviewers from various outside institutions to ensure scientific quality.</p> <p><strong>Journal of Renewable Energy and Smart Grid Technology (RAST)<br /></strong><strong>Journal Abbreviation:</strong> J. Renew. Energy Smart Grid Technol.<br /><strong>Start Year: </strong>2018</p> <p><strong>ISSN: </strong><strong>2630-0036 (Electronic version)</strong><strong><br />Frequency: 2 Issues/Year (1) January-June (2) July-December</strong></p> <p><strong>Language: </strong>English</p> <p><strong>Editor-in-Chief</strong> : Nipon Ketjoy<br /><strong>ORCID</strong> : <a href="https://orcid.org/0000-0002-9324-0905" target="_blank" rel="noopener">https://orcid.org/0000-0002-9324-0905</a></p> <p><strong>Crossref Membership &amp; DOI assignment</strong><br />RAST is a member of Crossref, with a DOI prefix of 10.69650. The direct DOI link is https://doi.org/10.69650/rast. Starting from Vol. 19 (2024), all of our published articles are assigned a DOI and registered in Crossref. Additionally, RAST implements reference linking, ensuring that each article's references are verified and DOIs are added.<br /><img src="https://ph01.tci-thaijo.org/public/site/images/niponk/crossref-logo.png" alt="" width="184" height="100" /></p> School of Renewable Energy and Smart grid Technology (SGtech), Naresuan University en-US Journal of Renewable Energy and Smart Grid Technology 2586-8764 <p>All copyrights of the above manuscript, including rights to publish in any media, are transferred to the SGtech.</p> <p>The authors retain the following rights;</p> <p> 1. All proprietary rights other than copyright.</p> <p> 2. Re-use of all or part of the above manuscript in their work.</p> <p> 3. Reproduction of the above manuscript for author’s personal use or for company/institution use provided that</p> <p> (a) prior permission of SGtech is obtained,</p> <p> (b) the source and SGtech copyright notice are indicated, and</p> <p> (c) the copies are not offered for sale.</p> https://ph01.tci-thaijo.org/index.php/RAST/article/view/261215 <p>Nowadays, solar energy is gaining more popularity in the world due to its significant nature of being green and sustainable. Yet, many are concerned about power generation because its efficiency is low. So, by using advanced algorithms like MPPT, we can improve the efficiency of solar power generation through PV panels. The Perturb and Observe (P&amp;O) MPPT algorithm is one of the most commonly used techniques due to its simplicity and cost-effectiveness. However, its performance is affected by load variations and rapidly changing environmental conditions, leading to power losses. This paper analyzes the effectiveness of the P&amp;O MPPT algorithm for different load conditions and explores various modifications to enhance tracking accuracy. The integration of MPPT with power converters further improves system efficiency. Simulation and experimental results demonstrate the feasibility of implementing P&amp;O MPPT in real-world PV systems. Future advancements in adaptive MPPT strategies will be crucial in maximizing solar energy utilization.</p> Venkata Anjani Kumar G Sriramulu Naik Mudhavath Kotla Siva Koti Reddy Copyright (c) 2025 School of Renewable Energy and Smart Grid Technology (SGtech) https://creativecommons.org/licenses/by-nc-nd/4.0 2025-07-23 2025-07-23 20 2 61 69 10.69650/rast.2025.261215