https://revistas.utb.edu.co/tesea <p><em>Transactions on Energy Systems and Engineering Applications</em> publishes peer-reviewed articles reporting on research, development, and applications on energy systems covering all areas of engineering and applied mathematics. The journal editor will enforce standards and a review policy to ensure that papers of high technical quality are accepted. The journal is published by the Universidad Tecnológica de Bolívar.</p> <p><strong>ISSN:</strong> 2745-0120 (<em>Online</em>)</p> <p><a href="http://creativecommons.org/licenses/by/4.0/" rel="license"><img src="https://i.creativecommons.org/l/by/4.0/88x31.png" alt="Licencia Creative Commons" /></a></p> Universidad Tecnológica de Bolívar en-US Transactions on Energy Systems and Engineering Applications 2745-0120 <p>Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative <a href="https://creativecommons.org/licenses/by/4.0/">Commons Attribution 4.0 International License</a>, which allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.</p> https://revistas.utb.edu.co/tesea/article/view/602 <p>In the dynamic realm of Autonomous Mobile Robots (AMRs), ensuring smooth navigation among obstacles is critical, especially as they become increasingly integral to industries such as manufacturing and transportation. Recent advances have introduced several learning models to aid in obstacle avoidance, but many face computational challenges. This research introduces the Adaptive Stochastic Gradient Descent with Least Angle Regression (ASGD-LARS) algorithm, specifically designed to enhance the navigation of AMRs. By carefully considering obstacle orientations, it facilitates quicker decision-making for direction changes. When compared with well-established algorithms like KNN, XG Boost, Naive Bayes, and Logistic Regression, ASGD-LARS consistently performs better in terms of accuracy, computational efficiency, and reliability. This study lays the foundation for the deployment of smarter and more efficient AMRs across diverse industries.</p> Abhishek Thakur Subhranil Das Sudhansu Kumar Mishra Subrat Kumar Swain Copyright (c) 2025 Abhishek Thakur, Subhranil Das, Sudhansu Kumar Mishra, Subrat Kumar Swain https://creativecommons.org/licenses/by/4.0 2025-09-15 2025-09-15 6 2 1 26 10.32397/tesea.vol6.n2.602 https://revistas.utb.edu.co/tesea/article/view/648 <p>Microgrids are gaining momentum these days as they can generate the cleaner and affordable electrical energy through renewable energy sources. The renewable energy sources such as wind has enough potential however, its operation is restricted as wind speed highly varies over the period of the day and that is why diesel engine generation is a possible solution to overcome the wind challenges as well as to supply the uninterrupted electrical energy to the customers. This paper presents the design of various PID controllers to match the energy generation with load demand and hence to stabilize the operation of the microgrid for various operating conditions. The performance of the PID controllers is obtained through gains calculation, diverse error values and through dynamic responses of the microgrids obtained through diverse controllers. Further, this paper also shows the impact of diverse energy storage devices (ESD) with PID controllers for the microgrid, and it is observed that PIL-PID with redox flow battery outperform other controllers and ESDs and most suited for various working conditions of the microgrid.</p> Vikash Rameshar Gulshan Sharma Pitshou N. Bokoro Copyright (c) 2025 Vikash Rameshar, Gulshan Sharma, Pitshou N. Bokoro https://creativecommons.org/licenses/by/4.0 2025-09-16 2025-09-16 6 2 1 16 10.32397/tesea.vol6.n2.648