Artículos de Revistas

URI permanente para esta colección

https://repositorio.uft.cl/handle/20.500.12254/2436

Examinar

Mostrando 1 - 9 de 9

A review of IoT-based smart energy solutions for photovoltaic systems
(Springer Nature, 2025-08-11) Rao, Challa Krishna
Harnessing renewable energy stands out as the most reliable and widely accepted method to address the surging global energy needs. In particular, advancing solar energy systems requires focused efforts in operational upkeep and practical deployment. To optimize solar output, Internet of Things enabled monitoring frameworks have been introduced, enabling data collection and analysis for performance evaluation and consistent energy delivery. A core obstacle in managing energy from the consumer side lies in leveraging green power sources efficiently while keeping expenses in check and avoiding excessive energy usage. As a result, thoughtful planning is essential when integrating alternative energy technologies. Smart energy systems critically optimize consumption amid growing grid reliance. Cloud computing resolves challenges and unlocks opportunities in modern power networks. This work examines energy coordination tools' dual role in industrial operations and academic research, demonstrating their synergistic value in advancing energy efficiency and grid resilience through technological and theoretical innovation. The investigation covers comprehensive evaluations of IoT’s role in solar power generation. Emerging IoT developments open new pathways for scholarly exploration, including the formulation of evaluation standards and the pursuit of novel improvement strategies. Furthermore, deeper investigations into intelligent energy systems within smart infrastructures are increasingly necessary. Such efforts are critical for enriching the knowledge base of IoT-driven solutions and promoting steady technological progress. Articulo WoS y SCOPUS Q2 El aprovechamiento de las energías renovables destaca como el método más fiable y ampliamente aceptado para hacer frente al creciente demanda energética mundial. En particular, el avance de los sistemas de energía solar requiere esfuerzos específicos en el mantenimiento operativo y la implementación práctica. Para optimizar la producción solar, se han introducido marcos de supervisión habilitados para el Internet de las cosas, que permiten la recopilación y el análisis de datos para la evaluación del rendimiento y el suministro constante de energía. Uno de los principales obstáculos en la gestión de la energía desde el lado del consumidor radica en aprovechar las fuentes de energía verde de manera eficiente, al tiempo que se controlan los gastos y se evita el uso excesivo de energía. Por lo tanto, es esencial una planificación cuidadosa a la hora de integrar tecnologías de energía alternativa. Los sistemas energéticos inteligentes optimizan de manera crítica el consumo en medio de una creciente dependencia de la red eléctrica. La computación en la nube resuelve los retos y abre nuevas oportunidades en las redes eléctricas modernas. Este trabajo examina la doble función de las herramientas de coordinación energética en las operaciones industriales y la investigación académica, demostrando su valor sinérgico en la promoción de la eficiencia energética y la resiliencia de la red eléctrica a través de la innovación tecnológica y teórica. La investigación abarca evaluaciones exhaustivas del papel del IoT en la generación de energía solar. Los nuevos avances en el IoT abren nuevas vías para la exploración académica, incluida la formulación de normas de evaluación y la búsqueda de nuevas estrategias de mejora. Además, cada vez es más necesario profundizar en la investigación de los sistemas energéticos inteligentes dentro de las infraestructuras inteligentes. Estos esfuerzos son fundamentales para enriquecer la base de conocimientos de las soluciones impulsadas por el IoT y promover un progreso tecnológico constante.
A review of IoT-based smart energy solutions for photovoltaic systems.
(Springer Nature, 2025-12-10) Rao, Challa Krishna
Harnessing renewable energy stands out as the most reliable and widely accepted method to address the surging global energy needs. In particular, advancing solar energy systems requires focused efforts in operational upkeep and practical deployment. To optimize solar output, Internet of Things enabled monitoring frameworks have been introduced, enabling data collection and analysis for performance evaluation and consistent energy delivery. A core obstacle in managing energy from the consumer side lies in leveraging green power sources efficiently while keeping expenses in check and avoiding excessive energy usage. As a result, thoughtful planning is essential when integrating alternative energy technologies. Smart energy systems critically optimize consumption amid growing grid reliance. Cloud computing resolves challenges and unlocks opportunities in modern power networks. This work examines energy coordination tools’ dual role in industrial operations and academic research, demonstrating their synergistic value in advancing energy efficiency and grid resilience through technological and theoretical innovation. The investigation covers comprehensive evaluations of IoT’s role in solar power generation. Emerging IoT developments open new pathways for scholarly exploration, including the formulation of evaluation standards and the pursuit of novel improvement strategies. Furthermore, deeper investigations into intelligent energy systems within smart infrastructures are increasingly necessary. Such efforts are critical for enriching the knowledge base of IoT-driven solutions and promoting steady technological progress.
A systematic review of recent developments in IoT-based demand side management for PV power generation
(De Gruyter, 2024-06-21) Rao, Challa Krishna
Demand-side management (DSM) with Internet of Things (IoT) integration has become a vital path for optimizing photovoltaic (PV) power generating systems. This systematic review synthesizes and evaluates the latest advancements in IoT-based DSM strategies applied to PV power generation. The review encompasses a comprehensive analysis of recent literature, focusing on the key elements of IoT implementation, data analytics, communication protocols, and control strategies in relation to solar energy DSM. The combined results show how IoT-driven solutions are changing and how they might improve PV power systems’ sustainability, dependability, and efficiency. The review also identifies gaps in current research and proposes potential avenues for future investigations, thereby contributing to the ongoing discourse on leveraging smart DSM in the solar energy domain using IoT technology.
Design and deployment of a novel decisive algorithm to enable real-time optimal load scheduling within an intelligent smart energy management system based on IoT
(Elsevier, 2024-12-01) Rao, Challa Krishna
Consumers routinely use electrical devices, leading to a disparity between consumer demand and the supply side a significant concern for the energy sector. Implementing demand-side energy management can enhance energy efficiency and mitigate substantial supply-side shortages. Current energy management practices focus on reducing power consumption during peak hours, enabling a decrease in overall electricity costs without sacrificing usage. To tackle the mentioned challenges and maintain system equilibrium, it is essential to develop a flexible and portable system. Introducing an intelligent energy management system could pre-empt power outages by implementing controlled partial load shedding based on consumer preferences. During a demand response event, the system adapts by imposing a maximum demand limit, considering various scenarios and adjusting appliance priorities. Experimental work, incorporating user comfort levels, sensor data, and usage times, is conducted using Smart Energy Management Systems (SEMS) integrated with cost-optimization algorithms.
Development of a smart cloud-based monitoring system for solar photovoltaic energy generation
(KeAi chinese roots global impact, 2025-04-01) Rao, Challa Krishna
The main controllers overseeing both solar panels and loads have all panels connected with sensors. The radiation striking the solar cell determines the power produced and real-time monitoring is crucial to evaluating the performance of a solar photovoltaic system. The emerging Internet of Things provides an opportunity to significantly enhance the monitoring of solar energy output and plant operations. To achieve this, a remote monitoring system is necessary, utilizing the Internet of Things to gather and transmit data. This study aims to utilize the Internet of the Things to monitor solar photovoltaic systems and assess their effectiveness. The monitoring system includes components such as a data gateway, data collection, and presentation for a cloud application. The collected data were stored in the cloud, enabling a visual representation of the sensed parameters. The system achieved a better accuracy rate, with an average transmission time of 53.01 s. The results indicate that the recommended monitoring system allowed users to observe current, voltage, and daylight, which could serve as a viable substitute for smart monitoring of solar energy output and plant operations.
Editorial: Recent advances in renewable energy automation and energy forecasting
(Frontiers Media S.A., 2023-05-10) Sahoo, Sarat Kumar
Renewable energy sources like solar, wind, and hydroelectric power are gaining popularity as we work towards a more sustainable future. However, their intermittent and often unpredictable nature, creates challenges for the energy industry in terms of being able to ensure continuous electric power generation over regular periods of time. Thus, accurate forecasting of renewable energy output is crucial for their reliable integration into the power grid. In this regard, automation and machine learning have made significant improvements in energy forecasting by enabling more precise predictions of energy output. Advanced algorithms and high-performance computing systems allow for better grid management and increased power generation systems’ efficiency. Automation is also being used for the operation and maintenance of renewable energy systems. Real-time monitoring and control systems enable a rapid response to changes in weather conditions, optimizing energy production. This editorial summarizes recent advancements in renewable energy automation and energy forecasting, which are critical areas for achieving a sustainable energy future. The Research Topic covers areas like machine learning-based energy forecasting, control and optimization of renewable energy systems, and the integration of renewable energy into microgrids as shown in Figure 1. Continued research and development in renewable energy automation and energy forecasting are essential for the transition towards a sustainable energy future.
Enhancing grid stability and sustainability through virtual power plants: A case study of Chile.
(Elsevier, 2026-07-17) Yanine, Fernando
The rapid growth of distributed solar photovoltaic (PV) generation in urban power networks has intensified challenges related to frequency stability, voltage regulation, and overall power quality, particularly in regions with high penetration of small- and medium-scale distributed generation (PMGD). This study evaluates the role of Virtual Power Plants (VPPs) as coordinated control mechanisms to mitigate these disturbances. A simulation-based framework is developed using representative operational data from ENEL Distribución Chile, combined with dynamic system modeling implemented in Python. Three operating scenarios are analyzed: (i) PMGD without VPP support, (ii) PMGD with integrated VPP coordination, and (iii) reduced PMGD capacity with and without VPP intervention. The analysis focuses on system-level dynamic response, including frequency, voltage, and phase behavior under high-generation conditions. Results demonstrate that VPP deployment significantly enhances grid stability, reducing frequency deviations from 0.5 Hz to 0.1 Hz and voltage fluctuations from 5% to 2%, while improving overall power quality metrics by approximately 80%. These findings confirm the effectiveness of coordinated VPP control in managing power imbalances and stabilizing renewable-rich distribution networks. The proposed approach provides a practical and scalable framework for integrating distributed renewable generation, offering insights for utilities and policymakers in Latin America and similar high-penetration contexts.
Intelligent power management system for optimizing load strategies in renewable generation
(Springer Nature, 2024-08-29) Rao, Challa Krishna
Effectively utilizing renewable energy sources while avoiding power consumption restrictions is the problem of demand-side energy management. The goal is to develop an intelligent system that can precisely estimate energy availability and plan ahead for the next day in order to overcome this obstacle. The Intelligent Smart Energy Management System (ISEMS) described in this work is designed to control energy usage in a smart grid environment where a significant quantity of renewable energy is being added. The proposed system evaluates various prediction models to achieve accurate energy forecasting with hourly and day-ahead planning. When compared to other prediction models, the Support Vector Machine (SVM) regression model based on Particle Swarm Optimization (PSO) seems to have better performance accuracy. Then, using the anticipated data, the experimental setup for ISEMS is shown, and its performance is evaluated in various configurations while considering features that are prioritized and user comfort. Furthermore, Internet of Things (IoT) integration is put into practice for monitoring at the user end.
IoT enabled intelligent energy management system employing advanced forecasting algorithms and load optimization strategies to enhance renewable energy generation
(KeAi chinese roots global impact, 2024-08-08) Rao, Challa Krishna
Effectively utilizing renewable energy sources while avoiding power consumption restrictions is the problem of demand-side energy management. The goal is to develop an intelligent system that can precisely estimate energy availability and plan ahead for the next day in order to overcome this obstacle. The Intelligent Smart Energy Management System (ISEMS) described in this work is designed to control energy usage in a smart grid environment where a significant quantity of renewable energy is being introduced. The proposed system evaluates various predictive models to achieve accurate energy forecasting with hourly and day-ahead planning. When compared to other predictive models, the Support Vector Machine (SVM) regression model based on Particle Swarm Optimization (PSO) seems to have better performance accuracy. Then, using the anticipated requirements, the experimental setup for ISEMS is shown, and its performance is evaluated in various configurations while considering features that are prioritized and associated with user comfort. Furthermore, Internet of Things (IoT) integration is put into practice for monitoring at the user end.

Examinar

Examinando Artículos de Revistas por Materia "05 - Producción, distribución y utilización racional de la energía"

Resultados por página

Opciones de ordenación