Repositorio UFT :: Examinando por Materia "05 - Producción, distribución y utilización racional de la energía"

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

Mostrando 1 - 20 de 26

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.
Análisis de viabilidad para implementar las plataformas X1 Wind para brindar suministro energético a la comuna de Chonchi, Región de Los Lagos, Chile
(Universidad Finis Terrae (Chile) Facultad de Ingeniería, 2025) Oliviera Parra, María Ignacia; Herrera Garrido, Francisco prof. guía
La presente investigación evalúa la viabilidad técnica, económica y ambiental de implementar las plataformas eólicas flotantes de la empresa X1 WIND en la comuna de Chonchi, Región de Los Lagos, Chile. Esta zona presenta un alto índice de viviendas sin acceso a energía eléctrica, lo que se agrava por su geografía insular y dispersión territorial. Ante ello, se propone el uso de tecnología offshore flotante como solución viable para suministrar energía limpia y sustentable. Se realiza un análisis del recurso eólico basado en datos históricos de la estación meteorológica de Mocopulli, abarcando cinco años de registro entre 2019 y 2023. A partir de estos datos se determina un factor de planta promedio de 77,26%, calculado en base a la información de velocidad del viento registrada en dicho periodo (Dirección Meteorológica de Chile, 2024). Este valor permite estimar la Producción Anual de Energía (AEP) y dimensionar la cantidad de plataformas necesaria. Se consideran además aspectos técnicos como el diseño de anclaje tipo TLP y la orientación pasiva del sistema PivotBuoy, propios del prototipo X30 de X1 WIND. Desde el punto de vista económico, se estiman los costos CAPEX y OPEX a partir de valores referenciales, obteniendo un Costo Nivelado de Energía (LCOE) de 50,41 CLP/kWh, lo que lo posiciona como una opción competitiva frente a otras fuentes renovables. Finalmente, se proponen posibles ubicaciones para la subestación eléctrica y se evalúan los impactos ambientales y sociales de la intervención. Los resultados sugieren que el proyecto es técnicamente factible y económicamente atractivo, con oportunidades reales de mejorar la cobertura energética en sectores vulnerables.
Chapter 12: Demand side energy management algorithms integrated with the IoT framework in the PV smart grid system
(Academic Press, 2024-01-01) Rao, Challa Krishna
The smart grid revolution in the electric power sector will play a major role in the future. In the electric power system, the combination of new technology and communication infrastructure makes the grid smarter. To incorporate intelligence into the grid, many technological challenges must be solved, including those posed by energy storage systems, the integration of renewable sources, communication, protection, control, and demand-side management with customer involvement. Considering the rising need for electricity, one of the primary operational difficulties in the power system is balancing power generation to the constantly shifting load. Under the smart grid, utilities have realized that through demand side management and different demand response (DR) efforts, customer participation may be efficiently used for this balancing mechanism. The two-way communication between supply and demand can be successfully implemented with the help of smart grid intervention. Customers participate in DR schemes by actively reducing or shifting loads from peak to nonpeak hours concerning the pricing scheme. Therefore, it is essential to develop new demand response strategies for the smart grid, taking into consideration all features of the utility provider and the customers.
Chapter 8: Impacts of energy storage system on PV prosumer based on household load profiles
(Taylor & Francis Group, 2024-09) Srikanth, Bevara
The development of renewable energy generation in power grids has reduced greenhouse emissions due to fossil fuels. Renewable energy sources take part in electricity generation, which affects the economy, environment, national security, and human health. Photovoltaic generating units have increased dramatically worldwide. Even high-generation PV could not meet high demands in the dawn and dusk as it could not produce power regularly. A duck curve always forms with the demand dip in the midday period. This leads to the curtailment of PV power, which in turn affects the environmental and economic advantages of renewable sources. To ensure dependability and stability, most hybrid systems still need a traditional generator or a connection to the main grid. Energy Storage Systems (ESS) are useful in this regard because they encourage the use of renewable energy from the charge and discharge cycles of power with respect to all time horizons. In recent years, the PV consumer market with BESS (battery energy storage systems) and super capacitors has expanded greatly, which has filled the gap between household load and PV power profiles. This chapter highlights the available combinations of storage systems and methodologies for the enhancement of PV prosumer profitability.
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.
Energy homeostasis management strategy for building rooftop nanogrids, considering the thermal model and a HVAC unit installed
(Elsevier, 2022-02-04) Yanine, Fernando
This paper presents a case study on power control and energy management for a 60 apartments’ residential building with solar generation and energy storage tied to the grid in Santiago, Chile. A new energy management algorithm based on energy homeostasis is designed for a small electro thermal generation system (nanogrid), with smart metering. The test bed employs supervisory control with energy management that regulates the temperature inside a large room by the action of an HVAC (Heating/Ventilating/Air Conditioning) unit. The main objective of supervisory control is to allow temperature comfort for residents while evaluating the decrease in energy cost. The study considers a room with rooftop grid-tie nanogrid with a photovoltaic and wind turbine generation plant, working in parallel. It also has an external weather station that allows predictive analysis and control of the temperature inside the abode. The electrical system can be disconnected from the local network, working independently (islanding) and with voltage regulation executed by the photovoltaic generation system. Additionally, the system has a battery bank that allows the energy management by means of the supervisory control system. Under this scenario, a set of coordination and supervisory control strategies, adapted for the needs defined in the energy management program and considering the infrastructure conditions of the network and the abode, are applied with the aim of efficiently managing the supply and consumption of energy, considering Electricity Distribution Net Billing Laws 20.571 and 21.118 in Chile (https://www.bcn.cl/historiadelaley/historia-de-la-ley/vista-expandida/7596/), the electricity tariffs established by the distribution company and the option of incorporating an energy storage system and temperature control inside the room. The results show the advantage of the proposed tariffs and the overall energy homeostasis management strategy for the integration of distributed power generation and distribution within the smart grid transformation agenda in Chile. Este artículo presenta un caso de estudio sobre control de potencia y gestión de energía para un edificio residencial de 60 departamentos con generación solar y almacenamiento de energía conectado a la red en Santiago, Chile. Se diseña un nuevo algoritmo de gestión energética basado en la homeostasis energética para un pequeño sistema de generación electrotérmica (nanogrid), con medición inteligente. El banco de pruebas emplea un control de supervisión con administración de energía que regula la temperatura dentro de una habitación grande mediante la acción de una unidad HVAC (Calefacción/Ventilación/Aire acondicionado). El objetivo principal del control de supervisión es permitir el confort de la temperatura para los residentes mientras se evalúa la disminución del costo de la energía. El estudio considera una habitación con nanorredes conectadas a la red en la azotea con una planta de generación fotovoltaica y eólica, trabajando en paralelo. También cuenta con una estación meteorológica externa que permite el análisis predictivo y control de la temperatura al interior de la morada. El sistema eléctrico se puede desconectar de la red local, trabajando de forma independiente (islanding) y con regulación de tensión ejecutada por el sistema de generación fotovoltaica. Adicionalmente, el sistema cuenta con un banco de baterías que permite la gestión de la energía a través del sistema de control de supervisión. Bajo este escenario, se aplican un conjunto de estrategias de coordinación y control supervisor, adaptadas a las necesidades definidas en el programa de gestión energética y considerando las condiciones de infraestructura de la red y del domicilio, con el objetivo de gestionar eficientemente el suministro y consumo de energía, considerando las Leyes de Facturación Neta de Distribución Eléctrica 20.571 y 21.118 de Chile (https://www.bcn.cl/historiadelaley/historia-de-la-ley/vista-expandida/7596/), las tarifas eléctricas establecidas por la empresa distribuidora y la posibilidad de incorporar un sistema de almacenamiento de energía y control de temperatura en el interior de la estancia. Los resultados muestran la ventaja de las tarifas propuestas y la estrategia general de gestión de la homeostasis energética para la integración de la generación y distribución de energía distribuida dentro de la agenda de transformación de redes inteligentes en Chile.
Engineering sustainable energy systems: how reactive and predictive homeostatic control can prepare electric power systems for environmental challenges
(Elsevier, 2017) Yanine, Fernando
Nowadays electric power generation and distribution systems are being faced with a number of challenges and concerns which emanate not so much from a shortage of energy supply but from environmental and operational issues. They are required to respond to such challenges very rapidly and effectively so as to preserve stability and continuity of operations at any time, regardless of what may occur in the surroundings. This in fact is the true measure of what sustainable energy systems (SES) are all about, and homeostatic control (HC) of energy systems seeks just that: to enable energy systems to become highly efficient and effective very rapidly, by attaining a state of equilibrium between energy supply and energy expenditure in electric power systems (EPS) operation. To accomplish so they ought to imitate homeostasis mechanisms present in all living organisms. Ever since Cannon (1929, 1935) first introduced the concept, attention on homeostasis and its applications have been the sole patrimony of medicine and biology to find cures for diseases like diabetes and obesity. Nevertheless, homeostasis is rather an engineering concept in its very essence - even more so than in the natural sciences - and its application in the design and engineering of sustainable hybrid energy systems (SHES) is a reality. In this paper we present the groundwork that supports the theoretical model underlining the engineering of homeostasis in SHES. Homeostasis mechanisms are present in all living organisms, and thus are also applicable to EPS in order to enable and maintain a sustainable performance when EPS are linked to energy efficiency (EE) and thriftiness. In doing so, both reactive and predictive homeostasis play a substantive role in the engineering of such mechanisms. Reactive homeostasis (RH) is an immediate response of the SES to a homeostatic challenge such as energy deprivation, energy shortage or imbalance. RH entails feedback mechanisms that allow for reactive compensation, reestablishing homeostasis or efficient equilibrium in the system. Predictive homeostasis (PH), on the other hand, is a proactive mechanism which anticipates the events that are likely to occur, sending the right signals to the central controller, enabling SES to respond early and proactively to environmental challenges and concerns. The paper explores both concepts based on previous work in order to advance the research in the field of HC applied to electric power systems.
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.
Estudio de factibilidad para producción de energía mediante una red de aerogeneradores ubicados a lo largo del metro de Santiago
(Universidad Finis Terrae (Chile) Facultad de Ingeniería, 2025) López Varas, Ariel Andrés; Rozas, Sergio prof. guía
La energía eólica transforma el movimiento generado por el viento en energía eléctrica, es una alternativa renovable y limpia que cada día va creciendo más en todos sus ámbitos. Este trabajo busca determinar la viabilidad de generación de energía con aerogeneradores en distintas áreas del metro de Santiago, para aprovechar las corrientes de aire que se encuentran presentes en ella. Para poder realizar esto se debieron realizar distintas actividades, tanto de investigación, como mediciones y cálculos, para poder determinar por ejemplo las estaciones en las cuales se ubicarían los aerogeneradores, las distintas velocidades de viento, la cantidad de energía que se podría llegar a producir y los costos/beneficios de esta misma. El proyecto tiene dos etapas, la primera que enfatiza más el ámbito económico, es decir los beneficios monetarios que entregaría la energía producida al metro de Santiago, y la segunda etapa que se enfoca en el ámbito estratégico, es decir los beneficios que el proyecto le entregaría a los ciudadanos que utilizan este medio de transporte en el día a día.
Factibilidad técnico-económica de la producción de hidróxido de litio a pequeña escala a partir de salmueras
(Universidad Finis Terrae (Chile) Facultad de Ingeniería, 2019) Velásquez Carrasco, Catalina; Cabrera Álvarez, Víctor Benigno prof. guía
La electrificación de nuestro mundo está impulsando un fuerte aumento en la demanda de litio y sobre todo de hidróxido de litio, ya que es una materia prima vital para la acumulación energía en baterías de ión de litio. Hoy en día, aproximadamente el 60% de la producción mundial de compuestos de litio se extrae de salmueras, una práctica que evapora el agua, en promedio un millón de litros por tonelada de carbonato de litio equivalente producida. Debido a eso, esta investigación presenta un nuevo método para producir hidróxido de litio directamente a partir de salmueras, basado en la electrólisis, en el desierto de Atacama, Chile, enfocado en una minera a pequeña escala. Esta región presenta condiciones particulares de clima desértico donde el agua es escasa y para ayudar a resolver este problema del proceso de producción convencional, se planteó un proceso modificado, con un consumo eficiente de agua, para mejorar la sostenibilidad ambiental de la planta de producción. En este se analizó en términos generales la factibilidad técnico – económica de implementar esta nueva metodología y se encontró que el consumo de agua por kilogramo de producto se modificó de un millón de litros de agua[46] por tonelada de carbonato de litio equivalente producido a 2596 litros y el costo fijo del proceso se estima en aproximadamente 3 dólares por kilogramo. Finalmente, se puede decir que los resultados presentados pueden considerarse como pautas para abordar la optimización del proceso industrial para obtener el LiOH.
Forecasting Electric Power Generation in a Photovoltaic Power Systems for Smart Energy Management
(Institute of Electrical and Electronics Engineers (IEEE), 2022-08-25) Rao, Challa Krishna
Solar electricity is generated using photovoltaic (PV) systems all over the world. Solar power sources are irregular in nature since PV system output power is intermittent and highly dependent on environmental conditions. Irradiance, humidity, PV surface temperature, and wind speed are only a few of these variables. The uncertainty in photovoltaic generating, it's crucial to plan ahead for solar power generation. Solar power forecasting is required for electric grid supply and demand planning. Because solar power generation is weather-dependent and unregulated, this forecast is complicated and difficult. Selective developed to this goal. Traditional approaches such as statistics, autoregressive moving average, regression, and others were used to forecast PV power before the widespread usage variables are assessed for prediction models based on Artificial Neural Networks (ANN) and regression models. Several PV forecasting algorithms have been of machine learning technologies. Artificial Neural Networks, Support Vector Machines, and hybrid techniques have grown popular as a result of recent advances in machine learning methodologies and access to huge data. This study examines the impacts of numerous environmental conditions on PV system output, as well as the working principle and application of various PV forecasting approaches, in order to better comprehend the insights of PV prediction. Furthermore, the important parameters influencing PV generation are calculated using real-time data.
Funcionamiento y comercialización del mercado eléctrico chileno y su proyección a futuro
(Universidad Finis Terrae (Chile) Facultad de Derecho, 2023) Lagos Mac-Pherson, Frany Liliana; Irarrázaval Armendáriz, Francisco, prof. guía
La ley General de Servicios Eléctricos (LGSE) de 1982, estableció profundos cambios en materia energética, dando paso a un mercado más competitivo, con un esquema descentralizado y participación de particulares. Se reconocieron tres segmentos claramente identificables: Generación, Transmisión y Distribución de energía. Generación respondió sin problemas a la nueva estructura de libre mercado por ser un segmento naturalmente competitivo, sin embargo, Transmisión y Distribución, por su carácter de monopolios naturales, quedaron sujetos a un modelo de regulación de precios. Esto se ha querido revertir a través del tiempo, con la promulgación de diversas reformas en la materia, permitiendo así la introducción de nuevos actores y tecnologías, así como la apertura y factibilidad para la generación de energías limpias. El proyecto de Portabilidad Eléctrica, que duerme en el congreso, es el último intento de reforma y modernización en materia de Distribución, abriendo la posibilidad hacia la comercialización y rebaja de precios.
Grid-tied distributed generation systems to sustain the smart grid transformation: tariff analysis and generation sharing
(MDPI, 2020) Yanine, Fernando
In this paper a novel model is being proposed and considered by ENEL—the largest electric utility in Chile—and analyzed thoroughly, whereby electric power control and energy management for a 60-apartments’ residential building is presented as an example of the utility’s green energy program, part of its Smart Grid Transformation plan to install grid-tied distributed generation (DG) systems, namely microgrids, with solar generation and energy storage in Santiago, Chile. The particular tariffs scheme analysis shown is part of the overall projected tentative benefits of adopting the new scheme, which will require the utility’s customers to adapt their consumption behavior to the limited supply of renewable energy by changing energy consumption habits and schedules in a way that maximizes the capacity and efficiency of the grid-tied microgrid with energy storage. The change in behavior entails rescheduling power consumption to hours where the energy supply capacity in the DG system is higher and price is lower as well as curtailing their power needs in certain hourly blocks so as to maximize DG system’s efficiency and supply capacity. Nevertheless, the latter presents a problem under the perspective of ENEL’s renewable energy sources (RES) integration plan with the electric utility’s grid supply, which, up until now and due to current electric tariffs law, has not had a clear solution. Under said scenario, a set of strategies based on energy homeostasis principles for the coordination and control of the electricity supply versus customers’ demand has been devised and tested. These strategies which consider various scenarios to conform to grid flexibility requirements by ENEL, have been adapted for the specific needs of these types of customers while considering the particular infrastructure of the network. Thus, the microgrid adjusts itself to the grid in order to complement the grid supply while seeking to maximize green supply capacity and operational efficiency, wherein the different energy users and their energy consumption profiles play a crucial role as “active loads”, being able to respond and adapt to the needs of the grid-connected microgrid while enjoying economic benefits. Simulation results are presented under different tariff options, system’s capacity and energy storage alternatives, in order to ompare the proposed strategies with the actual case of traditional grid’s electricity distribution service, where no green energy is present. The results show the advantage of the proposed tariffs scheme, along with power control and energy management strategies for the integration of distributed power generation within ENEL’s Smart Grid Transformation in Chile.
Homeostaticity of energy systems: How to engineer grid flexibility and why should electric utilities care
(Faculty of Engineering and Natural Sciences, 2019) Yanine, Fernando
Today’s power generation and distribution industry is being faced with a number of issues, from violent weather phenomena to earthquakes, fires and landslides; including acts of arson, terrorism and vandalism, all of which pose serious concerns for the sustainability of the distribution and supply of electricity. Electric utilities like ENEL are cognizant of this fact and know they must take action. Moreover, they are required by law to be prepared and act proactively to prevent service disruption, by responding to such challenges rapidly and effectively so as to preserve stability and continuity of operation. Homeostaticity of energy systems seeks just that: to bring about a rapid, effective and efficient state of equilibrium between energy supply and expenditure at all times, whatever the circumstances, to preserve stability of systems operation. The paper presents a prescriptive energy homeostaticity model being considered by ENEL as a means to further the incorporation of renewables in the electricity generation and distribution industry. The aim is to enhance control and energy management systems in distributed generation installations tied to the grid for urban and rural communities, in order to complement and diversify their electric power distribution services. The theoretical groundwork underlying the subject as well as other relevant contextual factors are also discussed and simulation results are presented under different tariff scenarios, and energy storage alternatives, in order to compare the proposed model with the actual case. Energy storage (ES) is found to be of paramount importance in the overall analysis of the results as it enhances and reinforces thriftiness on energy consumption.
Impacto del costo nivelado de energía (LCOE) en la comparación de invesores de cadena y central en una planta fotovoltáica
(Universidad Finis Terrae (Chile) Facultad de Ingeniería, 2025) Ramirez Cerna, César Sebastián; Yanine, Fernando prof. guía
La creciente necesidad de diversificar la matriz energética y disminuir la dependencia de combustibles fósiles ha impulsado el desarrollo de proyectos de generación renovable en Chile, destacando especialmente la energía solar fotovoltaica por su potencial técnico y económico. En este contexto, el presente estudio busca analizar el desempeño técnico-económico de dos configuraciones de inversores: central e inversores de cadena (también conocidos como inversores string), en una planta fotovoltaica de 9 MW ubicada en la Región del Maule. La problemática central radica en que, si bien ambas tecnologías son ampliamente utilizadas en sistemas de gran escala, existe escasa evidencia comparativa local sobre su comportamiento en condiciones reales de operación. Dado que la elección del tipo de inversor incide directamente en la eficiencia energética, los costos operacionales y la viabilidad económica del proyecto, se vuelve necesario evaluar cuál configuración resulta más conveniente para optimizar la rentabilidad. Para abordar este objetivo, se implementa una metodología mixta que integra simulaciones energéticas con el software PVsyst y el análisis de datos reales obtenidos desde el sistema SCADA de la planta. Se compara la producción estimada y real de cada tipo de inversor, y posteriormente se calcula el Costo Nivelado de Energía (LCOE), incorporando costos de inversión (CAPEX), operación y mantenimiento (OPEX). Los resultados evidencian que los inversores de cadena presentan una mejor eficiencia energética y menor pérdida frente a condiciones variables, mientras que los inversores centrales ofrecen una menor inversión inicial. En términos económicos, el LCOE de los inversores de cadena resultan levemente inferior al de los centrales bajo condiciones simuladas, aunque las diferencias se reducen bajo condiciones reales. Se concluye que la tecnología de cadena representa una alternativa más competitiva en escenarios donde se priorizan eficiencia y resiliencia operativa, aportando evidencia relevante para la toma de decisiones en proyectos solares en Chile.
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.

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

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