Repositorio UFT :: Examinando por Autor "Yanine, Fernando"

Examinando por Autor "Yanine, Fernando"

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A systematic review of recent developments in IoT-based demand side management for PV power generation
(De Gruyter, 2024-06-21) Rao, Challa Krishna; Sahoo, Sarat Kumar; Yanine, Fernando
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.
An IoT-based intelligent smart energy monitoring system for solar PV power generation
(De Gruyter Mouton, 2023-09-15) Rao, Challa Krishna; Sahoo, Sarat Kumar; Yanine, Fernando
As the world’s attention turns to cleaner, more dependable, and sustainable resources, the renewable energy sector is rising quickly. The decline in world energy use and climate change are the two most significant factors nowadays. PV forecasting was essential to enhancing the efficiency of the real-time control system and preventing any undesirable effects. The smart energy management systems of distributed energy resources, the forecasting model of irradiation received from the sun, and therefore PV energy production might mitigate the impact of uncertainty on PV energy generation, improve system dependability, and increase the incursion level of solar power generation. Smart sensors and Internet of Things technologies are essential for monitoring and controlling applications in a broad range of fields. As a result, solar power generation forecasting was essential for microgrid stability and security, as well as solar photovoltaic integration in a strategic approach. This paper examines how to use IoT, a solar photovoltaic system being monitored, and shows the proposed monitoring system is a potentially viable option for smart remote and in-person monitoring of a solar PV system.
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; Sahoo, Sarat Kumar; Yanine, Fernando
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 14: Roles and Challenges of 6G for the Human–Computer Interface
(Wiley, 2024-12-02) Priyabrata, Dash; Akankshya, Patnaik; Sahoo, Sarat Kumar; Yanine, Fernando
Needless to say, technology flies like time. Within a relatively short span of about 30 years, we have been able to visualize the advent of 2G, 3G, 4G, and, finally today, the whole world is fondly using 5G. It is without a doubt that the 5G network is successfully satisfying customers’ needs, but dealing with the flow of excessive data and massive network densification all around the world has made things difficult for telecommunications and industry digitalization. Thus, the evolution of wireless communication beyond 5G (B5G) or 6G may not only be necessary for future industry growth, encompassing massive digital transformation of several industries, but also certainly plausible. In this context, we will show, for example, that 6G is expected to deal with multi-sensory technologies in order to create new ways for people to interact with each other and with other technologies, in an effort to be updated with the upcoming global sustainability and fairness trends. 6G is believed to be a self-content application of Artificial Intelligence. Thus, as researchers, it is the right time to investigate and discover upcoming 6G technology deliverables, especially for the human–computer interface (HCI). HCI is a multidisciplinary topic of investigation and also a broad term that connects Computer Science, Cognitive Science, and Human Factors Engineering. HCI no longer focuses on the behavior of individual or generic users, but it broadens its base towards organizational and social computing. This chapter aims to clarify the proposed road map that lies ahead, which identifies certain roles of 6G technology for the human–computer interface. It also explores its role in current businesses and organizations. The chapter also unearths key tenets of the literature on the subject as well as helps researchers to discover both identified and unidentified challenges of 6G for HCI. The chapter also intends to identify potential technology challenges that may lie ahead and provide a solution for many upcoming problems and open a new horizon for imminent research on the matter, in order to advance knowledge in these areas. The main purpose of this chapter is to analyze and deliberate the various potentials and flaws of 6G for human–computer interfaces.
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; Sahoo, Sarat Kumar; Yanine, Fernando
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.
Design and development of grid connected home automation system for prosumers
(Institute of Electrical and Electronics Engineers (IEEE), 2023-03-23) Patro, Swati P.; Sahoo, Sarat Kumar; Thanarak, Paprita; Yanine, Fernando
Home automation system extend convenience and sophisticated to operate electronic product with in the household. Home automation can be a solution to automating functions like monitoring, controlling etcetera in the home. This paper describes the drives, restraints, opportunities and challenges pertaining to the home automation system market. The grid solar power system is connected to the utility grid where solar power is generated. The power generated if in excess send back to utility grid. Hence the consumer gets compensation as the extra power sent back to the utility grid. Whenever the sunlight, electricity is generated by solar cell, the inverter connected to grid convert the dc power into ac power. The electricity produced is routed to the grid from, where it used to run the various appliances such as air conditioners, washing machine, refrigerator, geyser, induction cooker, pump etc. The excess power at every instant is transmitted to the ground without grid connection and if solar power system is synchronized with the utility grid then return to the grid. It will also determine the feasibility of reducing green gas emission by the use of grid tied PV power system.
Design of an EEG analytical methodology for the analysis and interpretation of cerebral connectivity signals
(Elsevier, 2022-02-20) Córdova, Felisa M.; Cifuentes, Hugo F.; Díaz, Hernán A.; Yanine, Fernando; Pereira, Robertino
The objective of this study is to design an Electroencephalographic (EEG) analytic methodology that allows to develop a variety of analysis and interpretations of brain signals. The initial phase considers the acquisition and filtering of EEG signals, the division into bands in data ranges, and the storage of EEG signals in a cloud data base. Then, an analytical phase considering descriptive, predictive and prescriptive analysis is accomplished. A sequence of analytic intermediate processing steps is done in order to render a graphic visualization of significant correlations between pairs of EEG channels. Pearson correlation is utilized to detect synchronic connectivity through the brain areas. Time series in nearly instantaneous time lapses are treated by using Hilbert Huang Transform. An experimental design by submitting a set of students to an abbreviated version Raven visual test is made providing results in correlation maps of cerebral connectivity
Design of smart socket for monitoring of IoT-based intelligent smart energy management system
(Springer, 2021) Rao, Challa Krishna; Kumar Sahoo, Sarat; Balamurugan, M.; Yanine, Fernando
Smart socket is designed for collecting and sending the data from the various nodes in one field to other fields. Smart socket consists of the Arduino_Uno, XBee, sensors, gateway, computer, USB, and IDE. This works emphasis on design and development of smart socket with wireless capability, this can be used to collect the data from each electrical device by using sensors. An XBee transmitter and receiver node are used for data communication in wireless networks. Real-time data gathered at the central node can be used to prioritize and schedule the appliances. Then, the system analyzes the data to generate control commands to turn the devices attached to the smart socket on or off. This paper presents the operation and functions of smart socket in different sensor network topologies. The results show that the proposed smart socket can correctly read the data from the various nodes and also send it to different nodes of different parameters.
Designing an intelligent smart energy monitoring system for optimizing the utilization of PV energy
(Springer Nature, 2024-11-01) Rao, Challa Krishna; Sahoo, Sarat Kumar; Yanine, Fernando
Consumers in both residential and commercial settings are increasingly interested in reducing their energy consumption, influenced by feed-in tariffs for renewable resources and the recent surge in electricity rates. This study introduces a central control system and a smart power plug utilizing the XBee communication protocol to effectively manage energy usage. Smart energy management systems are employed to measure and optimize power consumption at the consumer premises level. The primary objective of this paper is the design and development of wireless smart plugs capable of assessing various power characteristics and collecting real-time data on individual consumer appliances' power usage. The SEMS setup establishes a Consumer Area Network through an XBee transmitter and receiver node, enabling real-time data collection at the central node for scheduling and prioritizing appliances. Utilizing the SEMS setup, consumer appliance datasets are generated and additional datasets aid in load disaggregation. The system configuration enables wireless data transfer from smart outlets to a central controller. Control instructions derived from data analysis are then used by the system to turn connected devices to the smart plug on or off. Test results indicate that the proposed smart plug accurately assesses power consumption up to eighteen meters away without compromising data integrity. The central controller, guided by a planned user program code, effectively manages multiple plugs based on the test findings. The Smart Energy Management algorithm suggests that employing smart plugs as load controllers results in a significant decrease in energy consumption (0.811 kW min or 0.0134 kWh) when accompanied by the appropriate scheduling algorithm. This technology holds potential in a comprehensive smart energy management system. The data's insights highlight the superiority of the proposed approach compared to current standard practices.
Diagnosing grid's service quality issues: the virtual microgrid and the digitization and innovations in the power distribution grid
(Elsevier, 2024-08-23) Cordova, Felisa; Yanine, Fernando; Carrasco, Sergio; Rother, Hans; Duarte, Vanessa
Power quality issues from small and medium-sized grid-integrated solar photovoltaic systems (PMGD), whose plant capacity is less than or equal to 9 MW, challenge electric power distribution companies like ENEL Distribución S.A. in Chile. To tackle these challenges, leveraging rapidly configurable, scalable, and easily deployable distributed energy resources (DER) through a virtual power plant (VPP) is crucial. This paper introduces a "virtual microgrid," a specific VPP design and functional specification that swiftly diagnoses and resolves power quality issues. Virtual power plants use renewable energy sources, energy storage, and smart energy management to provide ancillary services to the grid. With the expanding PMGD market in Chile and globally, there is an urgent need for deployable DER to energize feeder sub-sections during reliability events and create grid pathways between DER and loads. Thus, DER are essential for enhancing grid flexibility, reliability, and maintaining the stability and integrity of electric supply quality standards. VPPs can reduce high costs associated with utility grid power capacity deficiencies in areas with unstable power supply, enhancing resilience and flexibility without compromising system stability. This study presents a novel approach—currently at the conceptual development stage—for diagnosing service quality issues related to grid supply through the rapid deployment of a configurable and fully scalable virtual microgrid. This solution is particularly relevant for zones in Santiago, Chile, where ENEL Chile faces challenges due to the increasing presence of PMGD—independent solar farms injecting all their production into the grid for profit, as permitted by current Chilean electric law (N°88/2019 of Ministry of Energy). Such practices negatively impact grid service quality standards, which can be mitigated through the deployment of virtual microgrids. The concept of a "virtual microgrid" emphasizes rapid configurability, scalability, and ease of deployment, tailored to address specific grid quality issues. Unlike previous efforts, this approach focuses on seamlessly integrating DER with existing grid infrastructure to quickly address and mitigate power quality issues caused by PMGD.
Editorial: Recent advances in renewable energy automation and energy forecasting
(Frontiers Media S.A., 2023-05-10) Sahoo, Sarat Kumar; Yanine, Fernando; Kulkarni, Vikram; Kalam, Akhtar
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; Sanchez-Squella, Antonio; Barrueto, Aldo; Sahoo, Sarat Kumar; Parejo, Antonio; Cordova, Felisa M.
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; Sanchez-Squella, Antonio; Barrueto, Aldo; Cordova, Felisa M.; Kumar Sahoo, Sarat
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.
A fresh look at an old problem: saturation in the retail market and how it affects both retailers and consumers
(Indian Society for Education and Environment, 2019-05-28) Yanine, Fernando; Cordova, Felisa M.; Valenzuela, Lionel; Isla, Pablo
Objective: Traditional saturation analysis on competitive location decision science focuses on diminishing returns for incumbents and newcomers in a specific spatial location pertaining to commercial retail potential past a certain point of market saturation. Methods/Findings: This study looks at this problem but employs a different approach to the subject altogether, wherein saturation is no longer a variable affecting only retailers but one that affects both: the marginal utility of consumers and the revenue of retailers albeit differently. A new mathematical model is proposed based on selected papers, contributing new insight into an already widely discussed subject. Application: Analysis shows that it is important for competitive location decision-making to address saturation from both sides of the overall competitive location decision issue, not just from the retailers’ standpoint.
Grid-tied distributed generation systems to sustain the smart grid transformation: tariff analysis and generation sharing
(MDPI, 2020) Yanine, Fernando; Sánchez-Squella, Antonio; Barrueto, Aldo; Parejo, Antonio; Cordova, Felisa; Rother, Hans
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; Sanchez-Squella, Antonio; Barrueto, Aldo; Kumar Sahoo, Sarat; Parejo, Antonio; Shah, Dhruv; Cordova, Felisa
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.
Intelligent power management system for optimizing load strategies in renewable generation
(Springer Nature, 2024-08-29) Rao, Challa Krishna; Sahoo, Sarat Kumar; Yanine, Fernando
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
(Elsevier, 2024-08-08) Rao, Challa Krishna; Sahoo, Sarat Kumar; Yanine, Fernando
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.
Low carbon energy thecnologies in sustainable energy systems
(Elsevier, 2021) Yanine, Fernando; Sanchez-Squella, Antonio; Barrueto, Aldo; Kumar Sahoo, Sarat; Cordova, Felisa; Shah, Dhruv; Parejo, Antonio; Rother, Hans
Low Carbon Energy Technologies for Sustainable Energy Systems examines, investigates, and integrates current research aimed at operationalizing low carbon technologies within complex transitioning energy economies. Scholarly research has traditionally focused on the technical aspects of exploitation, R&D, operation, infrastructure, and decommissioning, while approaches which can realistically inform their reception and scale-up across real societies and real markets are piecemeal and isolated in separate literatures. Addressing both the technical foundations of each technology together with the sociotechnical ways in which they are spread in markets and societies, this work integrates the technoeconomic assessment of low carbon technologies with direct discussion on legislative and regulatory policies in energy markets. Chapters address issues, such as social acceptance, consumer awareness, environmental valuation systems, and the circular economy, as low carbon technologies expand into energy systems sustainability, sensitivity, and stability. This collective research work is relevant to both researchers and practitioners working in sustainable energy systems. The combination of these features makes it a timely book that is useful and attractive to university students, researchers, academia, and public or private energy policy makers.
A PI + sliding-mode controller based on the discontinuous conduction mode for an unidirectional buck–boost converter with electric vehicle applications
(MDPI, 2021-10-18) Gonzalez, Ileana; Sanchez, Antonio; Langarica-Cordoba, Diego; Yanine, Fernando; Ramirez, Victor
This paper solves the buck–boost converter operation problem in the discontinuous conduction mode and the feeding a DC bus of a combined battery/solar-powered electric vehicle grid. Since the sun’s radiation has a very important effect on the performance of photovoltaic solar modules due to its continuous variation, the main task of the system under study is the regulation of the output voltage from an MPPT system located at the output of the panels in order to obtain a DC bus voltage that is fixed to 24 V. This is ensured via a double-loop scheme, where the current inner loop relies on sliding-mode control; meanwhile, the outer voltage loop considers a proportional–integral action. Additionally, the current loop implements an adaptive hysteresis logic in order to operate at a fixed frequency. The closed-loop system’s performance is checked via numerical results with respect to step changes in the load, input voltage, and output voltage reference variations.

Examinando por Autor "Yanine, Fernando"

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