Artículos (Ingeniería de Sistemas y Automática)

URI permanente para esta colecciónhttps://hdl.handle.net/11441/11342

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Mostrando 1 - 20 de 518

A Multi-UAV Approach for Fast Inspection of Overhead Power Lines: From Route Planning to Field Operation
(Springer, 2025) Caballero Gómez, Álvaro; Román-Escorza, Francisco Javier; Maza Alcañiz, Iván; Ollero Baturone, Aníbal; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Union (UE); Universidad de Sevilla. TEP151: Robótica, Visión y Control
Overhead power lines are critical infrastructures to ensure a reliable energy supply, and failures in the grid can lead to significant service disruptions. Locating these faults quickly is crucial but often challenging, especially in hard-to-reach areas such as mountainous regions. This paper presents an integrated solution for the long-range visual inspection of overhead power lines in minimum time using teams of Unmanned Aerial Vehicles (UAVs). The solution, designed for effective field operation while meeting end-user requirements, comprises route planning, autonomous execution, and monitoring of the inspection mission. Concerning route planning, a capacitated min-max multi-depot vehicle routing problem has been formulated to compute feasible routes that cover the entire grid in minimum mission time. The method can be applied to heterogeneous multiUAV teams in terms of inspection speed and battery consumption, which helps maximise the utilisation of available robots. Moreover, the planning method is complemented by an accurate battery-consumption model based on energy principles that captures the effect of parameters often overlooked such as UAV mass, inspection speed, and weather conditions. The model has shown estimates with relative errors not exceeding 1.34% compared to real measurements. The proposed solution has been experimentally validated under real-world conditions, enabling the autonomous multi-UAV inspection of more than 10 kilometres of real power lines in 13 minutes, which represents a time reduction of up to 67.21% compared to the state of the art. The resulting videos enabled the identification of a simulated power outage and its exact location.
Standardized Evaluation of Counter-Drone Systems: Methods, Technologies, and Performance Metrics
(MDPI, 2025) De Cubber, Geert; Doroftei, Daniela; Petsioti, Paraskevi; Koniaris, Alexios; Brewczyński, Konrad; Życzkowski, M.; Maza Alcañiz, Iván; Ollero Baturone, Aníbal; Popa, Cristina; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Union. Internal Security Fund Police; Universidad de Sevilla. TEP151: Robótica, Visión y Control
This paper aims to introduce a standardized test methodology for drone detection, tracking, and identification systems. It is the aim that this standardized test methodology for assessing the performance of counter-drone systems will lead to a much better understanding of the capabilities of these solutions. This is urgently needed, as there is an increase in drone threats and there are no cohesive policies to evaluate the performance of these systems and hence mitigate and manage the threat. The presented methodology has been developed within the framework of the project COURAGEOUS funded by European Union’s Internal Security Fund Police. This standardized test methodology is based upon a series of standard user-defined scenarios representing a wide set of use cases. At this moment, these standard scenarios are geared toward civil security end users. However, the proposed standard methodology provides an open architecture where the standard scenarios can be modularly extended, providing standard users the possibility to easily add new scenarios. For each of these scenarios, operational needs and functional performance requirements are provided. Using this information, an integral test methodology is presented that allows for a fair qualitative and quantitative comparison between different counter-drone systems. The standard test methodology concentrates on the qualitative and quantitative evaluation of counter-drone systems. This test methodology was validated during three user-scripted validation trials.
Control tolerante a fallos en comunidades energéticas basado en blockchain
(Universidad Politécnica de Valencia, 2025) Sivianes Castaño, Manuel; Velarde, Pablo; Zafra Cabeza, Ascensión; Bordons Alba, Carlos; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Agencia Estatal de Investigación. España
Este trabajo presenta un sistema de control distribuido que optimiza la gestión energética en una comunidad utilizando control predictivo basado en modelos. Se ha extendido el sistema para dotar a cada agente de un mecanismo tolerante a fallos capaz de detectar, aislar y reconfigurar a gentes en caso de fallos. La detección se realiza mediante el cálculo de señales residuales y umbrales basados en restricciones de probabilidad para minimizar falsos positivos. Identificado el fallo, se ajustan los parámetros del controlador predictivo de la gente para mantener la seguridad del sistema. Si la reconfiguración afecta a múltiples a gentes, la información se comparte. El algoritmo de control utiliza un contrato inteligente en una red blockchain, resolviendo el problema de manera distribuida sin un coordinador central, y asegurando la seguridad e integridad de los datos. La estrategia propuesta ha sido evaluada mediante simulaciones en una comunidad energética.
Learning port maneuvers from data for automatic guidance of Unmanned Surface Vehicles
(Elsevier, 2025-07) Becerra-Mora, Yeyson; Acosta Rodríguez, José Ángel; Rodríguez Castaño, Ángel; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla; Universidad de Sevilla. TEP995: Multi-Robot and Control Systems
At shipping ports, some repetitive maneuvering tasks such as entering/leaving port, transporting goods inside it or just making surveillance activities, can be efficiently and quickly carried out by a domestic pilot according to his/her experience. This know-how can be seized by Unmanned Surface Vehicles (USV) in order to autonomously replicate the same tasks. However, the inherent nonlinearity of ship trajectories and environmental perturbations as wind or marine currents make it difficult to learn a model and its respective control. We therefore present a data-driven learning and control methodology for USV, which is based on Gaussian Mixture Model, Gaussian Mixture Regression and the Sontag’s universal formula. Our approach is capable to learn the nonlinear dynamics as well as guarantee the convergence toward the target with a robust controller. Real data have been collected through experiments with a vessel at the port of Ceuta. The complex trajectories followed by an expert have been learned including the robust controller. The effect of the controller over noise/perturbations are presented, a measure of error is used to compare estimates and real data trajectories, and finally, an analysis of computational complexity is performed.
Comparación de estrategias de control predictivo estocástico no lineal aplicadas a la quimioterapia
(Universidad Politécnica de Valencia, 2025) Hernández Rivera, Andrés; Velarde, Pablo; Zafra Cabeza, Ascensión; Maestre Torreblanca, José María; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Agencia Estatal de Investigación. España; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER)
El modelado matemático de sistemas biomédicos puede ayudar a los profesionales oncológicos a diseñar ciclos de administración de fármacos más seguros y eficaces. Para lograr este objetivo, en el proceso de toma de decisiones se utiliza el modelo matemático del crecimiento tumoral y el impacto de la quimioterapia. Sin embargo, los sistemas biomédicos son propensos a un alto grado de incertidumbre, no sólo por los errores de medición, sino también por la dinámica del sistema no modelada y la variabilidad entre pacientes. Para abordar este problema, se han aplicado restricciones probabilísticas al control del proceso de administración de fármacos, haciéndolo m ́as robusto frente a perturbaciones. Este trabajo compara una versión no lineal y otra linealizada de las formulaciones estocásticas del control predictivo basado en modelo. Ambos algoritmos mejoran la eficacia y la seguridad del tratamiento, con diferencias en cuanto a conservadurismo y coste computacional.
An Insurance Paradigm for Improving Power System Resilience via Distributed Investment
(IEEE, 2023) Billimoria, Farhad; Fele, Filiberto; Savelli, Iacopo; Morstyn, Thomas; McCulloch, Malcolm; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
Extreme events, exacerbated by climate change, pose significant risks to the energy system and its consumers. However there are natural limits to the degree of protection that can be delivered from a centralised market architecture. Distributed energy resources provide resilience to the energy system, but their value remains inadequately recognized by regulatory frameworks. We propose an insurance framework to align residual outage risk exposure with locational incentives for distributed investment. We demonstrate that leveraging this framework in large-scale electricity systems could improve consumer welfare outcomes in the face of growing risks from extreme events via investment in distributed energy.
Predicción de voltajes en la red eléctrica por interpolación Kriging
(Universidad Politécnica de Valencia, 2025) Moreno-Blázquez, Carlos; Fele, Filiberto; Limón Marruedo, Daniel; Alamo, Teodoro; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Ministerio de Ciencia, Innovación y Universidades (MICIU). España; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Universidad de Sevilla
En este trabajo, abordamos el problema de la predicción en línea de las trayectorias de voltaje e intensidad nodales en la red de distribución. Para esto, proponemos una formulación basada en datos utilizando la interpolación Kriging, una técnica de aprendizaje automático que ha mostrado aplicaciones prometedoras en el campo del control basado en datos. Producimos un oráculo de predicción no paramétrico que permite inferir trayectorias futuras directamente a partir de medidas de voltaje e intensidad en tiempo real. Además, proporcionamos una implementación algorítmica simple pero efectiva basada en el conocido esquema ISTA. Demostramos la efectividad de nuestra metodología para la predicción rápida (subsegundos) de la dinámica del voltaje mediante simulaciones.
Time Interleaving in the Analogue Circuitry of Oversampled Digital-to-Analogue Converters: Proof of Concept
(The Institution of Engineering and Technology, 2025) Laguna, Marta; Marsal, Esteban; Colodro Ruiz, Francisco; Martínez Heredia, Juana María; Arahal, Manuel R.; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Ministerio de Ciencia, Innovación y Universidades (MICIU). España; European Union (UE); Universidad de Sevilla. TIC275: Investigación y Desarrollo en Electrónica, Automática y Tecnologías Emergentes
Digital-to-analog converters (DACs) based on sigma-delta modulation are implemented with analog components that have low accuracy requirements. As a result, they have been widely employed in high-frequency transmitter architectures over the past decades. Time interleaving techniques allow parallel structures to operate at reduced speeds, thereby mitigating speed limitations in digital circuits. However, a common approach involves multiplexing the outputs of these parallel structures to reconstruct a single digital signal, which is subsequently converted to an analog voltage using a high-speed, low-resolution DAC. This work investigates the feasibility of employing a parallel array of low-speed DACs instead. To compensate for mismatches in analog paths, a novel dynamic element matching technique is proposed. Experimental results demonstrate that the proposed approach exhibits the characteristics required for high-frequency transmitter applications
Flight of the Future: An Experimental Analysis of Event-Based Vision for Online Perception Onboard Flapping-Wing Robots
(Wiley, 2025) Tapia López, Raúl; Luna-Santamaría, Javier; Gutiérrez Rodríguez, Iván; Rodríguez Gómez, Juan Pablo; Martínez de Dios, José Ramiro; Ollero Baturone, Aníbal; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Research Council (ERC)
Inspired by bird flight, flapping-wing robots have gained significant attention due to their high maneuverability and energy efficiency. However, the development of their perception systems faces several challenges, mainly related to payload restrictions and the effects of flapping strokes on sensor data. The limited resources of lightweight onboard processors further constrain the online processing required for autonomous flight. Event cameras exhibit several properties suitable for ornithopter perception, such as low latency, robustness to motion blur, high dynamic range, and low power consumption. This article explores the use of event-based vision for online processing onboard flapping-wing robots. First, the suitability of event cameras under flight conditions is assessed through experimental tests. Second, the integration of event-based vision systems onboard flapping-wing robots is analyzed. Finally, the performance, accuracy, and computational cost of some widely used event-based vision algorithms are experimentally evaluated when integrated into flapping-wing robots flying in indoor and outdoor scenarios under different conditions. The results confirm the benefits and suitability of event-based vision for online perception onboard ornithopters, paving the way for enhanced autonomy and safety in real-world flight operations.
Pareto Analysis of Electro-Mechanical Variables in Predictive Control of Drives
(MDPI, 2025) Garrido Satué, Manuel; Arahal, Manuel R.; Ortega Linares, Manuel Gil; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Ministerio de Ciencia, Innovación y Universidades (MICIU). España
Variable speed drives are often controlled by a double-loop scheme in which a proportional integral controller takes on the speed loop. The tuning of this loop is a complex job. In most cases just mechanical variables are considered for tuning. This paper presents a new Pareto analysis incorporating mechanical and electrical variables. A state of the art finite state model predictive controller is used for stator current control. The analysis is performed using experimental data from a five-phase induction motor and considers considering commonly found performance indicators derived from experimental data. The results show undocumented connections between those performance indicators. The analysis not only helps in PI tuning but, more importantly, prompts for a revision of the methods usually utilized to report performance enhancements of new methods.
Unified force and motion adaptive-integral control of flexible robot manipulators
(Elsevier, 2025-03) Rodríguez De Cos, Carlos; Acosta Rodríguez, José Ángel; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
In this paper, we propose an adaptive nonlinear strategy for the motion and force control of manipulators with flexible joints. Our approach provides force control when in contact and robust motion control in its absence, all without the need for a control switch. This self-tuning behaviour for mixed contact/non-contact scenarios results from a unified formulation of force and motion control, with an integral transpose-based inverse kinematics core and adaptive update laws to cope with the manipulator flexibility and the contact stiffnesses. The global boundedness of all signals and the asymptotic stability of this controller are guaranteed via Lyapunov analysis. Finally, we validate its applicability experimentally by using low-cost hardware in a realistic mixed-contact scenario, demonstrating low computational demand.
Active Network Management via grid-friendly electromobility control for curtailment minimization
(Elsevier, 2025) Čičić, Mladen; Vivas Venegas, Carlos; Canudas-de-Wit, Carlos; Rodríguez Rubio, Francisco; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Research Council (ERC); Ministerio de Ciencia e Innovación (MICIN). España
We propose an integrated power and transportation system control framework, combining the power grid model with a macroscopic electromobility model including charging stations under V2G operation. In this framework, the electrical vehicles (EVs) act as energy storage, but also as additional virtual power grid links, transporting energy from one point to another. This new holistic approach is used as a basis for optimal control design seeking to provide Active Network Management, in order to minimize curtailment of renewable energy sources and loads at various ports of the network, while accounting for the structural limitation of the grid and other constraints necessary for the optimal operation of the EVs. The proposed control scheme is shown to be able to outperform uncoordinated EV charging in terms of total curtailment in various studied scenarios. Additionally, we study the case when public charging stations are able to incentivize or disincentivise EVs to use them, by dynamically varying their charging price throughout the day, and show that this additional control input can further reduce curtailment in certain scenarios.
Three-time-scale control for discharging rate consensus and large-signal stability analysis in AC-bus microgrids
(Elsevier, 2025-06) Merchán-Riveros, María Camila; Albea-Sánchez, Carolina; Salas Gómez, Francisco; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Agencia Estatal de Investigación. España; Ministerio de Ciencia e Innovación (MICIN). España; Universidad de Sevilla. TEP102: Ingeniería Automática y Robótica
A distributed control scheme for islanded AC-bus microgrids is proposed, based on multi-agent system and singular perturbation theory. The goal is to achieve a balanced State Of Charge (SOC) for each Battery Energy Storage System (BESS) in discharging mode, ensuring stability properties of a large-signal model that considers the primary and secondary control loop dynamics. The power inverters are controlled through a voltage and current loop. Moreover, a droop control and consensus algorithm are proposed to ensure that the SOC of these BESSs are balanced. Furthermore, large-signal stability analysis is assessed for the complete network system by using singular perturbation theory. Indeed, through an appropriate selection of the parameters, the dynamics exhibit three-time-scale separation to fit each control goal (power converter control, droop control and consensus control). Experimental results on an Imperix power test bench validate the proposed control scheme, and verify the reliability and robustness with respect to any connection/disconnection event or communication failure through different scenarios.
Data-Driven Control Design for Power Converters Approximated as Switched Affine Systems and Experimental Validation
(IEEE, 2024) Merchán-Riveros, María Camila; Albea-Sánchez, Carolina; Seuret, Alexandre; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Agencia Estatal de Investigación. España; Universidad de Sevilla. TEP102: Ingeniería Automática y Robótica
This brief introduces a data-driven control design approach for power converters modelled as a switched affine system, that guarantees the global stability. Unlike many existing approaches, our contribution does not require a precise identification of a nonlinear model but it rather relies on prior random experimental data, which allows the design of a stabilizing control law in a direct manner. The proposed method is then evaluated on an Imperix power test bench. The experimental results not only confirm the viability of the data-driven approach for nonlinear systems but also demonstrate its applicability in real-world scenarios.
Hybrid Dynamical Control for Discharging Rate Consensus in AC-Bus Microgrids
(IEEE, 2023) Merchán-Riveros, María Camila; Albea-Sánchez, Carolina; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; Agence Nationale de la Recherche. France; Junta de Andalucía; Universidad de Sevilla. TEP102: Ingeniería Automática y Robótica
In this letter, a robust distributed hybrid algorithm is proposed for the primary and secondary control loops of an island AC-bus microgrid to provide large-signal stability of the complete system. A secondary control loop is designed from droop control and multi-agent systems theory to ensure that the State Of Charge (SOC) of the batteries in discharging mode converges to a consensus. Furthermore, this distributed strategy ensures robustness with respect to any plug-and-play event or communication failure. The DC-AC power converter of each battery in discharging mode is controlled in the primary loop by using hybrid dynamical system theory, which considers non-trivial issues in the model (switching and affine terms) and in the signals (constraints in the dwell time). A suited selection of gains allows using singular perturbation analysis to provide large-signal stability properties for the complete nonlinear model.
Three Time-Scale Singular Perturbation Hybrid Control and Large-Signal Analysis Stability in AC-Microgrids
(IEEE, 2023-08) Merchán-Riveros, María Camila; Albea-Sánchez, Carolina; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; Agence Nationale de la Recherche. France; Universidad de Sevilla. TEP102: Ingeniería Automática y Robótica
This work is devoted to propose a distributed control hybrid algorithm for the primary and secondary control loops of AC-bus microgrids in islanded mode and to provide a large-signal stability. A primary control loop based on Hybrid Dynamical System (HDS) theory manages the DC/AC inverters considering structural non-linearities in the model (affine terms and hybrid dynamics of their signals) and implementation constraints (dwell-time) and ensures the robustness of the output voltage with respect to any model variation. Moreover, the secondary control loop is designed based on the droop concept, which ensures that SOCs, reactive and active powers converge to their reference values, and on Multi-Agent System (MAS) theory to get a consensus among the reactive power and the State Of Charge (SOC) of the batteries in discharging mode. Moreover, it guarantees reliability and robustness with respect to any disconnection. The tuned system parameters are chosen in order to fit a three-time scale model (a time scale for each control objective: power converter control, droop control and consensus controls), which allows providing a large-signal stability analysis for the complete hybrid system based on HDS, MAS and singular perturbation theory.
Gestión óptima en microrredes con soporte fotovoltaico e hidrógeno verde
(Comité Español de Automática, 2025) Moliner Heredia, Rubén; Vivas Venegas, Carlos; Rodríguez Rubio, Francisco; Universidad de Sevilla. Departamento de Tecnología Electrónica; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Agencia Estatal de Investigación. España
La gestión de la energía es esencial para un correcto control de una microrred. Es importante que dicha gestión tenga en cuenta la optimización de la vida útil de los componentes de la microrred. Uno de los posibles comportamientos que se desean evitar es el apagado y encendido continuo de determinados componentes, tales como las celdas de combustible y los electrolizadores. En este artículo se ha propuesto un algoritmo usando control predictivo basado en modelo (MPC) utilizando diversas restricciones de tiempos mínimos de activación de dichos componentes para evitar efectos perjudiciales sobre los equipos de hidrógeno verde. Además, se ha propuesto un método de transmisión entre iteraciones del algoritmo para que la aplicación de dichas restricciones sea compatible con errores en las predicciones del algoritmo y de perturbaciones en el sistema. Para validar el algoritmo propuesto, se ha desarrollado un modelo simplificado de la microrred, y se han realizado simulaciones y comparaciones con varios algoritmos utilizando Matlab.
Integración de tecnologías Blockchain en un esquema de control predictivo distribuido y jerárquico para comunidades energéticas
(Universidad Politécnica de Valencia, 2025) Sivianes Castaño, Manuel; Velarde Rueda, Pablo; Zafra Cabeza, Ascensión; Bordons Alba, Carlos; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Agencia Estatal de Investigación. España; Universidad de Sevilla. TEP116: Automática y Robótica Industrial
En este estudio se introduce una plataforma de gestión energética jerárquica que incorpora la tecnología blockchain para eliminar la dependencia de un coordinador centralizado. La plataforma está diseñada para operar en comunidades energéticas afectadas por incertidumbres estocásticas. La estrategia se divide en dos niveles: en el nivel superior, donde se resuelve un problema de optimización de control predictivo distribuido estocástico, en el que todos los hogares de la comunidad participan para determinar las acciones de control de manera horaria. En este nivel, se utiliza un contrato inteligente como intermediario entre los hogares, encargado de realizar tareas de control e intercambio de información. Por otro lado, en el nivel inferior, cada hogar resuelve de manera local e independiente un problema de optimización de control predictivo para seguir las referencias establecidas después del consenso alcanzado por la capa superior, a una frecuencia significativamente mayor. La validez de esta plataforma para optimizar el funcionamiento económico de la comunidad y cumplir con las restricciones probabilísticas se ha validado con diferentes simulaciones.
Door-to-Door Parcel Delivery From Supply Point to User’s Home With Heterogeneous Robot Team: The euROBIN First-Year Robotics Hackathon
(Institute of Electrical and Electronics Engineers Inc.(IEEE), 2024) Suárez Fernández-Miranda, Alejandro; Kartmann, Rainer; Leidner, Daniel; Rossini, Luca; Huber, Johann; Azevedo, Carlos; González Morgado, Antonio; Pérez Sánchez, Vicente; Arrue Ullés, Begoña C.; Ollero Baturone, Aníbal; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Commission (EC); Universidad de Sevilla. TEP151: Robótica, Visión y Control
Logistics and service operations involving parcel preparation, delivery, and unpacking from a supply point to a user's home could be carried out completely by robots in the near future, taking advantage of the capabilities of the different robot morphologies for the logistics, outdoor, and domestic environments. The use of robots for parcel delivery can contribute to the goals of sustainability and reduced emissions by exploiting their different locomotion modalities (wheeled, legged, and aerial). This article reports the development and results obtained from the first robotics hackathon celebrated as part of the European Robotics and Artificial Intelligence Network involving eight robotic platforms in three domains: 1) an industrial robotic arm for parcel preparation at the supply point, 2) a Centauro robot, a dual-arm aerial manipulator, and a wheeled-legged quadruped for parcel transportation, and 3) two humanoid robots and two commercial mobile manipulators for parcel delivery and unpacking in domestic scenarios. The article describes the joint operation and the evaluation scenario, the features and capabilities of the robots, particularly those involved in the realization of the tasks, and the lessons learned.
Software Integration of Power System Measurement Devices with AI Capabilities
(MDPI, 2025-01) Arenas Ramos, Victoria; Cuesta Rojo, Federico; Pallares López, Víctor; Santiago Chiquero, Isabel; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Agencia Estatal de Investigación. España
The latest changes on the distribution network due to the presence of distributed energy resources (DERs) and electric vehicles make it necessary to monitor the grid using a real-time high-precision system. The present work centers on the development of an open-source software platform that allows for the joint management of, at least, power quality monitors (PQMs), phasor measurement units (PMUs), and smart meters (SMs), which are three of the most widespread devices on distribution networks. This framework could work remotely while allowing access to the measurements in a comfortable way for grid analysis, prediction, or control tasks. The platform must meet the requirements of synchronism and scalability needed when working with electrical monitoring devices while considering the large volumes of data that these devices generate. The framework has been experimentally validated in laboratory and field tests in two photovoltaic plants. Moreover, real-time Artificial Intelligence capabilities have been validated by implementing three Machine Learning classifiers (Neural Network, Decision Tree, and Random Forest) to distinguish between three different loads in real time.

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