J. Luque

Universidad de Sevilla

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Carlos León

Universidad de Sevilla

J.I. Escudero

Universidad de Sevilla

Julio Barbancho

Universidad de Sevilla

Alejandro Carrasco

Massachusetts Institute of Technology

Isabel Gómez

Universidad de Sevilla

Enrique Personal

Universidad de Sevilla

S. Martín

Universidade da Coruña

M. Mejías

Universidad de Sevilla

Robert Denda

Enel (Italy)

ÍM

Íñigo Monedero

Universidad de Sevilla

Cooperative Institutions

Universidad de Sevilla

Consejo Superior de Investigaciones Científicas

Universidad Complutense de Madrid

Universidad de Málaga

Unidades Centrales Científico-Técnicas

Instituto de Microelectrónica de Sevilla

Centro Nacional de Microelectrónica

Analogic (United States)

Técnicas y Servicios de Ingeniería (Spain)

Universidad Politécnica de Madrid

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Determining the channel capacity in SCADA systems using polling protocols [power system telecontrol]

IEEE Transactions on Power Systems (1996)

J. Luque Isabel Gómez J.I. Escudero

This article presents a method for calculating the capacity of a power system telecontrol multi-point communications channel when a polling protocol is used. Both an exact solution and an approximate but easier-to-use solution are obtained. With the results derived here, the number of remote stations that can communicate with the control center over a single channel can be determined. The analytical results are compared to the traffic results measured experimentally.

SCADA

10.1109/59.496175

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Citations (12)

Spectral Analysis of Electricity Demand Using Hilbert–Huang Transform

Sensors (2020)

J. Luque Davide Anguita Francisco Martos Robert Denda

The large amount of sensors in modern electrical networks poses a serious challenge in the data processing side. For many years, spectral analysis has been one of the most used approaches to extract physically meaningful information from a sea of data. Fourier Transform (FT) and Wavelet Transform (WT) are by far the most employed tools in this analysis. In this paper we explore the alternative use of Hilbert-Huang Transform (HHT) for electricity demand spectral representation. A sequence of hourly consumptions, spanning 40 months of electrical demand in Spain, has been used as dataset. First, by Empirical Mode Decomposition (EMD), the sequence has been time-represented as an ensemble of 13 Intrinsic Mode Functions (IMFs). Later on, by applying Hilbert Transform (HT) to every IMF, an HHT spectrum has been obtained. Results show smoother spectra with more defined shapes and an excellent frequency resolution. EMD also fosters a deeper analysis of abnormal electricity demand at different timescales. Additionally, EMD permits information compression, which becomes very significant for lossless sequence representation. A 35% reduction has been obtained for the electricity demand sequence. On the negative side, HHT demands more computer resources than conventional spectral analysis techniques.

Hilbert spectral analysis

Representation

Sequence (biology)

10.3390/s20102912

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Citations (19)

Analytic model of the measurement errors caused by communications delay

IEEE Transactions on Power Delivery (2002)

J. Luque J.I. Escudero F. Pérez

The protocols and communication systems used in the control of electric networks create delays due to various factors such as limitation of the transmission speed, retransfer among nodes, processing time, etc. These delays introduce some errors in the measurements used in the control center which depend on the magnitude of the delay and the evolution of the measurements. In this paper, an analytic model of the relationship between measurement error and delay is presented. The validity of the model is compared with experimental data from an electric network.

10.1109/61.997893

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Citations (15)

SSOT-Based Laboratory on IIoT for Industry 4.0 Architectures

Samuel Domíguez-Cid Diego Francisco Larios Francisco Javier Molina J. Luque Alejandro Carrasco

10.1109/taee59541.2024.10604981

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Machine Learning Estimation of Battery Efficiency and Related Key Performance Indicators in Smart Energy Systems

Energies (2023)

J. Luque Benedikt Tepe Diego Francisco Larios Carlos León Holger C. Hesse

Battery systems are extensively used in smart energy systems in many different applications, such as Frequency Containment Reserve or Self-Consumption Increase. The behavior of a battery in a particular operation scenario is usually summarized using different key performance indicators (KPIs). Some of these indicators such as efficiency indicate how much of the total electric power supplied to the battery is actually used. Other indicators, such as the number of charging-discharging cycles or the number of charging-discharging swaps, are of relevance for deriving the aging and degradation of a battery system. Obtaining these indicators is very time-demanding: either a set of lab experiments is run, or the battery system is simulated using a battery simulation model. This work instead proposes a machine learning (ML) estimation of battery performance indicators derived from time series input data. For this purpose, a random forest regressor has been trained using the real data of electricity grid frequency evolution, household power demand, and photovoltaic power generation. The results obtained in the research show that the required KPIs can be estimated rapidly with an average relative error of less than 10%. The article demonstrates that the machine learning approach is a suitable alternative to obtain a very fast rough approximation of the expected behavior of a battery system and can be scaled and adapted well for estimation queries of entire fleets of battery systems.

Performance indicator

10.3390/en16145548

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Citations (1)

Evaluation of MPEG-7-Based Audio Descriptors for Animal Voice Recognition over Wireless Acoustic Sensor Networks

Sensors (2016)

J. Luque Diego Francisco Larios Enrique Personal Julio Barbancho Carlos León

Environmental audio monitoring is a huge area of interest for biologists all over the world. This is why some audio monitoring system have been proposed in the literature, which can be classified into two different approaches: acquirement and compression of all audio patterns in order to send them as raw data to a main server; or specific recognition systems based on audio patterns. The first approach presents the drawback of a high amount of information to be stored in a main server. Moreover, this information requires a considerable amount of effort to be analyzed. The second approach has the drawback of its lack of scalability when new patterns need to be detected. To overcome these limitations, this paper proposes an environmental Wireless Acoustic Sensor Network architecture focused on use of generic descriptors based on an MPEG-7 standard. These descriptors demonstrate it to be suitable to be used in the recognition of different patterns, allowing a high scalability. The proposed parameters have been tested to recognize different behaviors of two anuran species that live in Spanish natural parks; the Epidalea calamita and the Alytes obstetricans toads, demonstrating to have a high classification performance.

10.3390/s16050717

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Citations (21)

Expert System-Based Alarm Management in Communication Networks.

International Conference on Enterprise Information Systems (2000)

S. Díaz J.I. Escudero J. Luque

The environment which makes possible rule-based expert system aided network management is described. One of the most important objectives for us is to integrate the management rules into the managed object itself, as an alternative to a solution where those rules were statically linked to the expert system shell.

Legal expert system

Network monitoring

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Raspberry Pi-based cluster network for the emulation of sensor networks in remote teaching

2022 Congreso de Tecnología, Aprendizaje y Enseñanza de la Electrónica (XV Technologies Applied to Electronics Teaching Conference) (2022)

Antonio Parejo Sebastián García Diego Francisco Larios Alejandro Gallardo J. Luque

Due to their versatility, sensor networks and Internet of Things (IoT) have become technologies of a great importance in many modern applications in so-diverse ambits such as environmental monitoring and smart cities. Therefore, these are included in the contents of the subject "Advanced Sensor Network Infrastructure" of the Master on Intelligent Systems on Energy and Transport of the University of Seville. This subject serves as an introduction to sensor networks, their applications, and their operating principles. Its schedule includes laboratory lessons in which the students use various sensor devices for learning about the existing communication and processing methods. The health crisis caused by the COVID-19 has made difficult that all the students have physical access to the laboratory at the same time, which forced to adapt the existing materials and facilities. In this sense, to solve this problem, a Raspberry Pi-based computer network has been deployed to allow the emulation of a sensor network while providing external remote access to the students for them to perform their laboratory tasks. At the same time, this proposal has expanded the subject contents to cover several data processing layers and architectures.

Raspberry Pi

10.1109/taee54169.2022.9840573

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Citations (3)

Datacab: a geographical‐information‐system‐based expert system for the design of cable networks

Expert Systems (2008)

Íñigo Monedero Carlos León Robert Denda J. Luque

Abstract: Telecommunication networks have evolved over time as a result of technological advances, and network topologies and equipment have become increasingly complex. Expert systems are being successfully applied to the management of telecommunication networks. However, applying expert systems to network design is another especially beneficial yet still not very common approach. In this paper we propose a rule‐based expert system called Datacab. Datacab was developed at Enditel Endesa in collaboration with the Electronic Technology Department of the University of Seville, for the automatic design of hybrid fibre coax (HFC) cable networks. Using data from a geographical information system as input, it automatically generates viable HFC network designs.

10.1111/j.1468-0394.2008.00445.x

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Citations (7)

KROME Ceramics Sistema de gestión del color para la industria cerámica

Boletín de la Sociedad Española de Cerámica y Vidrio (2013)

Alejandro Martı́n J. Luque O. Pla Sylvia Selvi

10.3989/cyv.2013.v52.i2.1193

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