Dynamic segmentation techniques applied to load profiles of electric energy consumption from domestic users

[EN] The electricity sector is currently undergoing a process of liberalization and separation of roles, which is being implemented under the regulatory auspices of each Member State of the European Union and, therefore, with different speeds, perspectives and objectives that must converge on a common horizon, where Europe will benefit from an interconnected energy market in which producers and consumers can participate in free competition. This process of liberalization and separation of roles involves two consequences or, viewed another way, entails a major consequence from which other immediate consequence, as a necessity, is derived. The main consequence is the increased complexity in the management and supervision of a system, the electrical, increasingly interconnected and participatory, with connection of distributed energy sources, much of them from renewable sources, at different voltage levels and with different generation capacity at any point in the network. From this situation the other consequence is derived, which is the need to communicate information between agents, reliably, safely and quickly, and that this information is analyzed in the most effective way possible, to form part of the processes of decision taking that improve the observability and controllability of a system which is increasing in complexity and number of agents involved. With the evolution of Information and Communication Technologies (ICT), and the investments both in improving existing measurement and communications infrastructure, and taking the measurement and actuation capacity to a greater number of points in medium and low voltage networks, the availability of data that informs of the state of the network is increasingly higher and more complete. All these systems are part of the so-called Smart Grids, or intelligent networks of the future, a future which is not so far. One such source of information comes from the energy consumption of customers, measured on a regular basis (every hour, half hour or quarter-hour) and sent to the Distribution System Operators from the Smart Meters making use of Advanced Metering Infrastructure (AMI). This way, there is an increasingly amount of information on the energy consumption of customers, being stored in Big Data systems. This growing source of information demands specialized techniques which can take benefit from it, extracting a useful and summarized knowledge from it. This thesis deals with the use of this information of energy consumption from Smart Meters, in particular on the application of data mining techniques to obtain temporal patterns that characterize the users of electrical energy, grouping them according to these patterns in a small number of groups or clusters, that allow evaluating how users consume energy, both during the day and during a sequence of days, allowing to assess trends and predict future scenarios. For this, the current techniques are studied and, proving that the current works do not cover this objective, clustering or dynamic segmentation techniques applied to load profiles of electric energy consumption from domestic users are developed. These techniques are tested and validated on a database of hourly energy consumption values for a sample of residential customers in Spain during years 2008 and 2009. The results allow to observe both the characterization in consumption patterns of the different types of residential energy consumers, and their evolution over time, and to assess, for example, how the regulatory changes that occurred in Spain in the electricity sector during those years influenced in the temporal patterns of energy consumption.[ES] El sector eléctrico se halla actualmente sometido a un proceso de liberalización y separación de roles, que está siendo aplicado bajo los auspicios regulatorios de cada Estado Miembro de la Unión Europea y, por tanto, con distintas velocidades, perspectivas y objetivos que deben confluir en un horizonte común, en donde Europa se beneficiará de un mercado energético interconectado, en el cual productores y consumidores podrán participar en libre competencia. Este proceso de liberalización y separación de roles conlleva dos consecuencias o, visto de otra manera, conlleva una consecuencia principal de la cual se deriva, como necesidad, otra consecuencia inmediata. La consecuencia principal es el aumento de la complejidad en la gestión y supervisión de un sistema, el eléctrico, cada vez más interconectado y participativo, con conexión de fuentes distribuidas de energía, muchas de ellas de origen renovable, a distintos niveles de tensión y con distinta capacidad de generación, en cualquier punto de la red. De esta situación se deriva la otra consecuencia, que es la necesidad de comunicar información entre los distintos agentes, de forma fiable, segura y rápida, y que esta información sea analizada de la forma más eficaz posible, para que forme parte de los procesos de toma de decisiones que mejoran la observabilidad y controlabilidad de un sistema cada vez más complejo y con más agentes involucrados. Con el avance de las Tecnologías de Información y Comunicaciones (TIC), y las inversiones tanto en mejora de la infraestructura existente de medida y comunicaciones, como en llevar la obtención de medidas y la capacidad de actuación a un mayor número de puntos en redes de media y baja tensión, la disponibilidad de datos sobre el estado de la red es cada vez mayor y más completa. Todos estos sistemas forman parte de las llamadas Smart Grids, o redes inteligentes del futuro, un futuro ya no tan lejano. Una de estas fuentes de información proviene de los consumos energéticos de los clientes, medidos de forma periódica (cada hora, media hora o cuarto de hora) y enviados hacia las Distribuidoras desde los contadores inteligentes o Smart Meters, mediante infraestructura avanzada de medida o Advanced Metering Infrastructure (AMI). De esta forma, cada vez se tiene una mayor cantidad de información sobre los consumos energéticos de los clientes, almacenada en sistemas de Big Data. Esta cada vez mayor fuente de información demanda técnicas especializadas que sepan aprovecharla, extrayendo un conocimiento útil y resumido de la misma. La presente Tesis doctoral versa sobre el uso de esta información de consumos energéticos de los contadores inteligentes, en concreto sobre la aplicación de técnicas de minería de datos (data mining) para obtener patrones temporales que caractericen a los usuarios de energía eléctrica, agrupándolos según estos mismos patrones en un número reducido de grupos o clusters, que permiten evaluar la forma en que los usuarios consumen la energía, tanto a lo largo del día como durante una secuencia de días, permitiendo evaluar tendencias y predecir escenarios futuros. Para ello se estudian las técnicas actuales y, comprobando que los trabajos actuales no cubren este objetivo, se desarrollan técnicas de clustering o segmentación dinámica aplicadas a curvas de carga de consumo eléctrico diario de clientes domésticos. Estas técnicas se prueban y validan sobre una base de datos de consumos energéticos horarios de una muestra de clientes residenciales en España durante los años 2008 y 2009. Los resultados permiten observar tanto la caracterización en consumos de los distintos tipos de consumidores energéticos residenciales, como su evolución en el tiempo, y permiten evaluar, por ejemplo, cómo influenciaron en los patrones temporales de consumos los cambios regulatorios que se produjeron en España en el sector eléctrico durante esos años.[CA] El sector elèctric es troba actualment sotmès a un procés de liberalització i separació de rols, que s'està aplicant davall els auspicis reguladors de cada estat membre de la Unió Europea i, per tant, amb distintes velocitats, perspectives i objectius que han de confluir en un horitzó comú, on Europa es beneficiarà d'un mercat energètic interconnectat, en el qual productors i consumidors podran participar en lliure competència. Aquest procés de liberalització i separació de rols comporta dues conseqüències o, vist d'una altra manera, comporta una conseqüència principal de la qual es deriva, com a necessitat, una altra conseqüència immediata. La conseqüència principal és l'augment de la complexitat en la gestió i supervisió d'un sistema, l'elèctric, cada vegada més interconnectat i participatiu, amb connexió de fonts distribuïdes d'energia, moltes d'aquestes d'origen renovable, a distints nivells de tensió i amb distinta capacitat de generació, en qualsevol punt de la xarxa. D'aquesta situació es deriva l'altra conseqüència, que és la necessitat de comunicar informació entre els distints agents, de forma fiable, segura i ràpida, i que aquesta informació siga analitzada de la manera més eficaç possible, perquè forme part dels processos de presa de decisions que milloren l'observabilitat i controlabilitat d'un sistema cada vegada més complex i amb més agents involucrats. Amb l'avanç de les tecnologies de la informació i les comunicacions (TIC), i les inversions, tant en la millora de la infraestructura existent de mesura i comunicacions, com en el trasllat de l'obtenció de mesures i capacitat d'actuació a un nombre més gran de punts en xarxes de mitjana i baixa tensió, la disponibilitat de dades sobre l'estat de la xarxa és cada vegada major i més completa. Tots aquests sistemes formen part de les denominades Smart Grids o xarxes intel·ligents del futur, un futur ja no tan llunyà. Una d'aquestes fonts d'informació prové dels consums energètics dels clients, mesurats de forma periòdica (cada hora, mitja hora o quart d'hora) i enviats cap a les distribuïdores des dels comptadors intel·ligents o Smart Meters, per mitjà d'infraestructura avançada de mesura o Advanced Metering Infrastructure (AMI). D'aquesta manera, cada vegada es té una major quantitat d'informació sobre els consums energètics dels clients, emmagatzemada en sistemes de Big Data. Aquesta cada vegada major font d'informació demanda tècniques especialitzades que sàpiguen aprofitar-la, extraient-ne un coneixement útil i resumit. La present tesi doctoral versa sobre l'ús d'aquesta informació de consums energètics dels comptadors intel·ligents, en concret sobre l'aplicació de tècniques de mineria de dades (data mining) per a obtenir patrons temporals que caracteritzen els usuaris d'energia elèctrica, agrupant-los segons aquests mateixos patrons en una quantitat reduïda de grups o clusters, que permeten avaluar la forma en què els usuaris consumeixen l'energia, tant al llarg del dia com durant una seqüència de dies, i que permetent avaluar tendències i predir escenaris futurs. Amb aquesta finalitat, s'estudien les tècniques actuals i, en comprovar que els treballs actuals no cobreixen aquest objectiu, es desenvolupen tècniques de clustering o segmentació dinàmica aplicades a corbes de càrrega de consum elèctric diari de clients domèstics. Aquestes tècniques es proven i validen sobre una base de dades de consums energètics horaris d'una mostra de clients residencials a Espanya durant els anys 2008 i 2009. Els resultats permeten observar tant la caracterització en consums dels distints tipus de consumidors energètics residencials, com la seua evolució en el temps, i permeten avaluar, per exemple, com van influenciar en els patrons temporals de consums els canvis reguladors que es van produir a Espanya en el sector elèctric durant aquests anys.Benítez Sánchez, IJ. (2015). Dynamic segmentation techniques applied to load profiles of electric energy consumption from domestic users [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/59236TESI

Dynamic clustering segmentation applied to load profiles of energy consumption from Spanish customers

[EN] The following article describes the work of dynamic segmentation of daily load profiles throughout years 2008 and 2009, of a representative sample of Spanish residential customers. The technique applied is classification of the energy consumption time series of load profiles by means of dynamic clustering algorithms. The techniques used and analysis performed prove adequate as a fast tool to classify clients according to their energy consumption patterns, as well as to evaluate their overall energy consumption trends at a glance. The segmentation of the energy consumption load profiles is performed, and the results are analyzed and discussed.The works developed in this document have been possible thanks to Iberdrola Distribucion Electrica S.A.U. and the development of the GAD project. The GAD or "Active Demand Management" (in Spanish) project was a project supported by the Spanish Government, and participated by 14 different companies and 14 research centers. It was sponsored by the CDTI (Technological Development Centre of the Ministry of Science and Innovation of Spain), and financed by the INGENIO 2010 program.Benítez Sánchez, IJ.; Quijano-Lopez, A.; Diez, J.; Delgado Espinos, I. (2014). Dynamic clustering segmentation applied to load profiles of energy consumption from Spanish customers. International Journal of Electrical Power & Energy Systems. 55:437-448. https://doi.org/10.1016/j.ijepes.2013.09.022S4374485

Classification of customers based on temporal load profile patterns

[EN] The deployment of Advanced Metering Infrastructure (AMI) is providing to utilities large amounts of energy consumption data from their customers, in form of daily load profiles with energy consumed per hour or a smaller period. These data can yield valuable results when analyzed, in order to extract useful knowledge about the typical patterns of consumption of energy from the customers. The proper mechanisms and tools have to be developed and implemented for this objective. Big Data and Big Data Analytics systems will contribute to analyze this information and help to extract knowledge from the data, summarized in form of patterns or other mining knowledge, that will aid experts in decision support. In the present work a classification of customers based on their temporal load profiles is proposed. This classification procedure could be implemented in the current Big Data Analytics software systems, providing an added value to their statistical analysis options. Previous works in the literature present algorithms that allow to classify load profiles from customers by processing batch datasets and obtaining static patterns of load profiles. The proposed technique allows to analyze patterns not only in shape but also in their evolution or trend of energy consumption at each hour of the day through time. Specific quantitative indicators that characterize the patterns (and the consumers associated to them) are described and tested for this purpose.Benítez Sánchez, IJ.; Quijano Lopez, A.; Delgado Espinos, I.; Diez Ruano, JL. (2017). Classification of customers based on temporal load profile patterns. Cigre Science & engineering. (7):143-148. http://hdl.handle.net/10251/104883S143148

Dynamic clustering of residential electricity consumption time seriesdata based on Hausdorff distance

[EN] As the analysis of electrical loads is reaching data measured from low voltage power distribution networks, there is a need for the main agents involved in the operation and management of the power grids to segment the end users as a function of their shapes of daily energy consumption or load profiles, and to obtain patterns that allow to classify the users in groups based on how they consume the energy. However, this analysis is usually limited to the analysis of single days. Since the smart metering data are time series formed by sequential measurements of energy through each hour or quarter of hour of the day, and also through each day, thanks to the implementation of Advanced Metering Infrastructure (AMI) and the Smart Grid technologies, it becomes clear that the analysis of the data needs to be extended to consider the dynamic evolution of the consumption patterns through days, weeks, months, seasons, and even years. This is the objective of the present work. A new framework is presented that addresses the dynamic clustering, visualization and identification of temporal patterns in load profiles time series, fulfilling the detected gap in this area. The present development is a generic framework that allows the clustering and visualization of load profiles time series applying different classical clustering algorithms. A novel dynamic clustering algorithm is also presented, based on an initial segmentation of the energy consumption time series data in smaller surfaces, and the computation of a similarity measure among them applying the Hausdorff distance. Following, these developments are presented and tested on two dataset of energy consumption load profiles from a sample of residential users in Spain and London.The data set for the Spanish case used in this work has been provided by the Spanish DSO Iberdrola Distribucion Electrica S.A. as part of the works developed in the Spanish R&D project GAD. The GAD or "Active Demand Management" (in Spanish) project was a project financed by the INGENIO 2010 program and supported by the CDTI (Technological Development Centre of the Ministry of Science and Innovation of Spain).Benítez Sánchez, IJ.; Diez Ruano, JL.; Quijano Lopez, A.; Delgado Espinos, I. (2016). Dynamic clustering of residential electricity consumption time seriesdata based on Hausdorff distance. Electric Power Systems Research. 140:517-526. doi:10.1016/j.epsr.2016.05.023S51752614

Development of a prediction model for short-term remission of patients with Crohn’s disease treated with anti-TNF drugs

Therapy with anti-tumor necrosis factor (TNF) has dramatically changed the natural history of Crohn’s disease (CD). However, these drugs are not without adverse events, and up to 40% of patients could lose efficacy in the long term. We aimed to identify reliable markers of response to anti-TNF drugs in patients with CD. A consecutive cohort of 113 anti-TNF naive patients with CD was stratified according to clinical response as short-term remission (STR) or non-STR (NSTR) at 12 weeks of treatment. We compared the protein expression profiles of plasma samples in a subset of patients from both groups prior to anti-TNF therapy by SWATH proteomics. We identified 18 differentially expressed proteins (p ≤ 0.01, fold change ≥ 2.4) involved in the organization of the cytoskeleton and cell junction, hemostasis/platelet function, carbohydrate metabolism, and immune response as candidate biomarkers of STR. Among them, vinculin was one of the most deregulated proteins (p < 0.001), whose differential expression was confirmed by ELISA (p = 0.054). In the multivariate analysis, plasma vinculin levels along with basal CD Activity Index, corticosteroids induction, and bowel resection were factors predicting NSTR

Paleoecología y cultura material en el complejo tumular prehistórico de Castillejo del Bonete (Terrinches, Ciudad Real)

Castillejo del Bonete es un complejo tumular situado en el borde meridional de la Meseta Ibérica, ocupado en fechas calcolíticas y de la Edad del Bronce, vinculado a la Cultura de las Motillas. Materiales arqueológicos muy diversos han sido recuperados asociados a las arquitecturas del lugar (túmulos, corredores, potentes muros, etc.). Se presenta un avance de la investigación paleoecológica sobre las colecciones de carbón, polen y microvertebrados. Además se presentan cuentas de piedra y madera, colgantes de concha, material lítico, la colección cerámica, nuevas metalografías e industria metálica y botones de marfil. El conjunto de estas evidencias arqueológicas pone de manifiesto la celebración ritual de banquetes y ofrendas durante la Prehistoria Reciente en una cueva monumentalizada mediante túmulos en el interior de la Península Ibérica

Predictors of Response to Exclusive Enteral Nutrition in Newly Diagnosed Crohn´s Disease in Children: PRESENCE Study from SEGHNP

Exclusive enteral nutrition (EEN) has been shown to be more effective than corticosteroids in achieving mucosal healing in children with Crohn´s disease (CD) without the adverse effects of these drugs. The aims of this study were to determine the efficacy of EEN in terms of inducing clinical remission in children newly diagnosed with CD, to describe the predictive factors of response to EEN and the need for treatment with biological agents during the first 12 months of the disease. We conducted an observational retrospective multicentre study that included paediatric patients newly diagnosed with CD between 2014–2016 who underwent EEN. Two hundred and twenty-two patients (140 males) from 35 paediatric centres were included, with a mean age at diagnosis of 11.6 ± 2.5 years. The median EEN duration was 8 weeks (IQR 6.6–8.5), and 184 of the patients (83%) achieved clinical remission (weighted paediatric Crohn’s Disease activity index [wPCDAI] 15 mg/L and ileal involvement tended to respond better to EEN. EEN administered for 6–8 weeks is effective for inducing clinical remission. Due to the high response rate in our series, EEN should be used as the first-line therapy in luminal paediatric Crohn’s disease regardless of the location of disease and disease activityS

Assessing Associations between the AURKA-HMMR-TPX2-TUBG1 Functional Module and Breast Cancer Risk in BRCA1/2 Mutation Carriers

While interplay between BRCA1 and AURKA-RHAMM-TPX2-TUBG1 regulates mammary epithelial polarization, common genetic variation in HMMR (gene product RHAMM) may be associated with risk of breast cancer in BRCA1 mutation carriers. Following on these observations, we further assessed the link between the AURKA-HMMR-TPX2-TUBG1 functional module and risk of breast cancer in BRCA1 or BRCA2 mutation carriers. Forty-one single nucleotide polymorphisms (SNPs) were genotyped in 15,252 BRCA1 and 8,211 BRCA2 mutation carriers and subsequently analyzed using a retrospective likelihood approach. The association of HMMR rs299290 with breast cancer risk in BRCA1 mutation carriers was confirmed: per-allele hazard ratio (HR) = 1.10, 95% confidence interval (CI) 1.04 – 1.15, p = 1.9 x 10−4 (false discovery rate (FDR)-adjusted p = 0.043). Variation in CSTF1, located next to AURKA, was also found to be associated with breast cancer risk in BRCA2 mutation carriers: rs2426618 per-allele HR = 1.10, 95% CI 1.03 – 1.16, p = 0.005 (FDR-adjusted p = 0.045). Assessment of pairwise interactions provided suggestions (FDR-adjusted pinteraction values > 0.05) for deviations from the multiplicative model for rs299290 and CSTF1 rs6064391, and rs299290 and TUBG1 rs11649877 in both BRCA1 and BRCA2 mutation carriers. Following these suggestions, the expression of HMMR and AURKA or TUBG1 in sporadic breast tumors was found to potentially interact, influencing patients’ survival. Together, the results of this study support the hypothesis of a causative link between altered function of AURKA-HMMR-TPX2-TUBG1 and breast carcinogenesis in BRCA1/2 mutation carriers

Ética Profesional y Responsabilidad Social Universitaria

este libro compila reflexiones y experiencias en responsabilidad social y ética profesional desde instituciones de Educación Superior. La responsabilidad social universitaria, como ámbito de investigación y de desarrollo conceptual y metodológico es transversal a las universidades, tanto desde el punto de vista organizacional, como desde el misional e investigativo. Quienes impulsen la responsabilidad social, requieren de ética profesional, que debe ser la clave para la construcción de principios que guíen a empresarios, políticos, gestores sociales, investigadores, entre otros, para lograr consensuar el a veces difícil equilibrio entre el bien común y el desarrollo personal

Clinical guide of the Spanish Society of Nephrology on the prevention and treatment of peritoneal infection in peritoneal dialysis

[Resumen] Las infecciones peritoneales siguen constituyendo una complicación muy relevante de la diálisis peritoneal, por su incidencia todavía elevada y por sus importantes consecuencias clínicas, en términos de mortalidad, fracaso de la técnica y costes para el sistema sanitario. Las prácticas de prevención y tratamiento de esta complicación muestran una notable heterogeneidad derivada, entre otros factores, de la complejidad del problema y de la escasez de evidencia clínica que permitan responder de manera clara a muchas de las dudas planteadas. El propósito de este documento es proporcionar una revisión completa y actualizada de los métodos de diagnóstico, prevención y tratamiento de estas infecciones. El documento se ha elaborado tomando como referencia de partida la guía más reciente de la Sociedad Internacional de Diálisis Peritoneal (2016). Mientras que para el capítulo diagnóstico se ha adoptado una estructura más narrativa, el análisis de las medidas de prevención y tratamiento ha seguido una metodología sistemática (Grading of Recommendations, Assessment, Development and Evaluation [GRADE]), que especifica el nivel de evidencia y la fuerza de las sugerencias y recomendaciones propuestas, y facilita actualizaciones futuras de la guía. La gran extensión y numerosas recomendaciones o sugerencias emanadas de la revisión ponen de manifiesto la complejidad y gran número de facetas a tener en cuenta para un adecuado abordaje de esta importante complicación de la diálisis peritoneal.[Abstract] Peritoneal infections still represent a most feared complication of chronic peritoneal dialysis, due to their high incidence and relevant clinical consequences, including direct mortality, technique failure and a significant burden for the health system. The practices for prevention and treatment of this complication show a remarkable heterogeneity emerging, among other factors, from the complexity of the problem and from a paucity of quality evidence which could permit to respond clearly to many of the raised questions. The purpose of this document is to provide a complete and updated review of the main methods of diagnosis, prevention and treatment of these infections. The document has been elaborated taking as a reference the most recent guidelines of the International Society of Peritoneal Dialysis (2016). The diagnostic considerations are presented in a narrative style while, for prevention and therapy, we have used a systematic methodology (Grading of Recommendations, Assessment, Development and Evaluation [GRADE]), which specifies the level of evidence and the strength of the proposed suggestions and recommendations and facilitates future updates of the document. The length of the document and the many suggestions and recommendations coming out of the review underline the large number and the complexity of the factors to be taken into consideration for an adequate approach to this complication of peritoneal dialysis