Der deutsche Energiemarkt befindet sich weiterhin in einem transformativen Wandel. Insbesondere der Begriff „Smart Metering“ wird seit etlichen Jahren immer wieder durch die Medien getragen. Anfang 2020 wurde nun die erforderliche Rechtssicherheit geschaffen, sodass Investitionen durch Energieversorger in die entsprechende Hardware erfolgen können, und der Rollout von digitalen Stromzählern ins Rollen kommt. Damit einher geht das Potential der Erzeugung von zahlreichen neuen Daten über das Verbrauchsverhalten der privaten Endverbraucher. Diese können zur Vereinfachung von Abrechnungsprozessen genutzt werden, aber auch die Basis zur Visualisierung und Analyse des Verbrauchs bilden. Ebenfalls sind sie eine mögliche Grundlage für neue innovative Dienstleistungen, die insb. im Kontext der Verbrauchstransparenz vom Kunden auch gefordert werden. Für den Energieversorger können sich neue Einnahmequellen ergeben, sowie Optionen zur Festigung der Kundenbeziehung. Die vorliegende Publikation hat das Ziel einen besseren Einblick in die zwei wesentlichen Stakeholder zum Themenfeld Smart Metering zu vermitteln: in die Sichtweisen und Absichten der Energieversorger, sowie in die Bedürfnisse der privaten Endverbraucher. Die Informationen dazu werden nach einem Mixed-Methods-Ansatz literaturbasiert und durch weitere Methoden, bspw. Befragungen, erhoben. Diese Ergebnisse sind wichtig, um die Ausgangssituation umfassend zu verstehen und damit eine sinnvolle Grundlage für weitere Forschungsarbeiten zu legen. Dabei werden zunächst Webseiten der Energieversorger einer Inhaltsanalyse unterzogen und verfügbare Informationen extrahiert. Als Vertiefung wurde eine Befragung als quantitative Querschnittsanalyse mit der Zielgruppe deutsche Energieversorger aufgesetzt, und ein Stand zur aktuellen und geplanten Nutzung von Kundenportalen, Smart Metering und möglichen Zusatzangebote erhoben. Kundenbedürfnisse wurden zunächst literaturbasiert als Review erhoben, und systematisieren den Bedarf an Lösungen zur Verbrauchstransparenz sowie die konkreten Informationsbedürfnisse. Eine Erhebung unter 1.000 privaten Haushalten zeigt weitere Indikationen zum Umgang mit dem Stromverbrauch. Damit bestätigt die Untersuchung die Informationsbedarfe und damit die Relevanz von entsprechenden Zusatzangeboten.:Abstract I Inhaltsverzeichnis II Abbildungsverzeichnis V Tabellenverzeichnis VII 1 Einleitung 8 1.1 Hardware zur Umsetzung von Smart Metering 8 1.2 Zeitliche Entwicklung des Rollouts in Deutschland 9 1.3 Datennutzung aus dem Smart Metering 12 1.4 Vorhergehende Untersuchungen zur Vorbereitung des Forschungsfeldes 13 1.5 Forschungsdesign und Konzeption der Publikation 14 2 Analyse der Energieversorger in Deutschland 17 2.1 Aufbau der Untersuchung 17 2.2 Quantitative Inhaltsanalyse der Webseiten deutscher Energieversorger 17 2.2.1 Untersuchungsziel 17 2.2.2 Methodik 18 2.2.3 Ergebnisse 22 2.2.4 Zusammenfassung 25 2.3 Durchführung einer Befragung unter Energieversorgern 26 2.3.1 Untersuchungsziel 26 2.3.2 Methodik 26 2.3.3 Ergebnisse 30 2.3.3.1 Kundenportal vorhanden oder geplant (Block 1, G1Q00001-4) 30 2.3.3.2 Funktionen des Kundenportals (Block 1, G1Q00001-4) 32 2.3.3.3 Stand der Einführung von Smart Metering (Block 2, G2Q0001-20) 34 2.3.3.4 Hintergründe zur Einführung von SM (Block 2, G2Q0001-20) 35 2.3.3.5 Umfang der Einführung von SM (Block 2, G2Q0001-20) 39 2.3.3.6 Verarbeitung der Daten aus dem SM (Block 2, G2Q0001-20) 41 2.3.3.7 Zusatzangebote mit Daten aus dem SM (Block 2, G2Q0001-20) 44 2.3.3.8 Daten über die Befragungsteilnehmer (Block 3, G1Q00001-4) 46 2.3.4 Zusammenfassung 49 2.4 Durchführung der Wiederholung der Erhebung (2020) 51 2.4.1 Untersuchungsziel und Methodik 51 2.4.2 Struktur der Befragung 51 2.4.3 Ergebnisse 55 2.4.3.1 Block 1: Nutzung und Funktionen des Kundenportals 55 2.4.3.2 Block 2: Einführung und Umfänge von Smart Metering 57 2.4.3.3 Block 3: Verarbeitung und Nutzung von Daten aus dem SM 61 2.4.3.4 Block 4: Abschließende Informationen 64 2.4.4 Zusammenfassung 66 3 Analyse der privaten Haushalte 68 3.1 Aufbau der Untersuchung 68 3.2 Literaturbasierte Analyse der Kundenbedürfnisse 68 3.2.1 Untersuchungsziel 68 3.2.2 Methodik 69 3.2.3 Ergebnisse 71 3.2.4 Zusammenfassung 80 3.3 Durchführung einer Erhebung unter privaten Haushalten 81 3.3.1 Untersuchungsziel 81 3.3.2 Methodik 82 3.3.3 Ergebnisse 82 3.3.4 Zusammenfassung 84 4 Zusammenführung 85 4.1 Ergebnisse der Teiluntersuchungen 85 4.2 Nächste Schritte 89 4.3 Weitere Limitationen 89 5 Literatur 91 6 Anhang 101 6.1 Fragebogen-Items des Online-Fragebogens 2015 101 6.2 Einladungstexte zur Befragung 103 6.2.1 Einführungstext 103 6.2.2 Text zum Nachfassen / Erinnerung 104 6.2.3 Einführungstext der Wiederholung der Studie 2020 105

The thesis deals with PLC technology and issues with Smart Metering. In the theoretical part, a principle of technology's functionality and its advantages and disadvantages were described. In the experimental part methodology of data concentrator and electric meters was designed. In addition, extensive testing set according to capturing of DLMS communication, link quality influencing, reading registers of meters were realized. In the second experimental part limits of communications between broadband BPL modems were detected by the power line communication hardware channel emulator. Measurement of throughput, latency, frame loss passed off according to RCF 2544, RFC 6349 recommendation and according to the methodology of TCP Throughput In the last part, two laboratory exercises were created, first one deals with Smart Metering system and communication between the data concentrator and electric meters and the second one deals with communication among broadband BPL modems not only for Smart Metering purposes.

The thesis deals with the design of wireless communication system using Wireless M- Bus, which works in the 169 MHz band. This system is designed to collect data from meters that are not equipped with a radio and have pulse outputs. The thesis describes the Wireless M-Bus standard and the current components of the communication system used by ModemTec. It also describes the selection and design of a suitable hardware implementing the receiver and transmitter modules and the firmware design for these modules. The thesis deals with the parameterization of the transmitter module in order to specify the parameters of the transmitted measured quantity.

Non-residential users contribute to a significant portion of the total water delivered by water supplying agencies. However, a very limited number of studies have attempted to investigate the water use behavior of non-residential users. With the emergence of newer “smart” meters, water use now can be measured and recorded at a very high temporal frequency. Smart meters can help determine total water use, timing, and component end uses to better understand water use practices by non-residential users. Water end use disaggregation is the process of separating the water used by each fixture or process within a facility. This is useful because having a breakdown of the consumption of all end uses may encourage users to consume less water and gives them indications on how to do so. This project involved collecting and working with three different datasets with three different temporal scales (monthly billing data, 5-minute water use data, and 5-second water use data). We analyzed monthly billing data to solicit potential participating facilities for the study. For each participating facility, new smart devices were installed on their existing water meters, including an advanced water meter register and a pulse counting data logger. The newer registers logged and transmitted data to a web-accessible data portal at 5-minute intervals, while the pulse counters recorded water use at 5- second intervals. These devices enabled us to measure the timing and volume of different water uses (e.g., indoor versus outdoor versus industrial processes uses). In this project, we identified different water use events, average water used by each end use (from plumbing fixtures to industrial machinery), variability in end uses (faucets/toilets versus showers), variability in use by the type of user (manufacturing facilities versus assisted living homes), and the impact of the business type on the water use.

Yes / The introduction of smart metering has brought more detailed information on the actual load profile of a house. With the ability to measure, comes the desire to control the load profile. Furthermore, advances in renewable energy have made the consumer to become supplier, known as Prosumer, who therefore also becomes interested in the detail of his load, and also his energy production. With the lowering cost of smart plugs and other automation units, it has become possible to schedule electrical appliances. This makes it possible to adjust the load profiles of houses. However, without a market in the demand side, the use of load profile modification techniques are unlikely to be adapted by consumers on the long term. In this research, we will be presenting work on scheduling of energy appliances to modify the load profiles within a market environment. The paper will review the literature on algorithms used in scheduling of appliances in residential areas. Whilst many algorithms presented in the literature show that scheduling of appliances is feasible, many issues arise with respect to user interaction, and hence adaptation. Furthermore, the criteria used to evaluate the algorithms is often related only to reducing energy consumption, and hence CO2. Whilst this a key factor, it may not necessarily meet the demands of the consumer. In this paper we will be presenting work on a novel genetic algorithm that will optimize the load profile while taking into account user participation indices. A novel measure of the comfort of the customer, derived from the standard deviation of the load profile, is proposed in order to encourage the customer to participate more actively in demand response programs. Different scenarios will also be tested. / This work was supported by the British Council and the UK Department of Business Innovation and Skills under GII funding for the SITARA project.

Internet of Things (IoT) is a revolutionary paradigm approaching both industries and consumers everyday life. It refers to a network of addressable physical objects that contain embedded sensing, communication and actuating technologies, to sense and interact with the environment where being deployed. It can be considered as a modern expression of Mark Weiser's vision of ubiquitous computing where tiny networked computers become part of everyday objects, fusing together the virtual world and the physical word. Recent advances in hardware solutions have led to the emergence of powerful wireless IoT systems that are entirely energy-autonomous. These systems extract energy from their environment and operate intermittently, only as power is available. Battery-less sensors present an opportunity for the pervasive wide-spread of remote sensor deployments that require little maintenance and have low cost. As the number of IoT endpoint grows -- industry forecast trillions of connected smart devices in the next few years -- new challenges to program, manage and maintain such a huge number of connected devices are emerging. Web technologies can significantly ease this process by providing well-known patterns and tools - like cloud computing - for developers and users. However, the existing solutions are often too heavyweight or unfeasible for highly resource-constrained IoT devices. This dissertation presents a comprehensive analysis of two of the biggest problems that the IoT is currently facing: R1) How are we going to provide connectivity to all these devices? R2) How can we improve the quality of service provided by these tiny autonomous motes that rely only on limited energy scavenged from the environment? The first contribution is the study and deployment of a Low-Power Wide-Area-Network as a feasible solution to provide connectivity to all the expected IoT devices to be deployed in the following years. The proposed technology offers a novel communication paradigm to address discrete IoT applications, like long-range (i.e., kilometers) at low-power (i.e., tens of mW). Moreover, results highlight the effectiveness of the technology also in the industrial environment thanks to the high immunity to external noises. In the second contribution, we focus on smart metering presenting the design of three smart energy meters targeted to different scenarios. The first design presents an innovative, cost-effective smart meter with embedded non-intrusive load monitoring capabilities intended for the domestic sector. This system shows an innovative approach to provide useful feedback to reduce and optimize household energy consumption. We then present a battery-free non-intrusive power meter targeted for low-cost energy monitoring applications that lower both installation cost due to the non-intrusive approach and maintenance costs associated to battery replacement. Finally, we present an energy autonomous smart sensor with load recognition capability that dynamically adapts and reconfigures its processing pipeline to the sensed energy consumption. This enables the sensor to be energy neutral, while still providing power consumption information every 5 minutes. In the third contribution, we focus on the study of low-power visual edge processing and edge machine learning for the IoT. Two different implementations are presented. The first one discusses an energy-neutral IoT device for precision agriculture, while the second one presents a battery-less long-range visual IoT system, both leveraging on deep learning algorithms to avoid unnecessary wireless data communication. We show that there is a clear benefit from implementing a first layer of data processing directly in-situ where the data is acquired, providing a higher quality of service to the implemented application.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / This Master s dissertation presents the development of a methodology to evaluate and estimate the behavior of the residential consumer facing the application of the white hourly tariff. In the context of the Smart Grids, this rate is applied aiming to encourage the consumers to shift their consumption to times of lower loading of system, looking for a better utilization of the infrastructure of the electric system. Considering this, the proposed methodology considers the analysis about the habits of use of electric shower, which is the household equipment that presents the greatest contribution on the final consumption and on the peak of the load curve of residential consumers. In this way the analysis considers data from the Brazilian Center of Information in Energy Efficiency - PROCEL INFO, which includes information about habits of use of household. This database, combined with the application of the Monte Carlo method, provide an overview of the possible effects of the application of the hourly rate to the consumers and to the electrical system, as well as, a guideline of actions that can be taken for a better adaptation of the consumers, considering this new trend. / Esta dissertação apresenta o desenvolvimento de uma metodologia para avaliar e estimar o comportamento do consumidor residencial frente a aplicação da tarifa horária branca. No contexto das Redes Elétricas Inteligentes, esta tarifa visa incentivar os consumidores a deslocarem o seu consumo para horários de menor carregamento do sistema e, consequentemente, buscar um melhor aproveitamento da infraestrutura do sistema elétrico. Neste sentido, a metodologia proposta considera a análise sobre os hábitos de utilização do chuveiro elétrico, carga com maior representatividade no consumo final e na ponta da curva de carga dos consumidores residenciais. Desta forma, são utilizados dados do Centro Brasileiro de Informação de Eficiência Energética PROCEL INFO, que reúne uma base de informações sobre os hábitos de utilização de equipamentos oriunda de pesquisas realizadas no mercado residencial brasileiro no ano de 2005. Esta base de dados, aliada a aplicação do Método de Monte Carlo, fornece uma visão dos possíveis efeitos da aplicação da tarifa horária para o consumidor e para o sistema elétrico, assim como, nortear ações que possam ser tomadas em função de uma melhor adaptação do consumidor frente a esta nova tendência.

In the European Union (EU), increasing final energy efficiency, so as to save energy, has become mandatory. This obligation will fundamentally alter the EU energy sector. The relevant EU directive, 2006/32/EG, requires that adjustments be made to energy billing and, where technically feasible, that new metering technologies (i.e. smart metering) be introduced. Individual EU countries are implementing these requirements in different ways: Smart metering is either being nearly fully implemented (e.g. in Italy), is being planned (e.g. in Germany), or completely disregarded (e.g. in the Czech Republic). Since the introduction of smart metering affects virtually all value-added steps, organisational structures and areas of operation in medium-sized energy providers, these providers must take the relevant requirements into account at as early a stage as possible. The present thesis analyses the effects of the introduction of smart metering on the business management of such companies. A deductive method was chosen and the effects of intro- ducing smart metering were assessed through a cross-sectional study of two separate data collections. Experts were interviewed and their statements were qualitatively evaluated. A written survey followed via online questionnaires, the results of which were quantitatively evaluated. Institutional, functional and activity-based perspectives were considered as well as normative, strategic and operative aspects of business management. The evaluation of the survey enabled a better assessment and analysis of the introduction of smart metering. An analysis of the scope of the upcoming alterations within energy providers illustrates just how fundamental a change this will bring to medium-sized energy providers. However, the outcome of the written survey shows that most executives do not recognise this need for change and therefore are unable to initiate it. These management deficiencies threaten the very existence of these companies and must be resolved through the timely initiation of consistent change management.

Beschlossen 2015 im Gesetzesentwurf zur Digitalisierung der Energiewende (s. BMWi (2015a)) sollen verstärkt Smart Meter ausgerollt werden. Diese digitalen Stromzähler bestehen aus einem digitalen Zählwerk sowie einer Kommunikationseinheit, welche eine sichere und standardisierte Kommunikation ermöglichen soll. Die Smart Meter erfassen und veranschaulichen den aktuellen Verbrauch und können zusätzlich sogar simultan die momentane Erzeugung von Energie, z. B. durch eine Solaranlage, erfassen. Durch die ständige Erfassung des aktuellen Energieverbrauchs, verbunden mit der Übermittlungsfunktion an den EVU, kann dem Kunden unmittelbar sein aktueller Verbrauch aufgezeigt werden – eine wesentliche Grundlage für Transparenz im Verbrauch, Datenauswertungen und Startpunkt für Verbrauchsoptimierungen (vgl. BMWi (2015b); Fox (2010), S. 408). [... aus Punkt 1.2]

[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. / [CAT] 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/10251/59236 / TESIS