An Electricity Price-Aware Open-Source Smart Socket for the Internet of Energy

[Abstracts] The Internet of Energy (IoE) represents a novel paradigm where electrical power systems work cooperatively with smart devices to increase the visibility of energy consumption and create safer, cleaner and sustainable energy systems. The implementation of IoE services involves the use of multiple components, like embedded systems, power electronics or sensors, which are an essential part of the infrastructure dedicated to the generation and distribution energy and the one required by the final consumer. This article focuses on the latter and presents a smart socket system that collects the information about energy price and makes use of sensors and actuators to optimize home energy consumption according to the user preferences. Specifically, this article provides three main novel contributions. First, what to our knowledge is the first hardware prototype that manages in a practical real-world scenario the price values obtained from a public electricity operator is presented. The second contribution is related to the definition of a novel wireless sensor network communications protocol based on Wi-Fi that allows for creating an easy-to-deploy smart plug system that self-organizes and auto-configures to collect the sensed data, minimizing user intervention. Third, it is provided a thorough description of the design of one of the few open-source smart plug systems, including its communications architecture, the protocols implemented, the main sensing and actuation components and the most relevant pieces of the software. Moreover, with the aim of illustrating the capabilities of the smart plug system, the results of different experiments performed are shown. Such experiments evaluate in real-world scenarios the system’s ease of use, its communications range and its performance when using HTTPS. Finally, the economic savings are estimated for different appliances, concluding that, in the practical situation proposed, the smart plug system allows certain energy-demanding appliances to save almost €70 per yearGalicia. Consellería de Cultura, Educación e Ordenación Universitaria; ED431C 2016-045Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; ED341D R2016/012Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; ED431G/01Agencia Estatal de Investigación; TEC2013-47141-C4-1-RAgencia Estatal de Investigación; TEC2015-69648-REDCAgencia Estatal de Investigación; TEC2016-75067-C4-1-

A model personal energy meter

Every day each of us consumes a significant amount of energy, both directly through transport, heating and use of appliances, and indirectly from our needs for the production of food, manufacture of goods and provision of services. This dissertation investigates a personal energy meter which can record and apportion an individual's energy usage in order to supply baseline information and incentives for reducing our environmental impact. If the energy costs of large shared resources are split evenly without regard for individual consumption each person minimises his own losses by taking advantage of others. Context awareness offers the potential to change this balance and apportion energy costs to those who cause them to be incurred. This dissertation explores how sensor systems installed in many buildings today can be used to apportion energy consumption between users, including an evaluation of a range of strategies in a case study and elaboration of the overriding principles that are generally applicable. It also shows how second-order estimators combined with location data can provide a proxy for fine-grained sensing. A key ingredient for apportionment mechanisms is data on energy usage. This may come from metering devices or buildings directly, or from profiling devices and using secondary indicators to infer their power state. A mechanism for profiling devices to determine the energy costs of specific activities, particularly applicable to shared programmable devices is presented which can make this process simpler and more accurate. By combining crowdsourced building-inventory information and a simple building energy model it is possible to estimate an individual's energy use disaggregated by device class with very little direct sensing. Contextual information provides crucial cues for apportioning the use and energy costs of resources, and one of the most valuable sources from which to infer context is location. A key ingredient for a personal energy meter is a low cost, low infrastructure location system that can be deployed on a truly global scale. This dissertation presents a description and evaluation of the new concept of inquiry-free Bluetooth tracking that has the potential to offer indoor location information with significantly less infrastructure and calibration than other systems. Finally, a suitable architecture for a personal energy meter on a global scale is demonstrated using a mobile phone application to aggregate energy feeds based on the case studies and technologies developed

Energy Efficiency in Public Buildings through Context-Aware Social Computing

[EN]The challenge of promoting behavioral changes in users that leads to energy savings in public buildings has become a complex task requiring the involvement of multiple technologies. Wireless sensor networks have a great potential for the development of tools, such as serious games, that encourage acquiring good energy and healthy habits among users in the workplace. This paper presents the development of a serious game using CAFCLA, a framework that allows for integrating multiple technologies, which provide both context-awareness and social computing. Game development has shown that the data provided by sensor networks encourage users to reduce energy consumption in their workplace and that social interactions and competitiveness allow for accelerating the achievement of good results and behavioral changes that favor energy savings.European Commision (EC). Funding H2020/MSCARISE. Project Code: 64179

Building Information Modelling : Indoor Localization

This thesis presents an integrated system where BIM software is used together with IoT devices to visualize data generated in real-time. Two different IoT devices are modelled as case study that collect environmental and localization data. These devices were installed inside a Test room of an area approx. 22 m2 in UiT Narvik premises . The collected data were, filtered & transferred to database server which were then retrieved and visualized by BIM software in real time. The report presents tools and technologies that are implemented to develop such system and provides details on basic blocks required for such integrations. The combined platform visualize information about the things as it happens in real-time. This makes such systems capable for digitalization of physical process and have various application domains. In the report it is applied as monitoring platform for temperature and illumination data and can be used for facility management applications. Similarly, indoor localization is monitored making it applicable for localization and safety management purpose. The performance of the system is also discussed based on test, observations, and calculation

Multi-User Low Intrusive Occupancy Detection

Smart spaces are those that are aware of their state and can act accordingly. Among the central elements of such a state is the presence of humans and their number. For a smart office building, such information can be used for saving energy and safety purposes. While acquiring presence information is crucial, using sensing techniques that are highly intrusive, such as cameras, is often not acceptable for the building occupants. In this paper, we illustrate a proposal for occupancy detection which is low intrusive; it is based on equipment typically available in modern offices such as room-level power-metering and an app running on workers’ mobile phones. For power metering, we collect the aggregated power consumption and disaggregate the load of each device. For the mobile phone, we use the Received Signal Strength (RSS) of BLE (Bluetooth Low Energy) nodes deployed around workspaces to localize the phone in a room. We test the system in our offices. The experiments show that sensor fusion of the two sensing modalities gives 87–90% accuracy, demonstrating the effectiveness of the proposed approach

Model Predictive Energy Management for Building Microgrids with IoT-based Controllable Loads

This thesis develops an economic scheduling framework for a building microgrid with internet of things (IoT) based flexible loads to synchronize the buildings’ controllable components, with occupant behavior and environmental conditions. We employ model predictive control (MPC) methods to minimize building operating costs, while maximizing the utilization of the on-site resources. The main research thrusts are: 1) Developing the building microgrid model; 2) Defining different building operation strategies; 3) Minimizing the building’s daily operating costs. Simulation results show that the proposed approach provides superior energy cost savings and peak load reduction in comparison with other operation controls, such as All from Utility (AFU), AFU with installed IoT-based Building Energy Management System (BEMS), and MPC-Mix Integer Linear Programming (MILP) without IoT-based BEMS. An economic analysis is also conducted to provide a road map for the implementation of installing advanced energy efficiency technologies across loads in building microgrid and integrating them with the building microgrid’s control strategy

Home Automation System based on Intelligent Transducer Enablers

This paper presents a novel home automation system named HASITE (Home Automation System based on Intelligent Transducer Enablers), which has been specifically designed to identify and configure transducers easily and quickly. These features are especially useful in situations where many transducers are deployed, since their setup becomes a cumbersome task that consumes a significant amount of time and human resources. HASITE simplifies the deployment of a home automation system by using wireless networks and both self-configuration and self-registration protocols. Thanks to the application of these three elements, HASITE is able to add new transducers by just powering them up. According to the tests performed in different realistic scenarios, a transducer is ready to be used in less than 13 s. Moreover, all HASITE functionalities can be accessed through an API, which also allows for the integration of third-party systems. As an example, an Android application based on the API is presented. Remote users can use it to interact with transducers by just using a regular smartphone or a tablet.Comment: 27 pages, 17 figures, accepted version of Sensors journal articl

Smart home technology for aging

The majority of the growing population, in the US and the rest of the world requires some degree of formal and or informal care either due to the loss of function or failing health as a result of aging and most of them suffer from chronic disorders. The cost and burden of caring for elders is steadily increasing. This thesis focuses on providing the analysis of the technologies with which a Smart Home is built to improve the quality of life of the elderly. A great deal of emphasis is given to the sensor technologies that are the back bone of these Smart Homes. In addition to the Analysis of these technologies a survey of commercial sensor products and products in research that are concerned with monitoring the health of the occupants of the Smart Home is presented. A brief analysis on the communication technologies which form the communication infrastructure for the Smart Home is also illustrated. Finally, System Architecture for the Smart Home is proposed describing the functionality and users of the system. The feasibility of the system is also discussed. A scenario measuring the blood glucose level of the occupant in a Smart Home is presented as to support the system architecture presented

Técnicas de computación social e información contextual para el desarrollo de actividades de aprendizaje colaborativo

[EN]Educational innovation is a field in which its processes has been greatly enriched by the use of Information and Communication Technologies (ICT). Thanks to technological advances, the use of learning models where information comes from many different sources is now usual. Likewise, student-student, student-device and device-device collaborations provides added value to the learning processes thanks to the fact that, through it, aspects such as communication, achievement of common goals or sharing resources. Within the educational innovation, we find as a great challenge the development of tools that facilitate the creation of innovative collaborative learning processes that improve the achievement of the objectives sought, with respect to individualized processes, and the fidelity of the students to the process through the use of contextual information. Moreover, the development of these solutions, that facilitate the work of teachers, developers and technicians encouraging the production of educational processes more attractive to students, presents itself as an ambitious challenge in which the perspectives of Ambient Intelligence and Social Computing play a key role. The doctoral dissertation presented here describes and evaluates CAFCLA, a framework specially conceived for the design, development and implementation of collaborative learning activities that make use of contextual information and that is based on the paradigms of Ambient Intelligence and Social Computing. CAFCLA is a flexible framework that covers the entire process of developing collaborative learning activities and hides all the difficulties involved in the use and integration of multiple technologies to its users. In order to evaluate the validity of the proposal, CAFCLA has supported the implementation of three concrete and different use cases. These experimental use cases have shown that, among other benefits, the use of Social Computing customizes the learning process, encourages collaboration, improves relationships, increases commitment, promotes behaviour change in users and enables learning to be maintained over time. In addition, in order to demonstrate the flexibility of the framework, these use cases have been developed in different scenarios (such as a museum, a public building or at home), different types of learning have been proposed (serious games, recommendations system orWebQuest) and different learning objectives have been chosen (academic, social and energy-efficient).[ES]La innovación educativa es un campo que ha sido enormemente enriquecido por el uso de las Tecnologías de la Información y las Comunicaciones (TIC) en sus procesos. Gracias a los avances tecnológicos, actualmente es habitual el uso de modelos de aprendizaje donde la información proviene de numerosas y diferentes fuentes. De igual forma, la colaboración estudiante-estudiante, estudiante-dispositivo y dispositivo-dispositivo, proporciona un valor añadido a los procesos de aprendizaje gracias a que, a través de ella, se fomentan aspectos como la comunicación, la consecución de una meta común, o la compartición de recursos. Dentro de la innovación educativa encontramos como un gran desafío el desarrollo de herramientas que faciliten la creación de procesos de aprendizaje colaborativo innovadores que mejoren los resultados obtenidos, respecto a los procesos individualizados, y la fidelidad de los estudiantes al proceso mediante el uso de información contextual.Más aún, el desarrollo de soluciones que faciliten el trabajo a profesores, desarrolladores y técnicos, fomentando la producción de procesos educativos más atractivos para los estudiantes, se presenta como un ambicioso reto en el que las perspectivas de la Inteligencia Ambiental y la Computación Social juegan un papel fundamental. La tesis doctoral aquí presentada describe y evalúa CAFCLA, un framework especialmente concebido para el diseño, desarrollo e implementación de actividades de aprendizaje colaborativo que hagan uso de información contextual basándose en los paradigmas de la Inteligencia Ambiental y la Computación Social. CAFCLA es un framework flexible que abarca todo el proceso de desarrollo de actividades de aprendizaje colaborativo y oculta todas las dificultades que implican el uso e integración de múltiples tecnologías a sus usuarios. Para evaluar la validez de la propuesta realizada, CAFCLA ha soportado la implementación de tres casos de uso concretos y diferentes entre sí. Estos casos de uso experimentales han demostrado que, entre otros beneficios, el uso de la Computación Social personaliza el proceso de aprendizaje, fomenta la colaboración, mejora las relaciones, aumenta el compromiso, favorecen el cambio de comportamiento en los usuarios y mantiene su implicación en el proceso a lo largo del tiempo. Además, con el objetivo de demostrar la flexibilidad del framework, estos casos de uso se han desarrollado en diferentes escenarios (como un museo, un edificio público o el hogar), se han propuesto diferente tipos de aprendizaje (juegos serios, sistema de recomendaciones o WebQuest) y se han elegido diferentes objetivos de aprendizaje (académicos, sociales y de eficiencia energética)

μGIM - Microgrid intelligent management system based on a multi-agent approach and the active participation of end-users

[ES] Los sistemas de potencia y energía están cambiando su paradigma tradicional, de sistemas centralizados a sistemas descentralizados. La aparición de redes inteligentes permite la integración de recursos energéticos descentralizados y promueve la gestión inclusiva que involucra a los usuarios finales, impulsada por la gestión del lado de la demanda, la energía transactiva y la respuesta a la demanda. Garantizar la escalabilidad y la estabilidad del servicio proporcionado por la red, en este nuevo paradigma de redes inteligentes, es más difícil porque no hay una única sala de operaciones centralizada donde se tomen todas las decisiones. Para implementar con éxito redes inteligentes, es necesario combinar esfuerzos entre la ingeniería eléctrica y la ingeniería informática. La ingeniería eléctrica debe garantizar el correcto funcionamiento físico de las redes inteligentes y de sus componentes, estableciendo las bases para un adecuado monitoreo, control, gestión, y métodos de operación. La ingeniería informática desempeña un papel importante al proporcionar los modelos y herramientas computacionales adecuados para administrar y operar la red inteligente y sus partes constituyentes, representando adecuadamente a todos los diferentes actores involucrados. Estos modelos deben considerar los objetivos individuales y comunes de los actores que proporcionan las bases para garantizar interacciones competitivas y cooperativas capaces de satisfacer a los actores individuales, así como cumplir con los requisitos comunes con respecto a la sostenibilidad técnica, ambiental y económica del Sistema. La naturaleza distribuida de las redes inteligentes permite, incentiva y beneficia enormemente la participación activa de los usuarios finales, desde actores grandes hasta actores más pequeños, como los consumidores residenciales. Uno de los principales problemas en la planificación y operación de redes eléctricas es la variación de la demanda de energía, que a menudo se duplica más que durante las horas pico en comparación con la demanda fuera de pico. Tradicionalmente, esta variación dio como resultado la construcción de plantas de generación de energía y grandes inversiones en líneas de red y subestaciones. El uso masivo de fuentes de energía renovables implica mayor volatilidad en lo relativo a la generación, lo que hace que sea más difícil equilibrar el consumo y la generación. La participación de los actores de la red inteligente, habilitada por la energía transactiva y la respuesta a la demanda, puede proporcionar flexibilidad en desde el punto de vista de la demanda, facilitando la operación del sistema y haciendo frente a la creciente participación de las energías renovables. En el ámbito de las redes inteligentes, es posible construir y operar redes más pequeñas, llamadas microrredes. Esas son redes geográficamente limitadas con gestión y operación local. Pueden verse como áreas geográficas restringidas para las cuales la red eléctrica generalmente opera físicamente conectada a la red principal, pero también puede operar en modo isla, lo que proporciona independencia de la red principal. Esta investigación de doctorado, realizada bajo el Programa de Doctorado en Ingeniería Informática de la Universidad de Salamanca, aborda el estudio y el análisis de la gestión de microrredes, considerando la participación activa de los usuarios finales y la gestión energética de lascarga eléctrica y los recursos energéticos de los usuarios finales. En este trabajo de investigación se ha analizado el uso de conceptos de ingeniería informática, particularmente del campo de la inteligencia artificial, para apoyar la gestión de las microrredes, proponiendo un sistema de gestión inteligente de microrredes (μGIM) basado en un enfoque de múltiples agentes y en la participación activa de usuarios. Esta solución se compone de tres sistemas que combinan hardware y software: el emulador de virtual a realidad (V2R), el enchufe inteligente de conciencia ambiental de Internet de las cosas (EnAPlug), y la computadora de placa única para energía basada en el agente (S4E) para permitir la gestión del lado de la demanda y la energía transactiva. Estos sistemas fueron concebidos, desarrollados y probados para permitir la validación de metodologías de gestión de microrredes, es decir, para la participación de los usuarios finales y para la optimización inteligente de los recursos. Este documento presenta todos los principales modelos y resultados obtenidos durante esta investigación de doctorado, con respecto a análisis de vanguardia, concepción de sistemas, desarrollo de sistemas, resultados de experimentación y descubrimientos principales. Los sistemas se han evaluado en escenarios reales, desde laboratorios hasta sitios piloto. En total, se han publicado veinte artículos científicos, de los cuales nueve se han hecho en revistas especializadas. Esta investigación de doctorado realizó contribuciones a dos proyectos H2020 (DOMINOES y DREAM-GO), dos proyectos ITEA (M2MGrids y SPEAR), tres proyectos portugueses (SIMOCE, NetEffiCity y AVIGAE) y un proyecto con financiación en cascada H2020 (Eco-Rural -IoT)