The role of communication systems in smart grids: Architectures, technical solutions and research challenges

The purpose of this survey is to present a critical overview of smart grid concepts, with a special focus on the role that communication, networking and middleware technologies will have in the transformation of existing electric power systems into smart grids. First of all we elaborate on the key technological, economical and societal drivers for the development of smart grids. By adopting a data-centric perspective we present a conceptual model of communication systems for smart grids, and we identify functional components, technologies, network topologies and communication services that are needed to support smart grid communications. Then, we introduce the fundamental research challenges in this field including communication reliability and timeliness, QoS support, data management services, and autonomic behaviors. Finally, we discuss the main solutions proposed in the literature for each of them, and we identify possible future research directions

Enhancing the efficiency of electricity utilization through home energy management systems within the smart grid framework

The concept behind smart grids is the aggregation of “intelligence” into the grid, whether through communication systems technologies that allow broadcast/data reception in real-time, or through monitoring and systems control in an autonomous way. With respect to the technological advancements, in recent years there has been a significant increment in devices and new strategies for the implementation of smart buildings/homes, due to the growing awareness of society in relation to environmental concerns and higher energy costs, so that energy efficiency improvements can provide real gains within modern society. In this perspective, the end-users are seen as active players with the ability to manage their energy resources, for example, microproduction units, domestic loads, electric vehicles and their participation in demand response events. This thesis is focused on identifying application areas where such technologies could bring benefits for their applicability, such as the case of wireless networks, considering the positive and negative points of each protocol available in the market. Moreover, this thesis provides an evaluation of dynamic prices of electricity and peak power, using as an example a system with electric vehicles and energy storage, supported by mixed-integer linear programming, within residential energy management. This thesis will also develop a power measuring prototype designed to process and determine the main electrical measurements and quantify the electrical load connected to a low voltage alternating current system. Finally, two cases studies are proposed regarding the application of model predictive control and thermal regulation for domestic applications with cooling requirements, allowing to minimize energy consumption, considering the restrictions of demand, load and acclimatization in the system

Smart Urban Water Networks

This book presents the paper form of the Special Issue (SI) on Smart Urban Water Networks. The number and topics of the papers in the SI confirm the growing interest of operators and researchers for the new paradigm of smart networks, as part of the more general smart city. The SI showed that digital information and communication technology (ICT), with the implementation of smart meters and other digital devices, can significantly improve the modelling and the management of urban water networks, contributing to a radical transformation of the traditional paradigm of water utilities. The paper collection in this SI includes different crucial topics such as the reliability, resilience, and performance of water networks, innovative demand management, and the novel challenge of real-time control and operation, along with their implications for cyber-security. The SI collected fourteen papers that provide a wide perspective of solutions, trends, and challenges in the contest of smart urban water networks. Some solutions have already been implemented in pilot sites (i.e., for water network partitioning, cyber-security, and water demand disaggregation and forecasting), while further investigations are required for other methods, e.g., the data-driven approaches for real time control. In all cases, a new deal between academia, industry, and governments must be embraced to start the new era of smart urban water systems

An Approach to Guide Users Towards Less Revealing Internet Browsers

When browsing the Internet, HTTP headers enable both clients and servers send extra data in their requests or responses such as the User-Agent string. This string contains information related to the sender’s device, browser, and operating system. Previous research has shown that there are numerous privacy and security risks result from exposing sensitive information in the User-Agent string. For example, it enables device and browser fingerprinting and user tracking and identification. Our large analysis of thousands of User-Agent strings shows that browsers differ tremendously in the amount of information they include in their User-Agent strings. As such, our work aims at guiding users towards using less exposing browsers. In doing so, we propose to assign an exposure score to browsers based on the information they expose and vulnerability records. Thus, our contribution in this work is as follows: first, provide a full implementation that is ready to be deployed and used by users. Second, conduct a user study to identify the effectiveness and limitations of our proposed approach. Our implementation is based on using more than 52 thousand unique browsers. Our performance and validation analysis show that our solution is accurate and efficient. The source code and data set are publicly available and the solution has been deployed

Modelamiento y simulación de redes de telecomunicación para medición inteligente de energía eléctrica residencial en zonas urbanas

This thesis project allows us to analyze the behavior of the telecommunications network in urban areas; and thus warn the needed infrastructure to implement smart metering of electricity. To this end, a mathematical optimization model to minimize distances was raised as a method to cluster-unite devices (smart meters) within an urban area cellular coverage. For this, modeling must be adapted to the behavior of the cellular network, so that facilitates us to minimize the economic impact by implementing smart metering from scratch. Smart metering devices shall assume the sending and receiving data over cellular networks offered by operators of advanced mobile services which may be present in the same primary dealer or reducing infrastructure costs in a secondary operator through leasing. Due to the nature of these communications infrastructure is important to consider that an urban area involve determinants factors for data transfer behavior; for this reason, the network behavior parameters based on base station and smart meters transmission power, channel assignment and simulator propagation models are simulated.El presente proyecto de tesis, nos permite analizar el comportamiento de la red de telecomunicaciones en zonas urbana; así de esta manera advertir las necesidades para implementar la infraestructura de medición inteligente de electricidad. Para lograr este propósito, se planteó un modelo de optimización matemática para la minimización de distancias como método para conglomerar-aglutinar dispositivos (medidores inteligentes) dentro de una zona de cobertura celular urbana. Para este modelamiento se debe adaptar al comportamiento de la red celular, de tal manera que nos facilite minimizar el impacto económico por la implementación de medición inteligente desde cero. Los dispositivos de medición inteligente deberán asumir el envío y recepción de datos a través de las redes celulares ofertadas por las operadoras del servicio móvil avanzado que pueden estar presentes en el mismo operador primario o reduciendo costos de infraestructura en un operador secundario a través del arrendamient

Security and Privacy Threats on Mobile Devices through Side-Channels Analysis

In recent years, mobile devices (such as smartphones and tablets) have become essential tools in everyday life for billions of people all around the world. Users continuously carry such devices with them and use them for daily communication activities and social network interactions. Hence, such devices contain a huge amount of private and sensitive information. For this reason, mobile devices become popular targets of attacks. In most attack settings, the adversary aims to take local or remote control of a device to access user sensitive information. However, such violations are not easy to carry out since they need to leverage a vulnerability of the system or a careless user (i.e., install a malware app from an unreliable source). A different approach that does not have these shortcomings is the side-channels analysis. In fact, side-channels are physical phenomenon that can be measured from both inside or outside a device. They are mostly due to the user interaction with a mobile device, but also to the context in which the device is used, hence they can reveal sensitive user information such as identity and habits, environment, and operating system itself. Hence, this approach consists of inferring private information that is leaked by a mobile device through a side-channel. Besides, side-channel information is also extremely valuable to enforce security mechanisms such as user authentication, intrusion and information leaks detection. This dissertation investigates novel security and privacy challenges on the analysis of side-channels of mobile devices. This thesis is composed of three parts, each focused on a different side-channel: (i) the usage of network traffic analysis to infer user private information; (ii) the energy consumption of mobile devices during battery recharge as a way to identify a user and as a covert channel to exfiltrate data; and (iii) the possible security application of data collected from built-in sensors in mobile devices to authenticate the user and to evade sandbox detection by malware. In the first part of this dissertation, we consider an adversary who is able to eavesdrop the network traffic of the device on the network side (e.g., controlling a WiFi access point). The fact that the network traffic is often encrypted makes the attack even more challenging. Our work proves that it is possible to leverage machine learning techniques to identify user activity and apps installed on mobile devices analyzing the encrypted network traffic they produce. Such insights are becoming a very attractive data gathering technique for adversaries, network administrators, investigators and marketing agencies. In the second part of this thesis, we investigate the analysis of electric energy consumption. In this case, an adversary is able to measure with a power monitor the amount of energy supplied to a mobile device. In fact, we observed that the usage of mobile device resources (e.g., CPU, network capabilities) directly impacts the amount of energy retrieved from the supplier, i.e., USB port for smartphones, wall-socket for laptops. Leveraging energy traces, we are able to recognize a specific laptop user among a group and detect intruders (i.e., user not belonging to the group). Moreover, we show the feasibility of a covert channel to exfiltrate user data which relies on temporized energy consumption bursts. In the last part of this dissertation, we present a side-channel that can be measured within the mobile device itself. Such channel consists of data collected from the sensors a mobile device is equipped with (e.g., accelerometer, gyroscope). First, we present DELTA, a novel tool that collects data from such sensors, and logs user and operating system events. Then, we develop MIRAGE, a framework that relies on sensors data to enhance sandboxes against malware analysis evasion

Bit Bang 8: Digitalization

This book is the 8th in the Bit Bang series of books produced as multidisciplinary teamwork exercises by doctoral students participating in the course Bit Bang 8: Digitalization at Aalto University during the academic year 2015–2016. Digitalization has brought great opportunities for economic growth, productivity gain and job creation in our societies, and will change the way industry will operate. Bit Bang 8 addressed the topic of digitalization from the perspective of its economic, environmental and social sustainability. The course elaborated on the interconnectedness of these phenomena, and linked them to possible future scenarios, global megatrends and ethical considerations. How will digitalization shape our future? How can we prepare can prepare our societies to respond to these changes? Working in teams, the students set out to answer questions related to the digitalization and to brainstorm radical scenarios of what the future could hold. This joint publication contains articles produced as teamwork assignments for the course, in which the students were encouraged to take novel and radical views on digitalization. The Bit Bang series of courses is supported by the Multidisciplinary Institute of Digitalisation and Energy (MIDE). Previous Bit Bang publications are available from http:/mide.aalto.fi

Aportaciones a la monitorización y predicción del recurso solar para la integración de fuentes renovables en sistemas eléctricos basadas en internet de las cosas

[SPA] Esta tesis doctoral se presenta bajo la modalidad de compendio de publicaciones. La necesidad de lograr una economía descarbonizada para evitar los efectos del cambio climático ha derivado en una serie de compromisos internacionales que obligan a España y Europa a reducir paulatinamente sus emisiones de gases de efecto invernadero hasta alcanzar la neutralidad climática en 2050. Este objetivo solo se puede alcanzar con un nuevo modelo energético basado en una integración masiva de energías renovables. Entre las tecnologías llamadas a convertirse en uno de los pilares de esta descarbonización de la economía se encuentra la energía solar fotovoltaica como consecuencia de su propia madurez tecnológica y la significativa reducción de costes que ha experimentado en los últimos años. Dentro de las instalaciones fotovoltaicas, una de las tipologías que ha recibido un mayor impulso son las instalaciones de autoconsumo ubicadas cerca de los puntos de demanda eléctrica gestionadas por los consumidores que pasan a ser también proveedores de energía y servicios a la red convirtiéndose en los denominados “prosumers“. Esta integración masiva de nuevas plantas de generación distribuida supone un desafío para la gestión de la red eléctrica que, tradicionalmente, ha respondido a un modelo de flujo de potencias unidireccional donde la potencia fluye desde grandes unidades de generación hacia los puntos de consumo, ajustando en todo momento la generación a la demanda y consiguiendo un balance de potencias que permitiese regular y controlar de manera efectiva los valores de tensión y frecuencia dentro de rangos admisibles. El nuevo modelo de generación distribuida basada en renovables requiere de nuevas herramientas y estrategias de gestión para hacer frente a la variabilidad que presentan estas energías renovables por su propia naturaleza y el gran número y dispersión geográfica de instalaciones que requieren una mayor flexibilidad ante nuevos retos en forma de flujo bidireccional de energía. Estas nuevas estrategias de gestión están apoyadas por los grandes avances realizados por las tecnologías de la información y la comunicación (TICs), que se han ido incorporando de forma paulatina de la mano de los operadores de red de cara a recoger diversas variables relacionadas con los estados de las unidades de generación y de los usuarios con objeto de optimizar la distribución y el consumo. En el caso de la fotovoltaica, hasta hace unos años, el coste y la complejidad de los sistemas de monitorización de las instalaciones fotovoltaicas limitaban su uso a las plantas fotovoltaicas de gran capacidad (a partir de 1 MW, tanto por motivos económicos como normativos), pero la aparición y la rápida evolución en el mercado del denominado Internet de las Cosas, IoT por sus siglas en inglés (Internet of Things), ha causado una explosión en la cantidad y variedad de soluciones de bajo costo que podrían permitir la implementación a gran escala de los sistemas de monitorización de manera rentable. Durante el desarrollo de esta tesis, de carácter eminentemente práctico, se ha trabajado en las tres capas que componen un sistema de IoT (percepción, comunicación y aplicación) para proponer un nuevo prototipo de gestión y comunicación de instalaciones fotovoltaicas de autoconsumo basado en estándares abiertos y soluciones de bajo coste. En la capa de percepción se han desarrollado y evaluado varios prototipos de sistemas de monitorización de acuerdo con los requisitos de la norma EC–61724, que describe las pautas generales para monitorizar y analizar el rendimiento de las plantas de energía fotovoltaica. Dentro de la capa de comunicaciones se ha trabajado en integración y evaluación de nuevos sistemas de comunicaciones de bajo coste, gran cobertura y baja demanda de energía (LPWAN) como medio para el intercambio datos en un entorno de Internet de las cosas (IoT). Por último, en la capa de aplicaciones se ha abordado el análisis de modelos de predicción de la generación de energía a corto plazo de estas instalaciones para proporcionar fiabilidad y estabilidad a la red, estudiándose tanto diferentes fuentes de datos de irradiancia para la aplicación de estos modelos como la influencia de los parámetros fundamentales de la red de comunicaciones en sus resultados. [ENG] This doctoral dissertation has been presented in the form of thesis by publication. The need to achieve a decarbonized economy to fight climate change has prompted several international commitments that oblige Spain and Europe to progressively reduce their greenhouse gas emissions until reaching climate neutrality in 2050. This goal can only be reached with a new energy model based on a massive integration of renewable energies. Among these technologies, photovoltaic solar energy is called to become one of the pillars to decarbonize the economy decarbonization thanks to its own technological maturity and the significant cost reduction, it has experienced in recent years. Within the different types of photovoltaic installations, one of the fastest growing is that of self-consumption, which are installations located near the points of electricity demand managed by the consumers themselves who also become providers of energy and services to the network, becoming the so-called prosumers.This massive integration of new distributed generation plants poses a challenge for the management of the electricity grid, which has traditionally responded to a unidirectional power flow model. In this unidirectional model, the power flows from the large generation units to the consumption points, adjusting the generation to achieve a power balance that allows effective regulation and control of the voltage and frequency values within the admissible ranges. The new decentralized distributed model requires new tools and management strategies to deal with the variability that renewable energies present due to their very nature and the large number and the geographical dispersion of installations that require greater flexibility to ensure a constant supply to cover demand and meet new challenges in the form of bidirectional flow of power These new management strategies are supported by the great advances made by information and communication technologies (ICTs) that have been gradually incorporated by the network operators in order to collect various variables related to generation units and consumer´s behavior in order to optimize distribution and consumption. In the case of photovoltaics, until a few years ago, the cost and complexity of monitoring systems for photovoltaic installations limited their use to large-capacity photovoltaic plants (from 1 MW, both for economic and regulatory reasons), but the appearance and rapid evolution in the market of the so-called Internet of Things, IoT, In this thesis, which has a practical approach, new contributions have been done to the three layers that make up an IoT system (perception, communication, and application) to propose a new management and communication prototype for selfconsumption photovoltaic installations based on open standards and low-cost IoT solutions. In the perception layer, several prototypes of monitoring systems have been developed and evaluated in accordance with the requirements of the EC–61724 standard, which describes the general guidelines for monitoring and analyzing the performance of photovoltaic power plants. Within the communications layer, work has been done on the integration and evaluation of new low-cost, high coverage, and low energy demand communications systems (LPWAN) to exchange data. Finally, in the applications layer, the analysis of short-term power generation prediction models for these facilities has been addressed to provide reliability and stability to the network, studying both different sources of irradiance data for the application of these models such as the influence of the fundamental parameters of the communications network in their results.Esta tesis doctoral se presenta bajo la modalidad de compendio de publicaciones. Está formada por un total de cinco artículos. 1. PV Module Monitoring System Based on Low-Cost Solutions: Wireless Raspberry Application and Assessment“. Paredes-Parra, J.M., Mateo-Aroca, A., Silvente- Niñirola, G., Bueso, M.C., Molina-García, A. 2018. Energies 11, no. 11: 3051. https://doi.org/10.3390/en11113051. 2. “An Alternative Internet-of-Things Solution Based on LoRa for PV Power Plants: Data Monitoring and Management“. Paredes-Parra, J.M., García-Sánchez, A.J., Mateo-Aroca, A., Molina-García, A. 2019. Energies 12, no. 5: 881. https://doi.org/10.3390/en12050881. 3. “A Characterization of Metrics for Comparing Satellite-Based and Ground-Measured Global Horizontal Irradiance Data: A Principal Component Analysis Application‘. Bueso, M.C., Paredes-Parra, J.M., Mateo-Aroca, A., Molina-García, A. 2020. Sustainability 12: 2454. https://doi.org/10.3390/su12062454. 4. “Sensitive Parameter Analysis for Solar Irradiance Short-Term Forecasting: Application to LoRa-Based Monitoring Technology“. Bueso, M.C., Paredes-Parra, J.M., Mateo-Aroca, A., Molina-García, A. 2022. Sensors (Basel) 22(4): 1499. https://doi.org/10.3390/s22041499. PMID: 35214398; PMCID: PMC8874705. 5. “Democratization of PV micro–generation system monitoring via an open source IoT gateway based on NB–IoT“. Paredes-Parra, J.M., Jiménez-Segura, R., Campos-Peñalver, D., Mateo-Aroca A., Ramallo-González, A.P., Molina-García, A. 2022. Sensors 22(13): 4966. https://doi.org/10.3390/s22134966.Escuela Internacional de Doctorado de la Universidad Politécnica de CartagenaUniversidad Politécnica de CartagenaPrograma de Doctorado en Energías Renovables y Eficiencia Energétic