Multi-Energy Management of Buildings in Smart Grids

The ongoing energy transition from centralized, fossil fuel power plants towards distributed, low-carbon generation resources implies fundamental changes in the energy infrastructures and their management. In the multidisciplinary domain of the energy sector and its transformation, this work tackles the challenge of rethinking the engineering and operation of energy systems to make them more efficient, more sustainable, and smarter. Taking an interdisciplinary approach between Power and Energy Engineering and Information and Communication Technologies, the research presented herein is part of the field of Energy Informatics and aims at contributing to the development of energy systems that promote energy efficiency and sustainability beyond what pure, traditional engineering solutions can do. In particular, we focus on the challenges of the energy management with increasing penetration of renewable sources at three levels of the energy system, namely, buildings, local energy communities, and transmission grids. The contribution of the present research to the field of Energy Informatics and smart energy systems is threefold. First, it lays the foundation for future smart home automation systems that can effectively contribute to building decarbonization. Second, it proposes a framework to mimic the dynamics of energy markets of the future, thereby giving more insights into the role of distributed resources in energy communities. Lastly, it provides the foundations for a new generation of planning tools for the transmission infrastructure that will rely both on robust and efficient networks allowing for high penetration of renewables

Sistema di visione per l'individuazione di sanguinamenti nel tratto gastrointestinale

Il sanguinamento del tratto gastrointestinale inferiore (LGIB) è una perdita ematica la cui origine è attribuibile distalmente al legamento di Treitz. L’incidenza annuale stimata è 20-27 casi/100000 adulti, di questi circa il 10% sono mortali. Ci sono varie cause che portano al LGIB, sia di origine patologica, sia derivanti da pratiche colonscopiche; tra le principali patologie troviamo la diverticolosi. Trovare la fonte del sanguinamentopuò essere difficoltoso in quanto il colon risulta essere “ricoperto” di sangue proveniente dalla lacerazione nonché sporco dei residui organici e dalla presenza di feci. La qualità dell’immagine che il medico riceve, inoltre, risulta essere fortemente degradata a causa dell’elevato scattering e assorbimento della radiazione dovuta al sangue. È evidente come il successo di una terapia endoscopica sia fortemente legato alla tempestività di intervento dell’endoscopista e dalla velocità con cui viene individuato il sito della lacerazione.. Molto spesso gli endoscopisti riescono a capire dov’è il punto di sanguinamento prestando attenzione alla variazione del colore del sangue. Infatti, il sangue all’uscita della lacerazione ha un tipico colore rosso vivo, mentre allontanandosi da questo sito il sangue cambia colorazione passando ad un rosso più scuro. Questo lavoro si propone di sviluppare una capsula con un sistema di illuminazione custom con diverse lunghezze d’onda che riesca ad accentuare le differenze nel colore del sangue sfruttando le sue diverse proprietà ottiche, in modo che il medico riesca facilmente ad individuare il sito di origine del sanguinamento, rendendo questa procedura medica più veloce, sicura e meno dolorosa. I risultati in vivo mostrano che il sistema di illuminazione sviluppato riesce ad enfatizzare le differenze di colore di un fattore 3 rispetto a normale sistema di illuminazione dell’endoscopio. Lower gastrointestinal bleeding (LGIB) is defined as bleeding of recent duration, with origin beyond the ligament of Treitz. The most important cause of acute LGIB is diverticula bleeding which results from the asymmetric rupture of the vasa recta arteries present in the thin-walled diverticula. As a consequence, frequently, the endoscopist takes over two hours to individuate the lower gastrointestinal bleeding (LGIB)’s origin; because the presence of a bleeding in the gastrointestinal tract contribute to degrade the image quality because of blood scattering and absorption; making medical procedure longer than usual. There is evidence that during a LGIB a change in the blood colour can be observed: blood becomes much darker as it moves from the LGIB’s point along the colon. This phenomenon is due to the synergy of various factors: coagulation, oxygen dissociation, colon’s bacteria metabolism and changing in pH and temperature. Aim of this work is to propose a device able to enhance colour differences between blood near the bleeding point and far from it, in order to help the doctor to easily identify the origin of bleeding. A wired capsule was developed in order to discriminate the bleeding point from the optical behaviour of blood at different wavelengths. The capsule is composed by a commercial CCD camera, a set of internal permanent magnets, in order to enable an active magnetic locomotion of the capsule inside the colon, and the custom multispectral illumination. A human machine interface (HMI) has been developed to control in real-time each groups of LEDs. The overall system has a diameter of 11 mm and is 22 mm in length which is small enough not to cause pain during the medical practice. The results of in-vivo tests session show that the differences in blood colours in the images acquired with the custom illumination board are three times higher than the differences in the images acquired with artificial white light. So it could really help the doctor in bleeding detection. Moreover an extensive in-vivo testing session will be performed in the near future with the purpose to have a complete and reliable vision analysis of this system to allow a comparison with traditional devices

Energy management for user’s thermal and power needs:A survey

The increasing world energy consumption, the diversity in energy sources, and the pressing environmental goals have made the energy supply–demand balance a major challenge. Additionally, as reducing energy costs is a crucial target in the short term, while sustainability is essential in the long term, the challenge is twofold and contains clashing goals. A more sustainable system and end-users’ behavior can be promoted by offering economic incentives to manage energy use, while saving on energy bills. In this paper, we survey the state-of-the-art in energy management systems for operation scheduling of distributed energy resources and satisfying end-user’s electrical and thermal demands. We address questions such as: how can the energy management problem be formulated? Which are the most common optimization methods and how to deal with forecast uncertainties? Quantitatively, what kind of improvements can be obtained? We provide a novel overview of concepts, models, techniques, and potential economic and emission savings to enhance energy management systems design

The integration of storage in HV grids: optimal use of renewable sources

This thesis work is developed with the aim of investigating how the introduction of storage systems can bring benefits for a power system with a high penetration of renewable production. Our first research question deals with the model of the grid: how can a power system be represented as a graph, taking into account its fundamental physical aspects and the main characteristics of its components? The second goal is running a DC power ow to minimize an objective function. Given the load demand and the installed generation plants, which is the objective function that minimizes the daily operational costs, maintaining the supply-demand balance? Finally, we introduce some storage systems. Do they lead a better exploitation of the renewable production, in terms of reduction of curtailment and relief of transmission congestion? Having a set of devices, which is their best siting? This thesis consists in two main parts: the topological representation of a power system as a graph and the simulation of a DC power flow above it. In the first part, the grid used as test case is topologically represented as a weighted graph, by describing four kinds of node and assigning the main line characteristics to the edges; load demand and renewable profiles are defined deterministically over a 24-hour horizon and with a quarterly resolution. Then, a DC power flow is run above all the grid, with the aim of minimizing the daily costs of production. At the beginning, in case of surplus of available renewable power, the model takes into account only the possibility of curtailment, while, at a later stage, some storage systems are added, following different policies. Both goals are reached by means of a new developed program, which solves a linear programming problem, where the variables involved are subjected to constrains

Creation and configuration of hybrid machine learning models for process optimization in the series production of complex optics

TCC (graduação) - Universidade Federal de Santa Catarina, Centro Tecnológico, Engenharia de Controle e Automação.Nos últimos anos, objetos óticos sofisticados e vidros finos têm sido usados cada vez mais por mercados alemães em crescimento, como os setores automotivo, de eletrônica e tecnologia em geral. Devido à complexidade, a produção em série desses produtos está suscetível a irregularidades e, portanto, faz-se necessário o emprego the procedimentos de controle de qualidade. Existe uma preocupação especial em relação ao processo de conformação a quente de vidros finos, por causa da dificuldade em medir este procedimento utilizando sensores. Existem alternativas para prever o resultado dessa operação utilizando aprendizado de máquina, mas elas demandam cientistas de dados treinados e uma quantidade significativa de dados de alta qualidade, o que são requisitos desafiadores para pequenas e médias empresas cumprirem. O presente Projeto de Finalização de Curso apresenta uma abordagem usando modelos híbridos, que combinam aprendizado de máquina e modelos baseados na física e possuem menos exigências em relação a dados históricos e equipe especializada. Essa solução tem como objetivo o desenvolvimento de um módulo que automaticamente cria e configura modelos híbridos para prever o desvio de forma de vidro durante o processo de conformação a quente. Para cumprir esse objetivo, foram conduzidos estudos iniciais para explorar o estado da arte das aplicações de modelos híbridos de machine learning e para entender as diferentes possibilidades de estrutura. Em seguida, os requisitos do projeto foram analizados e um fluxo de processo foi criado para descrever a geração de modelos híbridos. Posteriormente, a lógica criada foi colocada em prática utilizando Python e a validade foi verificada aplicando-a ao caso de uso.In recent years, sophisticated technical optics and thin glasses have seen increased usage in German growth markets such as the automotive, electronics, and tech industries. Due to the complexity of these products, their serial production is susceptible to irregularities; therefore, procedures for quality control need to be employed. There is a special concern for quality control during the hot forming of thin glass, given that it is difficult to measure details about this process using sensors. There are alternatives to predict the outcome using machine learning models; nevertheless, they usually demand trained data scientists and a significant amount of high-quality data, which are challenging requirements for small and medium enterprises to meet. This thesis presents an approach using hybrid models that combine machine learning and physics-based models and have fewer prerequisites regarding historical data and specialized personnel. This solution aims to develop a framework that automatically creates and configures a hybrid model structure to predict the shape deviation of glass during the hot forming process. To meet this objective, initial studies were conducted to explore the state of the art in the applications of hybrid machine learning models and to understand the different layout possibilities. Subsequently, the requisites of the project were further analyzed, and a workflow was created to describe the process of generating hybrid models. Thereafter, a computer program was created using Python to put this logic into practice and its validity was checked by applying it to the use case

Electric vehicles as distribution grid batteries:a reality check

Abstract The current transition towards electric mobility implies that a significant portion of electricity is drawn by and stored in the electric vehicle’s (EV) batteries. Vehicle-to-grid (V2G) technologies can potentially give distribution system operators access to such energy to provide ancillary services, while remunerating the vehicle owners for their availability to participate. Although the benefits of stabilization and grid efficiency improvements are clear, is it appealing and lucrative for the vehicle owners to participate in such services? In this work, we answer this question by modelling the V2G system and performing economic projections of the possible benefits for EV owners. In particular, we present a novel way of parametrizing the electric vehicle driving profile and the V2G energy transfer to compute battery degradation costs. A profit model is developed to evaluate the profit earned by the vehicle owners offering their batteries. The profit is estimated on the basis of the owner’s inclination to buy and sell energy from the grid based on the electricity price. Using data of the German electricity market, we estimate a profit of 662 €/EV/Year for a vehicle with 100 kWh capacity, 95% battery round trip efficiency and driving 52 km per day. The remuneration is meaningful and can have the potential to encourage EV owners to participate in V2G service

User indoor localisation system enhances activity recognition: A proof of concept

Older people would like to live independently in their home as long as possible. They want to reduce the risk of domestic accidents because of polypharmacy, physical weakness and other mental illnesses, which could increase the risks of domestic accidents (i.e. a fall). Changes in the behaviour of healthy older people could be correlated with cognitive disorders; consequently, early intervention could delay the deterioration of the disease. Over the last few years, activity recognition systems have been developed to support the management of senior citizensâ\u80\u99 daily life. In this context, this paper aims to go beyond the state-of-the-art presenting a proof of concept where information on body movement, vital signs and userâ\u80\u99s indoor locations are aggregated to improve the activity recognition task. The presented system has been tested in a realistic environment with three users in order to assess the feasibility of the proposed method. These results encouraged the use of this approach in activity recognition applications; indeed, the overall accuracy values, amongst others, are satisfactory increased (+2.67% DT, +7.39% SVM, +147.37% NN)

A Cloud Robotics Solution to Improve Social Assistive Robots for Active and Healthy Aging

Technological innovation in robotics and ICT represents an effective solution to tackle the challenge of providing social sustainable care services for the ageing population. The recent introduction of cloud technologies is opening new opportunities for the provisioning of advanced robotic services based on the cooperation of a number of connected robots, smart environments and devices improved by the huge cloud computational and storage capability. In this context, this paper aims to investigate and assess the potentialities of a cloud robotic system for the provisioning of assistive services for the promotion of active and healthy ageing. The system comprised two different smart environments, located in Italy and Sweden, where a service robot is connected to a cloud platform for the provisioning of localization based services to the users. The cloud robotic services were tested in the two realistic environments to assess the general feasibility of the solution and demonstrate the ability to provide assistive location based services in a multiple environment framework. The results confirmed the validity of the solution but also suggested a deeper investigation on the dependability of the communication technologies adopted in such kind of systems

Household CO₂-efficient energy management

Abstract Residential and commercial buildings are responsible for one third of the total (CO2) emissions in the European Union, which are the main cause of global warming. Although the thermal load has long been considered the primary reason of domestic energy consumptions, the increasing demand for electricity has a non-negligible environmental impact, given that about 40% of electricity is generated by burning fossil fuels. Moreover, the amount of CO2 emitted to produce one kWh can greatly vary in time, depending on the sources used to generate it. For instance, the German electricity emissions intensity factor varied in 2017 between 113 and 533 gCO2eq/kWh. This paper proposes a novel CO2-efficient energy management approach to schedule household appliances while minimizing carbon dioxide emissions, given the possibility to change energy carriers (i.e., natural gas and electricity) and to shift loads in time. Several common loads are considered, and their operation is scheduled according to the emission factor of the German power grid. The results show that switching energy carriers can successfully enable up to 40% emissions reductions while indicating that shifting loads in time has little impact