Energy Analyzer Emulation for Energy Management Simulators

The simulation of microgrids to testing and validate energy management methodologies are an important step to take before the massive implementation of microgrids. However, microgrids are usually unavailable for R&D centers to perform tests and validations. To solve this issue is important to get the simulations closer to the reality, using real energy analyzers and loads. However, again, R&D centers lack from funding and space to buy and mount several loads in their laboratories. To solve this issue, this paper proposes a multi-agent system simulator for microgrids and an energy analyzer emulator that can be used to emulate individual loads or entire houses, and therefore, bringing the pure simulation closer to the reality.The present work has been developed under the EUREKA - ITEA2 Project M2MGrids (ITEA-13011), Project SIMOCE (ANI|P2020 17690), and has received funding from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013 and SFRH/BD/109248/2015.info:eu-repo/semantics/publishedVersio

Virtual to Reality Emulator for Electrical Loads

The test and validation of demand side management systems are a priority before installing this systems in real environments. This paper presents a load emulator that acts as an energy analyzer. This emulator enables its installation in physical environments, fooling the metering systems. This capability allows the placement of the emulator in a physical metering system while emulating a load that is not there. In a R&D center the emulator can be used to create buildings by placing several emulators for load emulation and using a real and physical metering system to read the consumption data while demand side management algorithms and techniques are used. Using the proposed emulator, the gap between research and real implementations can be fulfill in the laboratories to test and validate demand side management systems. The paper presents the emulator and its results.This work has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAMGO) and from FEDER Funds through COMPETE program and from National Funds through FCT, under the project UID/EEA/00760/2013.info:eu-repo/semantics/publishedVersio

Single-unit and multi-unit auction framework for peer-to-peer transactions

Peer-to-peer transactions appear in smart grids as a way to enable the direct transaction of energy among end-users (i.e., consumers, producers, and prosumers). This concept promotes the efficient use of local renewable energy sources among neighbours. Several studies proposed the application of peer-to-peer models for energy communities, microgrids, and aggregators to decrease energy costs for end-users and to promote the balance between consumption and generation. In this paper, it is proposed a framework to test, and validate, using a real environment, single- and multi-unit peer-to-peer auctions. It is also proposed six lightweight fully distributed peer-to-peer auction models, avoiding the need for a central operator. The lightweight of the proposed models enables their execution in the fog-computing layer using single-board computers deployed in end-users. The proposed framework, together with the proposed day-ahead models, was tested and validated in a real microgrid with five prosumers. The results of two weeks are discussed using a comparative economic analysis. The proposed framework and models were able to reduce energy costs for the end-users, promoting competitive free market behaviours, with multi-unit models outperforming single-unit models in the overall trading efficiency and monetary profits.This work has received funding from the European Union's Horizon 2020 research and innovation programme under project DOMINOES (grant agreement No 771066) and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UIDB/00760/2020.info:eu-repo/semantics/publishedVersio

Cohesion policy and metropolitan governance: innovation in stakeholders collaboration practices in Lisbon

This study examines the impact of Cohesion Policy on metropolitan governance and stakeholders’ collaboration practices in the Lisbon region. The financial crisis and subsequent austerity policies have underscored the importance of institutional arrangements and governance processes, particularly at the local and regional levels. Focusing on the Lisbon metropolitan area, which faces fragmented institutional structures and governance challenges, this research highlights the role of Cohesion Policy through Integrated Territorial Investments (ITI) in fostering innovation and collaboration among stakeholders. The EVA (Green and Blue Corridor) project in the Lisbon Metropolitan Area exemplifies the role of EU funding in promoting cooperation and governance innovation. The introduction of ITI under the Cohesion Policy has facilitated the establishment of collaborative networks and innovative practices in the metropolitan area. These initiatives have broken down planning silos, promoting "soft spaces of governance" that encouraged knowledge exchange and institutional learning among territorial stakeholders. However, challenges persist in the absence of a coherent regional strategy and the prioritization of broad EU objectives over tailored regional needs. This hampers the potential for integrated and proactive territorial management. Nevertheless, Cohesion Policy has stimulated stakeholder collaboration and innovation in metropolitan governance, paving the way for sustainable and inclusive development in the Lisbon region.info:eu-repo/semantics/publishedVersio

IoT-Based Human Fall Detection System

Human falls are an issue that especially affects elderly people, resulting in permanent disabilities or even in the person’s death. Preventing human falls is a social desire, but it is almost impossible to achieve because it is not possible to ensure full prevention. A possible solution is the detection of human falls in near real-time so that help can quickly be provided. This has the potential to greatly reduce the severity of the fall in long-term health consequences. This work proposes a solution based on the internet of things devices installed in people’s homes. The proposed non-wearable solution is non-intrusive and can be deployed not only in homes but also in hospitals, rehabilitation facilities, and elderly homes. The solution uses a three-layered computation architecture composed of edge, fog, and cloud. A mathematical model using the Morlet wavelet and an artificial intelligence model using artificial neural networks are used for human fall classification; both approaches are compared. The results showed that the combination of both models is possible and brings benefits to the system, achieving an accuracy of 92.5% without false negatives.The present work has received funding from the European Regional Development Fund (FEDER) through the Northern Regional Operational Program, under the PORTUGAL 2020 Partnership Agreement and the terms of the NORTE-45-2020-75 call—Support System for Scientific and Technological Research—“Structured R&D&I Projects”—Horizon Europe, within project RETINA (NORTE 01-0145-FEDER-000062).info:eu-repo/semantics/publishedVersio

An Intelligent Smart Plug with Shared Knowledge Capabilities

The massive dissemination of smart devices in current markets provides innovative technologies that can be used in energy management systems. Particularly, smart plugs enable efficient remote monitoring and control capabilities of electrical resources at a low cost. However, smart plugs, besides their enabling capabilities, are not able to acquire and communicate information regarding the resource's context. This paper proposes the EnAPlug, a new environmental awareness smart plug with knowledge capabilities concerning the context of where and how users utilize a controllable resource. This paper will focus on the abilities to learn and to share knowledge between different EnAPlugs. The EnAPlug is tested in two different case studies where user habits and consumption profiles are learned. A case study for distributed resource optimization is also shown, where a central heater is optimized according to the shared knowledge of five EnAPlugs.This work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 641794 (project DREAM-GO) and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013 and SFRH/BD/109248/2015.info:eu-repo/semantics/publishedVersio

Building learning opportunities in classrooms of disadvantage: rethinking the learning trajectories

Researching learning trajectories in classrooms of disadvantage introduces specific challenges as well as opportunities. Situating our work within design research, we illustrate the power of theoretical approaches in which close attention is paid to both learners' conceptual developments and the means capable of supporting such developments for all learners. We illustrate how considerations of teachers' learning can and should inform the formulation of (students') learning trajectories, if these are to become viable outside of research studies

Ausência do carreamento nasal de Staphylococcus aureus resistentes à meticilina em pacientes em unidade básica de saúde de Porto Alegre, Brasil

INTRODUCTION: Community-associated methicillin-resistant Staphylococcus aureus (MRSA) has emerged as a pathogen in individuals without traditional risk factors. MATERIAL AND METHODS: MRSA nasal carriage was assessed in individuals consulting at a Primary Health Unit in Brazil. RESULTS: A total of 336 individuals were included: 136 were tested only for MRSA and 200 for any S. aureus. No MRSA was found among the 336 individuals and 23 (11.5%) of 200 were colonized by S. aureus. DISCUSSION: Low prevalence rates have been found in non-hospitalized individuals, but MRSA surveillance should be encouraged to monitor clinical and molecular epidemiology of CA- MRSA.INTRODUÇÃO: Staphylococcus aureus resistentes à meticilina associados à comunidade (CA-MRSA) têm emergido como patógeno em indivíduos sem os tradicionais fatores de risco. MATERIAIS E MÉTODOS: Carreamento nasal de MRSA foi avaliado em indivíduos atendidos em unidade básica de saúde. RESULTADOS: 336 indivíduos foram incluídos: 136 foram testados somente para MRSA e 200 para qualquer S. aureus. Nenhum MRSA foi encontrado nos 336 indivíduos e 23 (11.5%) de 200 eram colonizados por S. aureus. DISCUSSÃO: Baixas taxas de prevalência têm sido encontradas em indivíduos não-hospitalizados, entretanto a vigilância de MRSA é encorajada para o monitoramento da epidemiologia clínica e molecular do CA- MRSA

Indoor Real-Time Locating System comparison: Polaris vs FIND3

The use of real-time locating systems can be used in several fields, from security and health to building and energy management. However, there is no consensus in what the better solution or technology is to be used in an indoor location system. This paper presents a comparative study between a market real-time locating system and an open source real-time locating system. The systems that will be compared are Polaris and FIND3. The tests were performed in an office building.The present work was done and funded in the scope of the following projects: H2020 DREAM-GO Project (Marie Sklodowska-Curie grant agreement No 641794), from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2019 and SFRH/BD/109248/2015.info:eu-repo/semantics/publishedVersio

Smart Grid Ecosystem Modeling Using a Novel Framework for Heterogenous Agent Communities

The modeling of smart grids using multi-agent systems is a common approach due to the ability to model complex and distributed systems using an agent-based solution. However, the use of a multi-agent system framework can limit the integration of new operation and management models, especially artificial intelligence algorithms. Therefore, this paper presents a study of available open-source multi-agent systems frameworks developed in Python, as it is a growing programming language and is largely used for data analytics and artificial intelligence models. As a consequence of the presented study, the authors proposed a novel open-source multi-agent system framework built for smart grid modeling, entitled Python-based framework for heterogeneous agent communities (PEAK). This framework enables the use of simulation environments but also allows real integration at pilot sites using a real-time clock. To demonstrate the capabilities of the PEAK framework, a novel agent ecosystem based on agent communities is shown and tested. This novel ecosystem, entitled Agent-based ecosystem for Smart Grid modeling (A4SG), takes full advantage of the PEAK framework and enables agent mobility, agent branching, and dynamic agent communities. An energy community of 20 prosumers, of which six have energy storage systems, that can share energy among them, using a peer-to-peer market, is used to test and validate the PEAK and A4SG solutions.The authors acknowledge the work facilities and equipment provided by the GECAD research center (UIDB/00760/2020) to the project team.info:eu-repo/semantics/publishedVersio