The current electricity default rates in continental countries, such as Brazil, pose risks to the economic stability and investment capabilities of distribution utilities. This situation results in higher electricity tariffs for regular customers. From a regulatory perspective, the key issue regarding this challenge is devising incentive mechanisms that reward distribution utilities for their operational and investment choices, aiming to mitigate or decrease electricity non-payment rates and avoid tariff increases for regular customers. Despite adhering to the principles of incentive regulation, the Brazilian Electricity Regulatory Agency (ANEEL) uses a methodological approach to define regulatory targets for electricity defaults tied to econometric models developed to determine targets to combat electricity non-technical losses (NTLs). This methodology has been widely criticized by electricity distribution utilities and academics because it includes many ad hoc steps and fails to consider the components that capture the specificities and heterogeneity of distribution utilities. This study proposes a fuzzy inference-based model for defining regulatory default targets built independently of the current methodological approach adopted by ANEEL and aligned with the principles of incentive regulation. An empirical study focusing on the residential class of electricity consumption demonstrated that it is possible to adopt a specific methodology for determining regulatory default targets and that the fuzzy inference approach can meet the necessary premises to ensure that the principles of incentive regulation and the establishment of regulatory targets are consistent with the reality of each electricity distribution utility.

Rapid technological changes and disruptive innovations have resulted in a significant shift in people’s behavior and requirements. Electronic gadgets, including smartphones, notebooks, and other devices, are indispensable to everyday routines. Consequently, the demand for high-capacity batteries has surged, which has enabled extended device autonomy. An alternative approach to address this demand is battery swapping, which can potentially extend the battery life of electronic devices. Although battery sharing in electric vehicles has been well studied, smartphone applications still need to be explored. Crucially, assessing the batteries’ state of health (SoH) presents a challenge, necessitating consensus on the best estimation methods to develop effective battery swap strategies. This paper proposes a model for estimating the SoH curve of lithium-ion batteries using the state of charge curve. The model was designed for smartphone battery swap applications utilizing Gated Recurrent Unit (GRU) neural networks. To validate the model, a system was developed to conduct destructive tests on batteries and study their behavior over their lifetimes. The results demonstrated the high precision of the model in estimating the SoH of batteries under various charge and discharge parameters. The proposed approach exhibits low computational complexity, low cost, and easily measurable input parameters, making it an attractive solution for smartphone battery swap applications.

Greenhouse gas emissions-related issues have been extensively discussed in the past years, with over 70 countries already committed to a carbon-neutral economy by 2050. The electrification of transportation modals has increased following these goals, where Electric Vehicles (EVs) are starting to take Internal Combustion Engine Vehicles (ICEV) market share all over the globe. Besides the particular complexity in comparing EVs and ICEVs, challenges involving the nature of EVs and their integration with cities, such as the lack of public locals for charging, are also critical and interfere with their development. In this context, this work aims at studying the problem of a Battery Swapping Station (BSS), a structure where the EVs users swap their depleted batteries for fully or partially charged ones. In order to simulate the BSS daily operations and battery charging schedule, a novel Mixed Integer Linear Programming (MILP) model is proposed, taking into account battery heterogeneity, the use of local photovoltaic (PV) production, and battery degradation based on charging profile. A collection of BSS operation metrics are designed to evaluate the solution quality of the proposed scheduling model. A numerical experiment comprising four case studies based on real data from the US power and transportation systems is presented, with insights and analyses on the PV and grid power use, as well as a BSS financial comparison against close-related benchmark scheduling approaches, together with sensitivity analyses on BSS sizing plan and costumers service. Results highlight the importance of battery degradation in the optimization model, since its consideration as an operational cost brought a reduction of 16%.

Esse trabalho se propõe a examinar a contribuição de aspectos arquitetônicos em habitações de interesse social de modo a proporcionar conforto térmico aos moradores e redução do consumo de energia de tais residências. Foram examinados recursos arquitetônicos que possibilitem que as edificações tenham baixo consumo energético e como tais recursos podem ser aplicados em projeto de habitações de interesse social no Brasil. Foi feita uma análise da apropriação desses aspectos arquitetônicos no projeto do Condomínio Refazenda o que permitiu identificar a possibilidade de se elaborar projetos de habitação de interesse social que proporcionem conforto térmico e com baixo consumo de energia.

O objetivo deste trabalho é simular diversos modelos de elementos de sombreamento de fachadas com a integração de filmes FV orgânicos (OPV), possibilitando a expansão da utilização desta tecnologia de geração de energia solar. A partir da identificação de uma lacuna na literatura relacionada à OPV integrado a elementos de sombreamento em fachadas, buscou-se o desenvolvimento de elementos de sombreamento mais eficientes que além de evitar a incidência solar direta na fachada pudessem também gerar energia elétrica. Assim, foram unidas duas estratégias para alcançar uma maior eficiência energética do sistema e um maior conforto ambiental. No total foram projetados 25 modelos inspirados em aplicações de outras tecnologias fotovoltaicas em elementos de sombreamento e se obteve um modelo mais adequado para cada cenário proposto: o primeiro sendo o cenário ideal e desconsiderando limitações de dimensões do OPV; e o segundo respeitando os limites técnicos de OPV existentes atualmente no mercado nacional. Para simular este sistema utilizaram-se os programas de computador Rhinoceros em conjunto com os plug-ins Grasshopper e Ladybug, para o cálculo da incidência solar na superfície dos elementos de sombreamento visando à redução das áreas ociosas nos painéis FV. Como resultado, a geração energética obtida variou entre 17,88 - 35,70 kWh devido à eficiência do material disponível no mercado nacional.

This paper introduces the mobile battery network for electronic devices through powerbanks in a city, and proposes an optimization model to find the optimum site and set-up of the network considering costumers demand, logistics components, the batteries degradation, and terminal’s charger regime. To this end, a series of degradation tests were carried out on lithium-ion batteries, in four different charger regimes, in which the battery voltage amplitude and the charging electric current were varied. The results of these tests were incorporated into the optimization model as the depreciation rate and charge time over battery life. The mathematical modeling innovates by including new components designed specifically for this new problem: battery availability according to charging time; different types of customer service; objective function modeling that includes the logistical costs of battery relocation, terminal maintenance, and battery depreciation. The results indicate that the network performance using batteries in the fastest charging configuration tends to have a positive impact on their efficiency and profitability. The model can be used as a reference for other applications that require recharge points that enable the use of mobile batteries, such as electric scooters, electric bicycles, and drones, among others.

This work proposes to examine the contribution of architectural aspects in social housing in order to provide thermal comfort to residents and reduce energy consumption of such residences. Architectural resources that allow buildings to have low energy consumption were examined and how such resources can be applied in social housing projects in Brazil. An analysis was made of the appropriation of these architectural aspects in the Condomínio Refazenda project, which allowed us to identify the possibility of developing social housing projects that provide thermal comfort and low energy consumption.

This paper presents an algorithm based on Convolutional Neural Networks (CNN) to find the depth and angles of inclination and rotation of a foreign object inside the human body based on images of the magnetic field generated by it. The key challenge is to provide information with enough accuracy to be used in surgical procedures. We tested three distinct CNN architectures for values prediction, and our best model achieved a mean - average F1-score of 66 %, 100 %, and 98 % in the test dataset for depth and angles of inclination and rotation, respectively. We also propose an approach for converting classification values to real values and we calculate the type A uncertainty for all models, with our best model showing an uncertainty of 10.8 mm for depth, 2.0° for inclination and 7.5° for rotation values.

The development of systems capable of characterizing the positioning and inclination of metallic objects inside the human body is seen with great interest by health professionals who are responsible for their extraction. A surgical procedure can be shortened from a few hours to minutes with a system that provides accurate positioning data. Thus, the present work aims at the construction of a measurement system of magnetic fields originated by ferromagnetic objects, based on magnetoimpedance (GMI) sensors. The developed system is capable of positioning a ferromagnetic object to be measured with 5 degrees of freedom, being 3 linear (X, Y, Z) and 2 angular (θ, Φ), and measure the magnetic flux density of this source in an automated way. Three tests were performed with a steel needle, varying the angles of inclination to the measurement plane (θ) and rotation angles in the same plane (Φ). The obtained results yieded records of the magnetic patterns formed by the needle, which can be later processed in order to create a localization software.

Studies in the literature suggest that smartphone-based applications are not suitable for measuring illuminance levels. The measurement of this photometric quantity is useful in several sectors, including monitoring the adequacy of lighting conditions in workplaces. This work investigates the contribution of attaching a diffuser dome to the embedded light sensors of smartphones and tablets associated with different applications on their performance for measuring illuminance. Two experimental arrangements were developed using an LED lamp (294.84 lx, 475.58 lx, 880.39 lx) and a xenon arc lamp (607.94 lx, 1013.72 lx, 4012.26 lx, 23933.33 lx). In the comparative analysis, the impact of using diffusion dome attachment was evidenced, indicating its potential to enable some of the device/application combinations to achieve adequate performance for being applied in the daily assessment of illuminance.

With the increasing development of portable devices, research on mobile power sources have been an important goal. Thus, the improvement on their safety, energy density and degradation rate is the current challenge of different researchers. The present work seeks to develop an algorithm, based on artificial neural networks, to predict the voltage curve of a lithium-ion battery based on destructive tests. It was found that the developed system can define the condition of the battery in the test and generates voltage curves that allow the estimation of the batterys charge and its charging time.

There are several studies in the literature on monitoring carbon dioxide concentrations in combination with various other parameters to assess indoor air quality. However, no study describes the monitoring of air quality in different locations of the same environment. The characterization of the spatial distribution of atmospheric parameters can contribute to more appropriate analyses, providing customized planning’s for improvements. The present work develops a multiparametric measuring system for real-time monitoring of the spatial distribution of carbon dioxide, temperature, humidity, particulate matter, volatile organic compounds, and barometric pressure. Preliminary results indicate the necessity of multiple-location measurement for appropriate air quality analyses.

The research on renewable energies was accelerated due to the speed-up of the global warming, caused by the accumulation of greenhouse gases (GHG) released largely by the burning of fossil fuels. Photovoltaic energy is environment friendly, however it can present adverse effects like electrical non-linearity. To mitigate such effects, the most efficient solution is the implementation of a maximum power point tracking algorithm (MPPT). The aim of this work is to carry out a review on the latest five years (2015 to 2020), regarding the conventional and novel methods of MPPT. In order to fulfill this objective a bibliographic research was carried out in the Scopus database. The analysis of the selected articles pointed out to 67 MPPT algorithms and show that although there are many algorithms being proposed today, yet still exists a lack of a deeper cost approach which lead to a reduction in the inverter's final prices.

Quality and risk management have evolved with the advancement of pharmaceutical and technological development in healthcare, allowing greater control of each biomedical device's manufacturing processes. Failure Mode and Effect Analysis (FMEA) has been widely used in healthcare to ensure the quality of manufactured products. It is dedicated to preventing adverse events or incidents, identifying failures to prioritize risk, and optimizing resources, for better quality in medical devices or equipment. Quality by Design (QbD), in turn, has been applied in the pharmaceutical industry for product quality assurance since the development stage. This work integrates QbD and FMEA for application in the development of electromedical equipment. Preliminary results of the proposed hybrid method applied to the development phase of a low-cost and high-sensitivity magnetic measuring system for metallic foreign bodies' location in patients are presented.

This work presents the adaptation of the Quality by Design (QbD) approach for application in the quality assurance of a biomedical measuring system under development. First attempts in applying QbD to biomedical technologies indicated a significantly higher number of parameters than its traditional application in the pharmaceutical industry. These preliminary studies did not fulfill the QbD stage of Design Space (DS) configuration for biomedical devices, an essential step to identifying the proper operating ranges of parameters and guaranteeing quality features. Therefore, it persisted the challenge of configuring DS for health devices, overcoming dependences in the interaction of multiple process parameters and critical attributes. The present work develops a hybrid QbD-Fuzzy approach for multiparametric DS configuration. The proposed method was applied in the development phase of a low-cost and high-sensitive magnetic measuring system for locating metallic foreign bodies in patients, employing sensors based on the Giant Magnetoimpedance effect. The results provided the acceptable operating ranges of the multiple process parameters to ensure the biomedical equipment's suitability. The proposed strategy contributes to the QbD implementation in biomedical technologies and, therefore, promotes the reliability of diagnostic and therapeutic results in the clinical environment.

Distributed energy generation is growing at an accelerated level in Brazil. This scenery induces to an economic imbalance on the distributors, requiring a new tariff model that captures those effects. For this aim, the National Electric Energy Agency (ANEEL) purpose five alternatives tariff models to update the current Brazilian regulatory model (micro and mini-generation). This article aims to identify the main actors involved in the change process, highlighting the impacts that can affect those scenarios. The results show that the scenario choosed by ANEEL it is the most conflicting and its adopting will discourage the distributed generation.

This article aims to simulate the insertion of a solar generating plant in an area where there is an overload power feeder, measuring the reduction of technical electrical losses. A 2.99 MVA transformer was selected with 30% overloading during afternoon hours, so that would be possible to place the solar generator source of up to 1 MWp to overlap this. The Interplan® software was used to simulate the impact in technical losses. It was possible to observe a reduction of up to 33.12% in technical energy losses due to the insertion of distributed generation.

The aim of this article is to simulate different shading devices, changing its design and configurations. For each device it is designed a photovoltaic set with panels, which is positioned on the louvers. Computer simulations were performed in Rhinoceros 5.0, Honeybee and Ladybug in order to measure the building's performance considering zero, two, three and four louvers shading devices in order to measure its impact on electricity generation and inner thermal load of a building facade in Rio de Janeiro. Results have shown a reduction of 14%-19% on cooling loads and 770-989 kWh generated by PV devices. Altogether, the addition of PV shading devices reduced in up to 32% the net energy demand of the building.

This paper presents a new optimization model to define a network of terminals that distribute charging batteries (powerbanks) for mobile devices. The model is applied to a Startup in Rio de Janeiro and is part of a more comprehensive study sponsored by ENEL enterprise that includes the logistics component presented here and another component for the study and development of batteries and charging terminals. A mix integer programming model (MIP) is developed based on bicycle sharing network location models and combines strategic network location and sizing decisions (where to install and the capacity of the terminals) with operational decisions (allocation and reallocation of batteries at the terminals). The mathematical modeling uses as a reference the maximum coverage location model of bike-sharing systems presented by Frade and Ribeiro (2015) and innovates by including new aspects in the model: battery recharge time; different types of customer service; charging system settings and battery performance. Another new aspect of the model is related to the Objective Function (FO) which seeks to maximize the economic performance of the network obtained from the difference between the revenue generated by the leasing of batteries and the logistical costs of reallocating batteries, maintenance of terminals and depreciation of batteries in the system. The FO is given by equation 1.

Transcranial magnetic stimulation (TMS) is a noninvasive technique that promotes the neuromodulation effect aiming at treating diseases of neuro-psychiatric origin. TMS electromagnetic coils provide an alternating magnetic field that induces bioelectric currents in a targeted region of the brain tissue. The guarantee of treatment effectiveness and safety of both patients and device operators depends on the distribution of the magnetic flux density emitted in the vicinity of the TMS equipment, according to the design of the induction coil employed. This work presents the development of a multichannel measuring system to evaluate the configuration of magnetic flux density generated in the proximities of TMS devices. By using the developed measuring system, it is performed the magnetic mapping along a plane under the figure-of-eight TMS coils, including the study of its response to different intensities and distances from the device. The results allow characterizing the decay of field magnitude towards the region closer to the operator’s hand position and its spatial distribution in areas intended to receive the therapeutic effect.