Browsing by Author "Baptista, Pedro"
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- COVID-19 Next Day Trend ForecastPublication . Costa, Marcelo; Rodrigues, Margarida; Baptista, Pedro; Henriques, João; Pires, Ivan Miguel; Wanzeller, Cristina; Caldeira, FilipeHistorically, weather conditions are depicted as an essential factor to be considered in predicting variation infections due to respiratory diseases, including influenza and Severe Acute Respiratory Syndrome SARS-CoV-2, best known as COVID-19. Predicting the number of cases will contribute to plan human and non-human resources in hospital facilities, including beds, ventilators, and support policy decisions on sanitary population warnings, and help to provision the demand for COVID-19 tests. In this work, an integrated framework predicts the number of cases for the upcoming days by considering the COVID-19 cases and temperature records supported by a kNN algorithm.
- Design of Data Management Service Platform for Intelligent Electric Vehicle Charging Controller Multi-charger ModelPublication . Baptista, Pedro; Rosado, José; Caldeira, Filipe; Cardoso, FilipeThe electric charging solutions for the residential market imply, in many situations, an increase in the contracted power in order to allow to perform an efficient charging cycle that starts when the charger is connected and ends when the VE battery is fully charged. However, the increase in contracted power is not always the best solution for faster and more efficient charging. With a focus on the residential market, the presented architecture is suitable for single-use and shared connection points, which are becoming common in apartment buildings without a closed garage, allowing for sharing the available electrical connections to the grid. The multi-charger architecture allows using one or several common charging points by applying a mesh network of intelligent chargers orchestrated by a residential gateway. Managing the generated data load involves enabling data flow between several independent data producers and consumers. The data stream ingestion system must be scalable, resilient, and extendable.
- Intelligent Electric Vehicle Charging ControllerPublication . Gonçalves Cardoso, Filipe; Rosado, J.; Silva, Marco; Teixeira, C. J. Coelho; Agreira, C. I. Faustino; Caldeira, Filipe; Baptista, Pedro; Barreto, Francisco; Pereirinha, Paulo G.Abstract—For domestic consumers, electricity tariffs usually have two components: one is related to the maximum available current/total power (billed in C/day) and the other concerns to the energy consumption (C/kWh). The main switchboard current is usually limited, according to the contracted power level, by way of automatic switches. To avoid main switchboard tripping by current limit violation, Electric Vehicle (EV) owners may decide to increase their contracted power (and the energy bill) or to adopt charging strategies that limit the global consumption (EV plus house needs) to the contracted current/power. In this paper, an Intelligent Electric Vehicle Charging Controller (IEVCC), allowing to use the contracted power to the maximum extent, is presented. A set of user configurable parameters can be used to define the controller behavior, in order to prevent a full switch-off. Two versions are described: a single user version that can be used at private houses and a mesh version that can be used in multi apartment buildings, providing information about consumed energy, time of use, costs and past bills.