Browsing by Author "Silva, Sergio"
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- An Intelligent Weather StationPublication . Mestre, Goncalo; Ruano, Antonio; Duarte, Helder; Silva, Sergio; Khosravani, Hamid Reza; Pesteh, Shabnam; Ferreira, Pedro M.; Horta, RicardoAccurate measurements of global solar radiation, atmospheric temperature and relative humidity, as well as the availability of the predictions of their evolution over time, are important for different areas of applications, such as agriculture, renewable energy and energy management, or thermal comfort in buildings. For this reason, an intelligent, light-weight, self-powered and portable sensor was developed, using a nearest-neighbors (NEN) algorithm and artificial neural network (ANN) models as the time-series predictor mechanisms. The hardware and software design of the implemented prototype are described, as well as the forecasting performance related to the three atmospheric variables, using both approaches, over a prediction horizon of 48-steps-ahead.
- The IMBPC HVAC system: a complete MBPC solution for existing HVAC systemsPublication . Ruano, Antonio; Pesteh, Shabnam; Silva, Sergio; Duarte, Helder; Mestre, Gonçalo; Ferreira, Pedro M.; Khosravani, Hamid Reza; Horta, RicardoThis paper introduces the Intelligent MBPC (IMBPC) HVAC system, a complete solution to enable Model Based Predictive Control (MBPC) of existing HVAC installations in a building. The IMPBC HVAC minimizes the economic cost needed to maintain controlled rooms in thermal comfort during the periods of occupation. The hardware and software components of the IMBPC system are described, with a focus on the MBPC algorithm employed.The installation of IMBPC HVAC solution in a University building is described, and the results obtained in terms of economical savings and thermal comfort obtained are compared with standard, temperature regulated control. (C) 2016 Elsevier B.V. All rights reserved.
- Wireless sensors and IoT platform for intelligent HVAC controlPublication . Ruano, Antonio; Silva, Sergio; Duarte, Hélder; Ferreira, Pedro M.Energy consumption of buildings (residential and non-residential) represents approximately 40% of total world electricity consumption, with half of this energy consumed by HVAC systems. Model-Based Predictive Control (MBPC) is perhaps the technique most often proposed for HVAC control, since it offers an enormous potential for energy savings. Despite the large number of papers on this topic during the last few years, there are only a few reported applications of the use of MBPC for existing buildings, under normal occupancy conditions and, to the best of our knowledge, no commercial solution yet. A marketable solution has been recently presented by the authors, coined the IMBPC HVAC system. This paper describes the design, prototyping and validation of two components of this integrated system, the Self-Powered Wireless Sensors and the IOT platform developed. Results for the use of IMBPC in a real building under normal occupation demonstrate savings in the electricity bill while maintaining thermal comfort during the whole occupation schedule.