No abstract

Advances in distributed generation and increased contribution of renewable energy source (RES) require development of smart grid technologies. Smart metering systems, as a part of smart grid technologies, in cooperation with modern buildings equipped with building management system allows for improvement of energy efficiency. It is possible to partially cover the power demand of a building from the local RESs. However, in order to ensure maximum added value, energy management system (EMS) is essential. This article presents the project and practical implementation of an EMS implemented in smart-meter. The designed system is based on an original algorithm using fuzzy logic. The rule base was created in FCL language and the implementation was carried out in C++ with the object-oriented programming (OOP). For the efficiency rating indicator, peak-to-average ratio (PAR) was selected. This ratio depending on the daily load profile decreased within a range from 15 to 54%, and the average value was 30%. The proposed energy management algorithm helps to reduce energy consumption at peak demand by 34%, with the total reduction of energy consumption during the day of 7%. The described solution demonstrates a potential for real implementation and was tested in hardware.

Cutting-edge building energy management systems (BEMS) interact with heating, ventilation, air conditioning (HVAC) systems, which generally account for much of the energy consumption. Major attention is focused on the BEMS themselves, barring on-field equipment. In HVAC equipment, sub-optimal controller settings may lead to energy losses and user discomfort, for instance, due to oscillations of air temperature and fan speeds. The way to solve this problem could be to replace classical PID controllers with an alternative concept that does not require tuning and works optimally for a wide range of parameters. This paper compares a fuzzy logic controller (FLC) with a standard PID for a model-based simulation of an HVAC system in Simulink for different conditions using real building measurement data. The end result is the implementation of the developed methods in a newly designed universal control board for air handling units (AHU). The proposed FLC achieves better integral control quality indicators (IAE, ISE, ITAE, ITSE) by at least 27.4%, and smaller supply air temperature variation; the daily mean square error (MSE) was reduced by an average of 36%, which leads immediately to better occupant comfort and a presumed reduction in energy consumption. Compared to the untuned PID, energy consumption was 12.7% lower; this will ensure improved economy from the lowest level, and paves the way for interoperability with high-level energy management schemes.

Thermal analysis of smart buildinǵÁ bstract. In the paper the simulation and measurements of temperature distribution and humidity in a room of smart building are discussed. Initially, mathematical model has been created. For this purpose ANSYS Fluent has been used. The simulation has concerned changes in solar radiation, temperature, humidity, air velocity and the real structure of walls, ceiling and the floor of the room. Then, the measurement results and simulation results have been compared. Streszczenie. W artykule zaprezentowano model matematyczny pomieszczenia w inteligentnym budynku oraz dokonano analizy termicznej na podstawie symulacji wykonanych przy użyciu pakietu Ansys Fluent. W symulacji uwzględniono zmiany nasłonecznienia i związanej z nim temperatury oraz prędkosci powietrza, a także rzeczywistą strukturęścian, sufitu i podłogi pomieszczenia. Wykonano również analizę rzeczywistych pomiarów temperatury i wilgotnosci. (Analiza termiczna inteligentnego budynku)