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.

This publication presents a system for integrating machine learning and artificial intelligence solutions with building automation systems. The platform is based on cloud solutions and can integrate with one of the most popular virtual building management solutions, HomeAssistant. The System uses communication based on the Message Queue Telemetry Transport (MQTT) protocol. The example machine learning function described in this publication detects anomalies in the electricity waveforms and raises the alarm. This information determines power quality and detects system faults or unusual power consumption. Recently, increasing electricity prices on global markets have meant that buildings must significantly reduce consumption. Therefore, a fundamental element of energy consumption diagnostics requires detecting unusual forms of energy consumption to optimise the use of individual devices in home and office installations.

The paper presents a new family of low voltage direct current, hybrid circuit breakers for urban traction vehicles (DCH-T) that also can be used in related industrial applications. A hyper-speed current breaking operation is performed by the means of a serial hybrid system, additionally protected by a fuse and a surge arrester. This process is arcless under any conditions. DCH-T circuit breakers are characterized by unique constructional and operational features and superior short-circuit parameters that are unreachable for classical magnetic blow-out devices. They effectively reduce short-circuit currents and the thermal and electrodynamic consequences of this phenomenon. They can protect all types of semiconductor converters used in electric traction vehicle drives. Moreover, they operate selectively in relation to the substation circuit breakers. Their contact life (even under short-circuit conditions) is equal to their mechanical life. Despite all the breaker standard functions, they offer special functions, such as cooperation with an on-board vehicle computer or a traffic control system. They are environmentally neutral and they can meaningfully improve passenger safety. Chosen thermal problems of DCH-T breakers has been modeled with the aid of simulation software and analyzed. DCH-T short-circuit parameters have been verified experimentally and the results are presented herein.