This article presents the analysis of the influence of household appliances on the quality of the energy consumed by the end-user. The results of the research, then, concern the final consumer (the lowest level of the power grid). The research was conducted on 120 combinations of electrical appliances connected into a grid. Each combination consisted of three devices working simultaneously in a micro-grid. The obtained and statistically analyzed data proved that there are several types of appliances that have a great influence on the power quality (PQ) parameters changes. The results of the conducted experiments indicate the devices which influenced significantly the total harmonic distortion of voltage (THDV), the voltage frequency (FREQ) and the voltage fluctuation (V). Specific features of particular devices were examined in terms of their significance for the power quality deviation. This showed the most important features which should be considered while working out the prediction model. The future of smart grids resides in data analysis, predictive models and real-time optimization. One of the key characteristics is the reducing energy consumption generated by renewable energy sources. This phenomenon, namely looking for problems connected with sustainable power quality and their appropriate solution, is described in this article. We performed an extended analysis of the smart home appliances influence of individual quantities on a real model. Furthermore, we explored devices with a high impact on chosen power quality indicators. In the end, we discuss their specific behavior and relevance to the above-described phenomenon to improve the predictive model utility.

An Experimental Study of Laboratory Hybrid Power System with the Hydrogen Technologies

The massive development of internet of things (IoT) technologies is gaining momentum across all areas of their possible deployment—spanning from Industry 4.0 to eHealth, smart city, agriculture or waste management. This ongoing development is further pushed forward by the gradual deployment of 5G networks. With 5G capable smart devices, it will be possible to transfer more data with shorter latency thereby resulting in exciting new use cases such as Massive IoT. Massive-IoT (low-power wide area network-LPWAN) enables improved network coverage, long device operational lifetime and a high density of connections. Despite all the advantages of massive-IoT technology, there are certain cases where the original concept cannot be used. Among them are dangerous explosive environments or issues caused by subsurface deployment (operation during winter months or dense greenery). This article presents the concept of a hybrid solution of IoT LoRaWAN (long range wide area network)/IRC-VLC (infrared communication, visible light communication) technology, which combines advantages of both technologies according to the deployment scenario.

This paper deals with sensory equipment for swarm robots. It elaborates on reasons for choice of sensors based on their principles, ability to operate in swarms and use in a specified platform in previously defined conditions. Part of the thesis is also a background research and choice of individual sensors and numerous measuring experiments with them.