The paper considers an intelligent automated solar tracking control system designed to increase the efficiency of solar energy production. The proposed method of detecting cloudiness allows system to adapt to various weather conditions in real time by changing the angle of the solar panel. It is known that in case of strong scattering of solar radiation in cloudy weather panels installed horizontaly are more effective, rather than trackers which precisely oriented to the Sun. Proposed solar biaxial solar tracker equipped with two additional small solar modules. One of the modules is installed in a horizontal position, the second module is also a biaxial solar tracker. The algorithm for determining the position of the solar panel is based on known trajectory of the Sun during whole year saved in memory card and on monitoring the output currents of small solar panels built into the system. When cloudiness increases, the output current of a small solar horizontal module will exceed the current of the module oriented to the Sun. Then the big solar panel goes into a horizontal position. For remote monitoring of the energy characteristics of the solar battery, wireless data transmission based on LoRa AS32 TTL modules were added into the system. Experimental results showed that energy generated in cloudy weather using proposed method exceeds energy collected by biaxial solar tracker by 18%.

With the development of technologies and the growing need for accurate positioning inside buildings, the localization method based on Received Signal Strength Indicator (RSSI) fingerprinting is becoming increasingly popular. Its popularity is explained by the relative simplicity of implementation, low cost and the ability to use existing wireless infrastructure. This review article covers all the key aspects of building such systems: from the wireless communication technology and the creation of a radiomap to data preprocessing methods and model training using machine learning (ML) and deep learning (DL) algorithms. Specific recommendations are provided for each stage that can be useful for both researchers and practicing engineers. Particular attention is paid to such important issues as RSSI signal instability, the impact of multipath propagation, differences between devices and system scalability issues. In conclusion, the review highlights the most promising areas for further research. For smart cities, the approaches and recommendations presented in the review contribute to the development of urban services by combining indoor positioning systems with IoT platforms for automation, transport and energy management.

Modern solar follow-up systems make it possible to increase a solar cell’s efficiency and, as a result, solar energy utilization. The paper considers modern solar follow-up methods and their...

This paper considers an autonomous intelligent street lighting system with energy efficient predictive algorithm. The work is related to control of the system which uses algorithms that could provide with energy each lamppost during the night time. To this end, lamp posts are equipped with batteries, motion and light sensors and uniaxial solar trackers with azimuth orientation to the Sun. To simplify system monitoring, several lampposts are grouped together and controlled by a single control unit. The control unit is equipped with XBee 3 wireless module. Based on weather forecast for the coming days, the system adapts to weather condition changes and makes calculations of consumption and operating time. These calculations allow us to distribute the system energy consumption evenly during these days.

The paper considers modern street lighting systems and shows the drawbacks of existing street lighting systems. The concept of an autonomous street lighting system with wireless monitoring is considered. The power of this system is provided by solar panels and accumulators. The organization of a wireless network inevitably raises the question of energy consumption. In this paper, we presented a router duty mode, which reduces the overall power consumption of the wireless network. The router's duty mode is a process of sequentially switching nodes from the role of routers to the role of sensor nodes. The graphs of discharge of accumulators are constructed for the stationary mode of the network operation and for the duty mode.

Today’s research on concentrated photovoltaic (CPV) cells focuses on creating multi-junction semiconductor solar cells capable of withstanding high temperatures without losing their properties. This paper investigated silicon low concentrated photovoltaic (LCPV) devices using Fresnel lenses. The parameters of the silicon CPV cell were measured to simulate its operation based on a single-diode model with four and five parameters. The most optimal position of the Fresnel lens relative to the solar cell was shown, and the dependence of the CPV efficiency on the concentration ratio, incident solar power, and temperature was studied. Experiments on heating of a solar cell were conducted to build a model of heating of a solar cell under different solar radiation based on machine learning. Additionally, a cooling system was developed, and experiments were conducted for one LCPV cell. The resulting LCPV model was used to predict electrical power output and temperature change pattern using clear day data. Results of modeling show increase in generated energy by 27% compared with non-concentrated solar cells. Cooling system energy consumption was simulated, and the optimum cooling regime was determined. The proposed LCPV system can be used as a hybrid heat and electricity source, increase power generation, and does not require new solar cell production technologies.