Software prototype development for non-centralized objects of wind flow amplification
Keywords:wind energy, Internet of Things, software, real time, Django, process monitoring
This research is devoted to the development of software to increase the efficiency of autonomous wind-generating substations using panel structures, which will allow the use of wind energy to generate electricity with minimal losses and for the life support of buildings and structures. In the course of the work, a software and hardware system with a functional diagram for experimental measurements was developed. The paper also describes the process of modeling wind generation, collecting and transmitting real-time data to a web server via the HTTPS protocol. Due to the intensive development of wind energy in Kazakhstan, there is a need to apply methods to improve the energy generation process. In particular, the use of hardware and software to monitor and make decisions on optimizing the power generation process will help solve the problem of limited economic and labor resources. The results of the experiments revealed that the automatic control of the shield structures allows specialists to increase the effectiveness of the energy generation process by 25 % and, thus, a non-linear relationship between the power of the generated energy, the speed and direction of wind has been revealed. It should also be noted that the results obtained in the course of this research make it possible to solve the problem of saving electricity in the cities of Kazakhstan, since so far there are only large-scale wind farms, which is not always available in simple urban conditions. Moreover, the software developed during the study will allow autonomous control and analysis of the behavior of the wind farm, taking into account various weather conditions. In the future, the methods of data analysis will be applied to the data obtained via the process of modeling.
A script for receiving and transmitting real-time data with wind speed and direction sensors has been developed
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Copyright (c) 2022 Alina Gaukhar, Nurlan Tashatov, Galina Tatkeyeva, Madi Bauyrzhanuly, Dinara Kaibassova, Margulan Nurtay
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