Neural network pressure observerfor a turbomechanism electromechanical system powered by a wind generator

Abstract

Ecological and economic production of electrical energy through the use ofalternative energy sources is an urgent direction due to the trend of increasing prices of energy carriers used in the electrical energy production and as a result of significant damage of the energy system of Ukraine in consequence of the war on the country territory.It is worth noting that in some areas it is possible to use only autonomous power generation systems, since the laying of electrical networks in these districts is impractical and unprofitable. Usually, the mentioned systems are basedon a combination of a wind or hydro turbine -drive motor, and an electric generator. Such systems are characterized by high resource, reliability, low cost,and complexity of maintenance. Sometimes people's lives and the possibility of communication withthe outside world depend on the operation of an autonomous electric power generation system, which is especially important in the conditions of martial law. At the same time, the lack of stabilization of the hydraulic networkpressureof the water supply system can lead to the household conditions aggravation, the emergency situations occurrence, and the technological process disruption.In view of the mentioned factors, there is a need to measure the pressure of the hydraulic network, which is possible byusing technological coordinatesobserversbuilt on the basis of the artificial networks theory. In the paper a modern turbomechanism electromechanical control systempowered by an alternative electrical energy source under the conditions of pressure stabilization of thehydraulic network when using atechnological coordinatesobserver, namely a pressure estimator, is proposed. A mathematical description of the main elements of the investigatedsystem is given. A hydraulic network pressure observerbased onthe artificial neural networks theory isbuilt and studied. Features of design and training of technological coordinate estimators based on neural networks with feedback are described. The operation of the sensorless system during thepressure stabilization at a given level when the resistance of the hydraulic network changes within the typical daily cycle of water consumption is considered on a specific example. The results and analysis of the investigationof the developed observerin standard and sensorless control systems are shown.