Remote Monitoring System of an Autonomous Mixed Type Power Plant

The analysis of directions and ways of monitoring the systems of solar-wind autonomous power plant, as well as the possibility of predicting its state was carried out. A review of training and target patterns was carried out. The system of monitoring the state of systems of solar-wind autonomous power plant, predicting its status with the help of recurrent Elman neural network is developed. The possible advantages of implementing a control system based on neural networks in terms of technological and economic criteria are described. Conclusions about possibility of implementing the proposed system and its advantages are made.