An important task is the possibility of controlling the impact of energy facilities on the environment. Neural networks can be of great help in automatic monitoring of the state of natural objects, in determining the best location of energy facilities, in predicting the expected amount of energy produced. The authors propose neural network algorithms for monitoring the state of objects. Emphasis is placed specifically on energy facilities. The models developed by the authors can be used in monitoring the state of natural resources, in optimizing the location of renewable energy sources, in forecasting energy production.