Big Data Driven Hybrid AI Method for Energy Demand Forecasting and Operational Planning in Industrial Greenhouse Production

This project aims to develop a big data driven hybrid AI method for forecasting the energy demand of industrial greenhouse plant production. Energy demand forecast provide necessary information for planning and optimizing the operation of a grid connected local energy system that is based on distributed renewable energy resources. The application of the method provides the means for optimizing the operation of the local energy system and the operational planning of the interaction with the main grid in response to different energy pricing models.