System and methods for power system forecasting using deep neural networks

A computing device for managing energy, the computing device comprising:

• a load processor, and
• a data collection system configured to provide power load information, the data collection system located at a building and using a cloud analysis layer that employs machine-learning and artificial intelligence for optimization control;
• wherein the load processor is configured to:
• analyze the received power load information to disaggregate load waveform signals and identify device-based power loads by use of a neural network to perform historical device demand and performance analysis to generate device-based demand forecasting;
• generate demand forecasts for the building to mitigate peak demand based on analysis of a power draw signal and the generated device-based demand forecasting;
• and
• determine whether the generated demand forecast for the building is to peak in a near future, based on threshold values of at least one of generated device-based demand forecasting, power price or cost information, and user behavior analysis.

A non-transitory computer readable medium having stored therein a program for making a computer execute a method of managing energy, the method comprising:

• receiving power load information from a data collection system located at a building and using a cloud analysis layer that employs machine-learning and artificial intelligence for optimization control;
• analyzing the received power load information to disaggregate load waveform signals and identify device-based power loads by use of a neural network to perform historical device demand and performance analysis to generate device-based demand forecasting;
• generating demand forecasts for the building to mitigate peak demand based on analysis of a power draw signal and the generated device-based demand forecasting;
• and
• determining whether the generated demand forecast for the building is to peak in a near future, based on threshold values of at least one of generated device-based demand forecasting, power price or cost information, and user behavior analysis.