SYSTEM AND METHODS FOR POWER SYSTEM FORECASTING USING DEEP NEURAL NETWORKS

A method of managing energy by use of processing logic that comprises a load processor as a cloud service is provided. The method includes receiving power load information from a data collection system located at a building and using a cloud analysis layer that employs machine-learning and artificia...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Kvam, Jacques, Serven, Danny
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING CONTROL OR REGULATING SYSTEMS IN GENERAL CONTROLLING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES FUNCTIONAL ELEMENTS OF SUCH SYSTEMS MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS PHYSICS REGULATING SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Beschreibung
Zusammenfassung:	A method of managing energy by use of processing logic that comprises a load processor as a cloud service is provided. The method includes 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.