Auf einer Beschränkten Boltzmannmaschine Basiertes Quellentrennungsmodell mit Anwendung auf die Lastentrennung

Details

Veröffentlichungs-Nr.

EP4040338

Aktenzeichen

EP21205146

Anmeldetag

28. Oktober 2021

Veröffentlichung

15. Januar 2025

Erteilung

15. Januar 2025

Rechtsraum

EP

IPC

G06N3/044G06N3/045G06N3/047G06N3/09G06N3/096// G06Q50/06

Abstract

Load disaggregation is useful for both the consumers and producers of energy. The present-day supervised learning models for load disaggregation necessitate the learning of models for every appliance load of interest, which incurs high computational costs. Embodiments of the present disclosure implement a Restricted Boltzmann Machine (RBM) based source-separation model with application to load disaggregation of appliances of interest. Representations of appliance of interest are learnt, between the power aggregate data and the appliance signatures, to output the mapping of data representations on the appliance signatures, for load disaggregation. Discriminative ability for each load/appliance of interest is achieved by adding the free energies of softmax layers of the RBM on other loads/appliance, as a discriminating gradient to the approximate gradients obtained on the load under consideration.

Anmelder

Firma

Tata Consultancy Services Limited

Land

🇮🇳 Indien

Fachgebiete