Method for the computer-assisted modeling of a wind power installation or a photovoltaic installation with a feed forward neural network

US10133981B2 · kind B2 · utility

Assignee

• Siemens Aktiengesellschaft · DE

Inventors

• Jochen Cleve · Middelfart, DK
• Ralph Grothmann · Munich, DE
• Kai Heesche · Munich, DE
• Christoph Tietz · Ottobrunn, DE
• Hans Zimmermann · Mönchaltorf, CH

Key dates

• Filing date: Jul 24, 2012
• Grant date: Nov 20, 2018
• Expiry date: Jul 3, 2035

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N3/09
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

Disclosed is a method for the computer-assisted modeling of a technical system. One or more output vectors are modeled dependent on one or more input vectors by the learning process of a neural network on the basis of training data of known input vectors and output vectors. Each output vector comprises one or more operating variables of the technical system, and each input vector comprises one or more input variables that influence the operating variable(s). The neural network is a feedforward network with an input layer, a plurality of hidden layers, and an output layer. The output layer comprises a plurality of output clusters, each of which consists of one or more output neurons, the plurality of output clusters corresponding to the plurality of hidden layers. Each output cluster describes the same output vector and is connected to another hidden layer.