Publication

Load forecasting with neural nets: prediction of the hourly load with a time horizon of up to seven days-a common project of EOS, EPFL and ABB

Alain Germond
1996
Journal Articles

Abstract

This article discusses the forecasting of load for a period varying from an hour to a week. As usual for the modelling and prediction of nonlinear processes, the use of artificial neural nets appears very promising. In the project described, measured loads for the past seven days, those for the two preceding days, maxima and minima of average temperatures of the previous day, and predicted day temperatures were used as input values, with the day of the week and day of the year as indicators. The load and temperature are modelled separately. An automated method is used for online testing

Official source

https://infoscience.epfl.ch/entities/publication/58b89dd1-7417-4834-8dc3-f4b6eb43d9c9

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Alain Germond
1996
Journal Articles

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/58b89dd1-7417-4834-8dc3-f4b6eb43d9c9

About this result

Related concepts (32)

Convolutional neural network

Convolutional neural network (CNN) is a regularized type of feed-forward neural network that learns feature engineering by itself via filters (or kernel) optimization. Vanishing gradients and exploding gradients, seen during backpropagation in earlier neural networks, are prevented by using regularized weights over fewer connections. For example, for each neuron in the fully-connected layer 10,000 weights would be required for processing an image sized 100 × 100 pixels.

Recurrent neural network

A recurrent neural network (RNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. In contrast to uni-directional feedforward neural network, it is a bi-directional artificial neural network, meaning that it allows the output from some nodes to affect subsequent input to the same nodes. Their ability to use internal state (memory) to process arbitrary sequences of inputs makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition.

Artificial neural network

Artificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.

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Load forecasting with neural nets: prediction of the hourly load with a time horizon of up to seven days-a common project of EOS, EPFL and ABB

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