Title :
Residential micro-hub load model using neural network
Author :
Isha Sharma;Claudio Cañizares;Kankar Bhattacharya
Author_Institution :
Energy and Environmental Sciences Directorate, Oak Ridge National Laboratory, Tennessee, USA 37831
Abstract :
This paper presents the modeling of a residential micro-hub load based on real measurements and simulation data obtained using the Energy Hub Management System (EHMS) model of a residential load. A neural network (NN) is used to estimate the load model as a function of time, temperature, peak demand, and energy price. Different NN training approaches are compared to determine the best function to be used, based on the available data. Also, the number of hidden layer neurons are varied to obtain the best fit for the NN model. The results show that the proposed NN model is able to properly represent the behavior of an actual residential micro-hub.
Keywords :
"Artificial neural networks","Load modeling","Training","Data models","Mathematical model","Home appliances","Optimization"
Conference_Titel :
North American Power Symposium (NAPS), 2015
DOI :
10.1109/NAPS.2015.7335091