Artificial Neural Network Application to Load Forecasting in a Large Hospital Facility

被引：0

作者：

Bagnasco, A. ^{[1
]}

Saviozzi, M. ^{[1
]}

Silvestro, F. ^{[1
]}

Vinci, A. ^{[1
]}

Grillo, S. ^{[2
]}

Zennaro, E. ^{[3
]}

机构：

[1] Univ Genoa, DITEN IEES Lab, Genoa, Italy

[2] Politecn Milan, Dipartimento Elettron Informaz & Bioingn, Milan, Italy

[3] Univ Roma La Sapienza, Dept Elect Engn, Rome, Italy

来源：

2014 INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS (PMAPS) | 2014年

关键词：

Load forecasting; artificial neural network; distributed generation; smart grids;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

A Smart Grid approach to electric distribution system management needs to front uncertainties in generation and demand thus making forecasting an up-to-date area of research in electric energy systems. This works aims to propose a day-ahead load forecasting procedure for a medium voltage customer. The load forecasting is performed through the implementation of an artificial neural network (ANN). The proposed multi-layer perceptron ANN, based on backpropagation training algorithm, is able to take as inputs: loads, data concerning the type of day (e.g. weekday/holiday), time of the day and weather data (e.g. temperature, humidity). This procedure has been tested to predict the loads of a large university hospital facility located in Rome.

引用

页数：6