Short-term load forecasting can provide information which is applicable for the possible energy interchange with other utilities. Load forecasting is also advantegeous for system security, in fact if applied to the system security assessment problem, it can provide valuable information to detect many vulnerable situations in advance. In addition if the work environment is in a hospital reality, where a continuous energy and electricity utilization is required, all the problems previously listed are amplified and of a greater importance, because of the continuous use of new technological instruments. In this study a neural network approach for the hospital energy load forecast is illustrated .The data sets belong to the University Eye Clinic of Genoa, S. Martino Hospital, Genoa, Italy, and to the Department of Internal Medicine and Medical Specialties (DIMI) of the University of Genoa, Italy. These two environments represent different approaches in patient treatment and this study aims to determine if the same tool is beneficial in load forecasting for both wards. In both realities the presented approach reached a target of more than 75% of correct forecasts.
Short-Term Load Forecasting in Hospital Systems
BERTOLINI, SIMONA;MASSUCCO, STEFANO;SILVESTRO, FEDERICO;GRILLO, SAMUELE;GIACOMINI, MAURO
2013-01-01
Abstract
Short-term load forecasting can provide information which is applicable for the possible energy interchange with other utilities. Load forecasting is also advantegeous for system security, in fact if applied to the system security assessment problem, it can provide valuable information to detect many vulnerable situations in advance. In addition if the work environment is in a hospital reality, where a continuous energy and electricity utilization is required, all the problems previously listed are amplified and of a greater importance, because of the continuous use of new technological instruments. In this study a neural network approach for the hospital energy load forecast is illustrated .The data sets belong to the University Eye Clinic of Genoa, S. Martino Hospital, Genoa, Italy, and to the Department of Internal Medicine and Medical Specialties (DIMI) of the University of Genoa, Italy. These two environments represent different approaches in patient treatment and this study aims to determine if the same tool is beneficial in load forecasting for both wards. In both realities the presented approach reached a target of more than 75% of correct forecasts.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.