The paper presents the results of a preliminary electric energy consumption analysis carried out on a manufacturing company operating in the Central Italy in the aeronautics and industrial sectors. Objective of this study is the development of a Multiple Linear Regression (MLR) model to predict and analyse daily electricity consumptions. The dependent variable (electricity demand) is function of different parameters referring to outdoor temperature (which influences the energy request for cooling) and production data available in the company database. Many preliminary MLR models were developed, by considering different parameters. The outcome of the study is the creation of a 5 parameters MLR model able to simulate the electricity demand with less than 7 % error. Considering the accuracy of this model, next aim of the study is his application to the monitoring of electricity demand, aiming to detect malfunctions and inefficiencies.
Development of Regression Models to Predict Energy Consumption in Industrial Sites: The Case Study of a Manufacturing Company in the Central Italy
Moretti, Elisa
Writing – Original Draft Preparation
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2019
Abstract
The paper presents the results of a preliminary electric energy consumption analysis carried out on a manufacturing company operating in the Central Italy in the aeronautics and industrial sectors. Objective of this study is the development of a Multiple Linear Regression (MLR) model to predict and analyse daily electricity consumptions. The dependent variable (electricity demand) is function of different parameters referring to outdoor temperature (which influences the energy request for cooling) and production data available in the company database. Many preliminary MLR models were developed, by considering different parameters. The outcome of the study is the creation of a 5 parameters MLR model able to simulate the electricity demand with less than 7 % error. Considering the accuracy of this model, next aim of the study is his application to the monitoring of electricity demand, aiming to detect malfunctions and inefficiencies.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
