Most of the production facilities in Europe make use of compressed air to drive equipment for manufacturing and Compressed Air Systems (CAS) account for about 10% of the total electrical energy consumption of European industries. Therefore, reducing CAS energy consumption is a crucial task to meet the European goals of improving energy efficiency and reducing environmental impact of the industrial sector. This work is part of a wider research activity aimed at developing a strategy to optimize the energy use in CAS. In particular, this paper shows the importance of monitoring energy consumption and control energy use in compressed air generation, to enable energy saving practices, enhance the outcomes of energy management projects, and to guide industries in energy management. We propose a novel procedure in which measured data are compared to a baseline obtained through mathematical modelling (i.e. regression functions) to enable faults detection and energy accounting, through the use of control charts (i.e. variations' control and the Cumulative Sums). The effectiveness of the proposed methodology is demonstrated in a case study, namely the compressed air system of a pharmaceutical manufacturing plant.
New efficiency opportunities arising from intelligent real time control tools applications: The case of compressed air systems' energy efficiency in production and use
Bonfa F.;Benedetti M.;
2019-01-01
Abstract
Most of the production facilities in Europe make use of compressed air to drive equipment for manufacturing and Compressed Air Systems (CAS) account for about 10% of the total electrical energy consumption of European industries. Therefore, reducing CAS energy consumption is a crucial task to meet the European goals of improving energy efficiency and reducing environmental impact of the industrial sector. This work is part of a wider research activity aimed at developing a strategy to optimize the energy use in CAS. In particular, this paper shows the importance of monitoring energy consumption and control energy use in compressed air generation, to enable energy saving practices, enhance the outcomes of energy management projects, and to guide industries in energy management. We propose a novel procedure in which measured data are compared to a baseline obtained through mathematical modelling (i.e. regression functions) to enable faults detection and energy accounting, through the use of control charts (i.e. variations' control and the Cumulative Sums). The effectiveness of the proposed methodology is demonstrated in a case study, namely the compressed air system of a pharmaceutical manufacturing plant.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
