Abstract—In this work the application of Mixed Integer Linear Programming (MILP) techniques is proposed for choosing the optimal topology of an air compressor room, while (i) focusing on energy efficiency and (ii) keeping the input power to the lowest value. Usually the proposal of the best configuration (type of machines, size and number) is driven by the experience of the personnel performing the assessment, according to his own knowledge of the available products/machines on the market. The paper proposes the formulation of two optimization prob- lems which enable (i) to perform the best configuration of a com- pressor room, according with an available machines database; (ii) to ensure that the best choice implies the minimization of the input power for the compressor room, thus, the minimum consumption for the end-user. The presented formulations are tested using both simulated and real case studies, showing how a higher level of knowledge of the flow profile can help in the reduction of the energy consumption. It will be also demonstrated that important energy savings improvements can be obtained if we compare the choices derived from our methodology with real compressor rooms, whose choice was done without applying such method, as it may happen on the market.
Mixed-integer linear programming for the optimal design and management of air compressor rooms
ANGLANI, NORMA
2014-01-01
Abstract
Abstract—In this work the application of Mixed Integer Linear Programming (MILP) techniques is proposed for choosing the optimal topology of an air compressor room, while (i) focusing on energy efficiency and (ii) keeping the input power to the lowest value. Usually the proposal of the best configuration (type of machines, size and number) is driven by the experience of the personnel performing the assessment, according to his own knowledge of the available products/machines on the market. The paper proposes the formulation of two optimization prob- lems which enable (i) to perform the best configuration of a com- pressor room, according with an available machines database; (ii) to ensure that the best choice implies the minimization of the input power for the compressor room, thus, the minimum consumption for the end-user. The presented formulations are tested using both simulated and real case studies, showing how a higher level of knowledge of the flow profile can help in the reduction of the energy consumption. It will be also demonstrated that important energy savings improvements can be obtained if we compare the choices derived from our methodology with real compressor rooms, whose choice was done without applying such method, as it may happen on the market.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
