Compressors can be considered as one of the most important utilities in industrial processes. Around 10–
14 percent of the electricity consumption in industry was used to produce compressed air. So, in industrial
facilities, compressors are the largest energy-consuming equipment. Therefore, energy saving in
multi-compressor systems (MCS) is very challenging. In this paper, a new symbolic model based on multi
objective Jaya algorithm for the MCS is proposed. The proposed model considered an optimal electrical
power consumption (EPC) as well as optimal life span while maintaining the demanded compressed
air flow during load change. The proposed model selected compressors that would meet the demanded
air flow by adjusting their partial load ratio (PLR) for each changeable variable speed drive compressor
(VSDC). This study has optimized the operating period for each compressor based on the optimal power
consumption of MCS as well as optimal life span of each compressor. Evolutionary multi-objective Jaya
algorithm is proposed to solve the optimization problem. Furthermore, Grey Wolf optimizer has been
used and its results have been compared to show that MO-Jaya showed better performance with the proposed
problem. Different practical cases of study have been considered and analyzed showing that the
multi-objective optimization model could dramatically reduce consumption costs and increase machine’s
life span. Besides, the maintenance schedule of each compressor could be predicted and planned based on
the MCS schedule. Variant air flow has been applied to test the effectiveness of the proposed model. |
