Retrofitting centralized air compressor stations with end-use-aware predictive set-pressure control using a physics-constrained pressure-drop model

Compressed air systems usually run at a constant set pressure well above the end-use requirement; the excess margin is wasted energy. A lightweight hierarchical nonlinear model predictive control (NMPC) scheme, retrofitted to the sequencing controller of a centralized compressor station typical of small and medium-sized plants, lowers the set pressure as far as the end-use requirement allows. It uses only two pressure gauges (receiver and one critical end-use point) and compressor data, without flow meters or piping surveys. The end-use pressure is predicted by a low-order pressure-drop model identified by least squares under stability, damping and steady-state equilibrium constraints, which serve use rather than accuracy: they let the measured pressure drop be held over the horizon with unit gain. Validated in three stages (plant data, a pipe-network simulator checked against measurements, and the actual controller, at most 1.41 s per update), the NMPC meets the required pressure under real demand and reduces the estimated annual energy consumption by 2.8 % relative to the current constant operation (9.3 % relative to 0.70 MPa). A PID cascade with the same gauge saves about as much only when tuned by a standard rule at its recommended setting from a constant-load step test, difficult in an operating plant; the NMPC needs no such test and keeps its performance with its initial model and default weights after plant expansion and network split. The margin becomes a design parameter instead of a fixed excess, and the controller's signals show where the supply system lacks headroom.