Monthly Peak-Shaving Control Strategies and Economic Analysis of an Ice-Storage Air-Conditioning System for Metro Stations

Abstract

The energy consumption and electricity cost of air-conditioning systems in metro stations keep rising with the expansion of rail transit. Ice thermal-energy storage (ITES) shifts cooling load to off-peak hours, yet existing studies mostly optimize ice-storage operation on a daily scale and rarely address multi-chiller load distribution, the coordination of the large and small systems of a station, or monthly peak shaving adapted to the two-part electricity tariff. For a standard metro station with platform screen doors in Wuxi, China, the annual hourly cooling loads of the large and small systems are simulated with DeST 2.0, and energy-consumption models of the chillers, multi-split units, and pumps are established. A two-layer monthly peak-shaving framework is then proposed: for the large system, a balanced load-distribution strategy and three stored-cooling allocation schemes (base-load chiller priority, cold-storage priority, and peak shaving) integrated via a monthly load-baseline switching model; for the small system, three annual regulation strategies. The balanced load-distribution strategy saves 0.49–14.90% of energy compared with full-load operation; the combined cold-storage-priority and peak-shaving strategy reduces the monthly demand charge by 15.69% and the annual electricity cost by 2.32% versus the single cold-storage-priority strategy; the ice-storage scheme cuts the annual energy cost by 23.02% versus the conventional system, with peak-shifting and valley-utilization ratios of 56.89% and 39.75%; and the energy-efficiency-priority strategy lowers the small-system energy consumption, operating cost and carbon emission by 8.19% and 16.90%. As these strategies are derived from the load profile and tariff structure of the case station, their applicability to stations with different conditions requires further validation.