Optimization and implementation of a load control scheduler using relaxed dynamic programming for large air conditioner loads

This paper presents the optimization and implementation of a relaxed dynamic programming (RDP) algorithm to generate a daily control scheduling for optimal or near-optimal air conditioner loads (ACLs). The conventional control mode for ACL includes demand control, cycling control, and timer control, to assist customers for saving electricity costs. The proposed load control scheduler (LCS) scheme supports any combination of these three control types to save costs optimally during the dispatch period. Microprocessor hardware techniques were applied to carry out the proposed strategy for realistic application. The Visual C++ language was adopted as the developing tool to carry out the proposed work. Field tests of controlling air conditioners located in the campus of National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan, were tested on-site to demonstrate the effectiveness of the proposed load control strategy. The results show that interruptible load scheduling can reduce the system load effectively, and the load capacity reduced by the proposed load control strategy follows closely the trajectory of the peak load.