Demand subscription services-an iterative dynamic programming for the substation suffering from capacity shortage

The iterative dynamic programming (IDP) is presented in this paper to carry out the demand subscription services (DSS) for reducing the peak load of the substation, which is suffering from capacity shortage. The optimal or near optimal schedule of the interruptible load can be obtained by the enumerative search structure of the algorithm. Besides, the shortcoming of the enumerative approach, in which enormous memory is needed, can also be circumvented in light of the iterative procedure. Moreover, for avoiding the influence of the uncertainties of the practical load on the results of the IDP, the heuristic inference rules (HIR) are introduced in the paper. The approach cannot only adjust the schedule of the interruptible load to enhance the robustness for the uncertainties but also possess the ability of real-time operation. Three cases of demand subscription services are implemented through the proposed algorithms. The results show that the interruptible load scheduling can reduce the system load effectively and the load capacity reduced by the DSS follows close on the trajectory of the peak load.