Nonlinear optimal power flow with intertemporal constraints

This letter describes an interior point dynamic optimal power flow (OPF) algorithm and illustrates its application to a model network that includes large energy-intensive consumers such as metal smelters that are able to reschedule demand to reduce electricity cost subject to meeting the day's production quota. Although the behavior predicted by the algorithm is no surprise (those consumers whose demand is price sensitive reschedule their power purchases to periods of lower energy cost), its efficiency demonstrates the power of the approach. Relaxation of intertemporal and operational constraints leads to an algorithm in which an inner loop rapidly solves a series of relatively small quadratic programming problems via an interior point method while an outer loop is performing computations analogous to an iterative load flow calculation.