Dynamic economic dispatch in deregulated systems

Scheduling of power transactions in deregulated environments was studied as a static problem, in which transactions in successive temporal intervals were presented as exclusive events (i.e. transactions at a specific temporal interval were a function of the state of the system at that particular interval). However, if we consider dynamic scheduling constraints such as minimum up/down times, minimum/maximum generating capacity, ramping constraints, crew constraints, fuel constraints and so on, the marker transaction in one temporal interval will be a function of decisions in other intervals, In this paper we analyse the effect of dynamic constraints on power transactions in deregulated environments. We calculate transition states using successive dynamic programming, and apply the Newton method to calculate optimal states within a utility for a given set of transactions Network flow constraints are considered by using a DC load flow model, The results for a three utility system are presented with an optimization horizon of 24 hours. (C) 1997 Elsevier Science Ltd.