Stochastic Optimal Power Generation Scheduling

Abstract

Optimal power (load) scheduling is an important problem for any electric utility system. Its importance has been further enhanced with the development of large integrated power systems. The solution of optimal power scheduling problem gives generation schedules at various generating plants, such that power demand is met at minimum possible operating cost and system constraints are satisfied. The problem has assumed increasingly higher importance and priority as the operating costs continue to escalate and the main thrust of the system analysts being on the conservation of conventional fuels such as coal and oil. For these reason, the optimal power scheduling problem still continues to be an important subject for carrying out extensive research for finding newer algorithms and methods for achieving the above mentioned objectives. Early work in this area was that of Kirchmayer in fiftees who solved an all-thermal system problem employing coordination equations derived by the Lagrange multiplier technique. In this formulation, the effects of the equality and inequality constraints imposed by the transmission and generating systems were either approximated or completely ignored. Carpentier in 1962 for the first time advanced an exact formulation of an all thermal system dispatch problem, taking into consideration the several equality and inequality constraints of the systems, which were not considered by the earlier researchers. Subsequently, several algorithms for solution were proposed in the literature to solve the problems as formulated by carpentier. Despite the extensive research focusing on optimal power scheduling, most of the efforts to date have been mainly centred around development of deterministic models applicable to steady state conditions. The systems data has normally been assumed to be known with complete certainty i.e. deterministic. However, in practice the power demand and water inflow at various hydroplants do vary randomly with time.